The Analysis of Company Business Processes - IS MUNI

FACULTY OF ECONOMICS AND ADMINISTRATION

The Analysis of Company Business

Processes

Master's Thesis

MONASHEV MIKHAIL

The Supervisor: Ing. Jaromír Skorkovský, CSc.

Business Management

Brno 2020

MUNIECON

MASARYKOVA UNIVERZITAFaculty of Economics and Administration

Lipová 41a, 602 00 BrnoIČ: 00216224

DIČ: CZ00216224

Master'sthesis description

Academic year: 2020/2021

Student: Mikhail Monashev

Programme: Business Management

Title of the thesis/dissertation: The analysis of company business processes

Title of the thesis in English: The analysis of company business processes

Thesis objective, procedure and methods used: Main aims: Process identification, description, analysis, whichinvolves the overall narrative of the organization, including itsstrategy and process architecture. Following review, the sug-gestion of process redesign will be made. Used tools: Theoryof constraints and Lean Six Sigma methodologies

Extent of graphics-related work: According to thesis supervisor’s instructions

Extent of thesis without supplements: 60 – 80 pages

Literature: KRISHNAMOORTHI. A First Course in Quality Engineering:Integrating Statistical and Management Methods to Quality.Third edition. Boca Raton: Taylor & Francis, CRC Press, 2018.ISBN 978-1-4987-6420-9.

DUMAS, Marlon, Marsello LA ROSA, Jan MENDLING andH. A. REIJERS. Fundamentals of business process ma-nagement. Second edition. Berlin: Springer, 2018. xxxii, 527.ISBN 9783662565087.

DUMAS, MaFundamentals of burlon. Fundamentals of busi-ness process management.. Springer, 2018. ISBN 978-3-662-56508-7.

Handbook on business process management.. Edited by JanVom Brocke - Michael Rosemann. Second edition. Berlin:Springer, 2015. xvii, 727. ISBN 9783642450990.

FRED, David and David FOREST. Strategic Management:A Competitive Advantage Approach. Concepts & Cases, 2017.ISBN 978-0-13-416784-8.

GOLDRATT, Eliyahu M. Theory of constraints. Great Barring-ton: North River Press, 1990. x, 161 s. ISBN 0-88427-166-8.

Thesis supervisor: Ing. Jaromír Skorkovský, CSc.

Thesis supervisor’s department: Department of Corporate Economy

Page 1 of 2

Thesis assignment date: 2020/04/01

The deadline for the submission of Master’s thesis and uploading it into IS can be found in the academic year calendar.

In Brno, date: 2020/12/27

Page 2 of 2

Name and surname of the author: Mikhail Monashev

Master's thesis title: The analysis of company business processes

Department: Department of Corporate Economy

Master's thesis supervisor: Ing. Jaromír Skorkovský, CSc.

Master's thesis date: 2020

Abstract

The Master's Thesis is devoted to a case study of improving the performance of the XYZ Group's

Payments Domain using the methodology which merges benefits of Business Process

Management (BPM), Lean Six Sigma (LSS), and Theory of Constraints (TOC). The thesis consists

of five chapters: 1 Theoretical Overview, 2 Research Methodology, 3 Industry and Company

Overview, 4 Analysis, and 5 Recommendations. The 1 Theoretical Overview chapter critically

examines literature devoted to methods of BPM, LSS, and TOC. The 2 Research Methodology

chapter utilizes methods described in the theoretical overview to breakdown the primary research

goal into secondary objectives. The 3 Industry and Company Overview chapter describes activities

performed during the BPM life cycle's Identification stage. The 4 Analysis chapter is devoted to

describing activities conducted within the process selection, process discovery, and process

analysis stages. The 5 Recommendations chapter describes the process redesign results and

estimates the overall effect of the proposed solutions.

Keywords: Business Process Management, Lean Six Sigma, Theory of Constraints, banking,

business process, business process analysis, business process redesign

Declaration

"I certify that I have written the Master's Thesis 'The analysis of company business processes' by

myself under the supervision of Ing. Jaromír Skorkovský, CSc. and I have listed all the literary

and other special sources in accordance with legal regulations, Masaryk University internal

regulations, and the internal procedural deeds of Masaryk University and the Faculty of Economics

and Administration".

Brno, Mikhail Monashev

Acknowledgments

This Master's Thesis concludes the important stage of my life connected with my master's studies

at Masaryk University. I want to express my gratitude to all people who were by my side during

this challenging and exciting journey and helped me grow professionally and personally.

First of all, I want to thank my supervisor, Jaromír Skorkovský, for his guidance and support during

the work on my Master's Thesis. Then, I want to express my gratitude to my colleagues from the

XYZ Group's Payments Domain for their openness and assistance with the data collection to

conduct a case study. Last but not least, I want to thank my family for continuous support and

motivation during my studies.

Table of Contents

Abbreviations and Acronyms ........................................................................................................... 9

List of Figures ................................................................................................................................ 10

List of Tables .................................................................................................................................. 12

Introduction .................................................................................................................................... 13

1 Theoretical Overview .................................................................................................................. 14

1.1 The Scope of Business Process Management ...................................................................... 15

1.2 Business Process Management Lifecycle ............................................................................. 23

1.2.1 Process Identification .................................................................................................... 26

1.2.2 Process Enactment ......................................................................................................... 28

1.2.3 Process Selection ........................................................................................................... 31

1.2.4 Process Discovery ......................................................................................................... 34

1.2.5 Process Analysis ............................................................................................................ 36

1.2.6 Process Redesign ........................................................................................................... 42

2 Research Methodology ................................................................................................................ 46

3 Industry and Company Overview ................................................................................................ 48

3.1 Industry Overview ................................................................................................................ 48

3.1.1 Banking Industry ........................................................................................................... 48

3.1.2 Insurance Industry ......................................................................................................... 54

3.2 Company Overview .............................................................................................................. 57

3.2.1 Internal Environment ..................................................................................................... 57

3.2.2 Company Performance .................................................................................................. 63

3.3 Payments Domain Overview ................................................................................................ 67

4 Analysis ....................................................................................................................................... 70

4.1 Process Selection .................................................................................................................. 70

4.2 Process Discovery ................................................................................................................ 72

4.3 Process Analysis ................................................................................................................... 75

5 Recommendations ....................................................................................................................... 84

5.1 Exploit Constraints ............................................................................................................... 84

5.2 Elevate Constraints ............................................................................................................... 89

5.3 To-be State of the “Process Payments” Process ................................................................... 91

Conclusion ...................................................................................................................................... 93

List of Sources Used ....................................................................................................................... 94

List of Appendices........................................................................................................................ 100

9

Abbreviations and Acronyms

6M Machine, Methods, Material, Man, Measurement, Milieu

ANOVA Analysis of Variation

AO Authorization Officer

BAM Business Activity Monitoring

BCG Boston Consulting Group

BPM Business Process Management

BPMN Business Process Model and Notation

BPMS Business Process Management System

BPTrends Business Process Trends

BVA Business-Value-Adding

CAGR Compound Annual Growth Rate

CAM Competitive Advantage Matrix

CRT Current Reality Tree

CSF Critical Success Factor

CT Cycle Time

CZK Czech Koruna

DBMS Database Management System

DMAIC Define, Measure, Analyze, Improve, Control

EC Evaporating Cloud

EPC Event-driven Process Chain

ERP Enterprise Resource Planning

EU European Union

FRT Future Reality Tree

ICT Information and Communication Technologies

ILA Industry Lifecycle Analysis

I-ORG Individual Organization

I-PER Individual Person

IT Information Technologies

ITIL Information Technology Infrastructure Library

KPI Key Performance Indicator

LSS Lean Six Sigma

NP Net Profit

NVA Non-Value-Adding

OE Operating Expense

PCF Process Classification Framework

PE Payments Engine

PLC Public Limited Company

PLM Process Landscape Model

PPM Product Portfolio Matrix

PPO Payments Processing Officer

ROI Return on Investment

SCOR Supply Chain Orientations Reference

SO Secondary Objective

TOC Theory of Constraints

TQM Total Quality Management

TRIZ Theory of Inventive Problem Solving

UDE Undesirable Effect

VA Value-Adding

10

List of Figures

Figure 1: The general model of a process ...................................................................................... 14 Figure 2: The six core elements of BPM ....................................................................................... 15 Figure 3: The four types of information used in BPM .................................................................. 20 Figure 4: The Model of Expertise in the Context of BPM ............................................................ 21

Figure 5: Business Process Management Lifecycle (Dumas et al., 2018) .................................... 23 Figure 6: The integrated BPM Lifecycle model ............................................................................ 25 Figure 7: An example of the strategy map .................................................................................... 27 Figure 8: A process architecture with three levels ........................................................................ 27 Figure 9: The Devil’s Quadrangle ................................................................................................. 29

Figure 10: Calculation of a yield of single process activity .......................................................... 30 Figure 11: The BCG’s Product Portfolio Matrix ........................................................................... 32 Figure 12: An example of the Pareto Chart (Process Selection) ................................................... 33 Figure 13: A process of process selection ..................................................................................... 34 Figure 14: Probability calculation for different types of process fragments ................................. 39

Figure 15: A template of the Ishikawa Diagram ........................................................................... 39 Figure 16: An example of the Pareto Chart (Process Analysis) .................................................... 40

Figure 17: An example of the Current Reality Tree ...................................................................... 41 Figure 18: Classification of LSS tools and techniques .................................................................. 41 Figure 19: Dependencies between required process changes and industry lifecycle stage ........... 43 Figure 20: An example of the Evaporating Cloud ......................................................................... 43

Figure 21: TRIZ systematic approach to problem-solving ............................................................ 44 Figure 22: An example of the Future Reality Tree ........................................................................ 45

Figure 23: The value chain of the commercial bank ..................................................................... 49 Figure 24: Banking Process Classification Framework ................................................................ 50 Figure 25: Competitive Advantage Matrix of the EU-28 banking industry .................................. 51

Figure 26: Dynamics of loans in the EU-28 from 2015 to 2019, € trillion ................................... 52 Figure 27: Dynamics of assets in the EU-28 from 2015 to 2019, € trillion .................................. 53

Figure 28: The banking industry lifecycle ..................................................................................... 54 Figure 29: Competitive Advantage Matrix of the EU-28 insurance industry ............................... 55

Figure 30: Dynamics of insurance premiums in the EU-28 from 2014 to 2018, € trillion ........... 56 Figure 31: Distribution of specialized segment companies’ shares in the insurance market ........ 56 Figure 32: The insurance industry lifecycle .................................................................................. 57 Figure 33: Bank-insurance KPIs of the XYZ Group in 2019 ........................................................ 60

Figure 34: The Process Landscape Model of the XYZ Group ...................................................... 61 Figure 35: Dynamics of the XYZ Group’s loans from 2015 to 2019, € billion ............................ 65 Figure 36: A PPM of the debt instruments market segment.......................................................... 65 Figure 37: Dynamics of the XYZ Group’s assets from 2015 to 2019, € billion ........................... 66 Figure 38: A PPM of the transactional operations market segment .............................................. 66

Figure 39: Dynamics of the XYZ Group’s insurance premiums from 2015 to 2019, € billion .... 67 Figure 40: A PPM of the insurance market ................................................................................... 67 Figure 41: A strategy house of the Payments Domain .................................................................. 68

Figure 42: A “Manage Transactions” process ............................................................................... 68 Figure 43: The process performance measures and the XYZ Group’s KPIs ................................ 70 Figure 44: Weights of the “Manage Transactions” process’ sub-processes in its cycle time ....... 71 Figure 45: Pareto Chart for “Process Payments” process.............................................................. 76

Figure 46: The Ishikawa Diagram (process cycle time) ................................................................ 81 Figure 47: A process knowledge and the influence of the work experience ................................. 82 Figure 48: The Current Reality Tree (Solution 1) ......................................................................... 84

Figure 49: The Evaporating Cloud for rework loop (as-is state) ................................................... 85 Figure 50: The Future Reality Tree (Solution 1) ........................................................................... 86

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Figure 51: The Current Reality Tree (Solution 2) ......................................................................... 86 Figure 52: The Future Reality Tree (Solution 2) ........................................................................... 87

Figure 53: The Current Reality Tree (Solution 3) ......................................................................... 88 Figure 54: The Future Reality Tree (Solution 3) ........................................................................... 88

Figure 55: The Current Reality Tree (Solution 4) ......................................................................... 89 Figure 56: The Future Reality Tree (Solution 4) ........................................................................... 90 Figure 57: A factor analysis of the simultaneous implementation of the proposed solution ........ 92 Figure 58: Correlation between work experience and personal productivity .............................. 120 Figure 59: Correlation between work experience and error rate ................................................. 121

12

List of Tables

Table 1: The major issues in BPM implementation ...................................................................... 15 Table 2: The six activities of business process strategic alignment .............................................. 16 Table 3: The eight business process government roles ................................................................. 17 Table 4: The five focusing steps of the Theory of Constraints ..................................................... 19

Table 5: ICT capabilities and process information types .............................................................. 20 Table 6: The four primary values of BPM .................................................................................... 22 Table 7: A comparison of different BPM lifecycle models........................................................... 24 Table 8: Stages of the integrated BPM Lifecycle model ............................................................... 25 Table 9: Stages of the BPM lifecycle and associated methods ..................................................... 26

Table 10: Process model quality aspects and assurance activities ................................................ 36 Table 11: The seven types of waste ............................................................................................... 37 Table 12: Cycle time and cost calculation for different types of process fragments..................... 38 Table 13: Stages of the BPM Lifecycle and secondary research objectives ................................. 46 Table 14: Research objectives and associated methods ................................................................ 47

Table 15: The largest banks of the EU in 2019 ............................................................................. 50 Table 16: Total market assets shares of the specialized business segment competitors ............... 51 Table 17: The selected companies’ market shares in the debt instruments segment .................... 52

Table 18: The selected companies’ market shares in the transactional operations segment ......... 53 Table 19: Sustainable profitable growth KPIs of the XYZ Group in 2019 ................................... 58 Table 20: Client centricity KPIs of the XYZ Group in 2019 ........................................................ 60

Table 21: Financial indicators of the XYZ Group from 2015 to 2019, € million ......................... 64 Table 22: Process profile of the “Manage Transactions” process ................................................. 69 Table 23: An average cycle time of the “Manage Transactions” process in 2019 ........................ 71

Table 24: A process health ratio of the “Manage Transactions” process’ sub-processes ............. 72 Table 25: A process profile of the “Process Payments” process ................................................... 75

Table 26: Cycle time of the “Process Payments” process activities, sec ...................................... 76 Table 27: A value stream analysis of the “Process Payments” process ........................................ 76

Table 28: Message flows in the “Process Payments” process ....................................................... 77 Table 29: Influence of rework the selected activities’ cycle time ................................................. 78

Table 30: A daily cycle time of the “Process Payments” process activities, hrs ........................... 78 Table 31: A daily working and idle time per process participant .................................................. 78 Table 32: A cycle time of the process activities ............................................................................ 79 Table 33: A sensitivity analysis ..................................................................................................... 80

Table 34: Identification of problems ............................................................................................. 82 Table 35: Root causes influencing the process cycle time ............................................................ 83

Table 36: An average duration of the “Initiate investigation” activity.......................................... 87 Table 37: A process profile of the “Process Payments” process (to-be state) ............................... 91 Table 38: An average cycle time of the “Manage Transactions” process (to-be state) ................. 92

Table 39: A working time distribution between resources of the process ..................................... 92 Table 40: An operating leverage dynamics in the banking industry (specialized businesses) .... 107 Table 41: A CIR dynamics in the banking industry (specialized businesses) ............................. 109

Table 42: An operating leverage dynamics in the insurance industry (specialized businesses) . 111

Table 43: A CIR dynamics in the insurance industry (specialized businesses) .......................... 112 Table 44: Calculation of the average duration of the “Correct error” activity execution ........... 119 Table 45: Calculation of the average error rate of the “Correct error” activity ........................... 120

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Introduction

In a highly volatile and uncertain environment, companies constantly adjust their behavior to

outperform competitors and increase their customer base. Such behavior adjustments are only

possible through ongoing organizational changes and innovations. However, due to resource

constraints, companies have to innovate smart and prioritize improvement areas based on

consistent and efficient methodology. A case study described in the thesis aims to prove the high

effectiveness of BPM as a methodology for smart innovating. It aims to improve the overall

performance of the XYZ Group’s Payments Domain by redesigning its bottleneck business

process.

The methodology implemented in the case study is based on a thorough examination of BPM-

related concepts, as described in the 1 Theoretical Overview chapter. Apart from BPM itself

defined as a company capability and a set of activities performed along the BPM lifecycle, the

theoretical overview includes the description of other managerial tools and techniques that can

support the BPM implementation. The most attention is given to the description of tools and

techniques commonly associated with the Theory of Constraints (TOC) and Lean Six Sigma

(LSS).

The 2 Research Methodology chapter utilizes methods described in the theoretical overview. It

sets secondary research objectives, which are prerequisites for achieving the primary research goal

of improving the overall performance of the XYZ Group’s Payments Domain by redesigning its

bottleneck business process. The secondary objectives are closely related to the BPM life cycle

stages and are supported by data collection techniques and data analysis procedures described in

the theoretical overview.

The 3 Industry and Company Overview chapter is devoted to the overview of the XYZ Group and

its Payments Domain to prepare a basis for selecting a bottleneck business process that should be

redesigned to improve the Domain's overall performance. The chapter begins with analyzing the

external environment presented by the markets where the XYZ Group competes. The XYZ Group's

internal environment is then described with special attention given to its strategy and process

architecture. The chapter finishes with an overview of the Payments Domain that shares the

approach implemented to the Company Overview.

The 4 Analysis chapter describes activities performed during the Process Selection, Process

Discovery, and Process Analysis to select the bottleneck business process and identify root causes

that influence the process performance. Methods of LSS and TOC described in the theoretical

overview are actively implemented to achieve these objectives.

The 5 Recommendations chapter focuses on developing solutions to improve process performance

by mitigating the negative effects of root causes identified during the process analysis.

Simultaneous implementation of the proposed solutions results in the process redesign project,

which includes the to-be process model and estimation of its impact on the Payments Domain's

overall performance.

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1 Theoretical Overview

This chapter is devoted to a literature review of concepts related to Business Process Management

(BPM). It describes BPM through its core elements (i.e., critical success factors) and activities

conducted along the BPM lifecycle. BPM is considered a broad managerial approach that utilizes

tools and techniques of other methodologies such as Lean Six Sigma (LSS) and Theory of

Constraints (TOC).

BPM can be perceived in several ways. According to Reijers et al. (2010), some people narrowly

associate BPM with a set of process-oriented tools and techniques, while others consider BPM as

a management concept. Authors themselves stick to the middle and define BPM as an integrated

management methodology that includes a set of practices to change business processes

incrementally or fundamentally.

The empirical study conducted by Skrinjar et al. (2008) has proven that “business process

orientation has a strong indirect impact on financial performance through non-financial

performance”. This conclusion is also supported by Hung (2006), who claims that BPM

implementation is positively associated with organizational performance.

The core concept of BPM is a business process. In general terms, the process aims to transform

inputs into the desired output and is influenced by controllable and uncontrollable factors that

originate from the internal or external environment, as presented in Figure 1.

Figure 1: The general model of a process

Source: Montgomery (2018), p. 3

Although there are many definitions of the business process, most scholars (e.g., Houy et al., 2015;

Rosemann & vom Brocke, 2015; Dumas et al., 2018; Weske, 2019) define the business process as

a set of subsequent activities undertaken to achieve a particular business goal, such as producing

and delivering goods and services to customers. Considering that management is carried out

through the implementation of specific changes to the existing system aiming to improve its output,

it can be concluded that BPM in its essence focuses on changing business processes to meet the

strategic goals of a company (e.g., to reduce costs, to increase customer satisfaction, to raise

productivity).

There are two major approaches to defining BPM in more detail: the scope-oriented approach and

the time-oriented approach. The scope-oriented approach aims to define BPM as an organizational

capability through its elements (i.e., critical success factors, CSFs). The main contributors to this

approach are Rosemann & vom Brocke (2015), who distinguish six core capabilities that lead to a

15

successful BPM implementation. The time-oriented approach aims to define BPM through its

activities and is mainly presented by BPM lifecycle models (e.g., van der Aalst, 2011; Kirchmer,

2017; Dumas et al., 2018; Weske, 2019).

1.1 The Scope of Business Process Management

Rosemann & vom Brocke (2015) suggested the framework of six core elements (i.e., CSFs)

consisted of several capability areas as presented in Figure 2 to ensure a holistic understanding of

BPM. They perceive BPM “not just as the execution of the tasks along an individual process

lifecycle”, but as “an organizational capability”.

Figure 2: The six core elements of BPM

Source: Rosemann & vom Brocke (2015), p. 111

There are other classifications of BPM CSFs in academic literature, but the framework of

Rosemann & vom Brocke (2015) is seen as the most developed one. For instance, Skrinjar &

Trkman (2013) group critical BPM practices into five CSFs of BPM: strategic alignment,

performance measurement, organizational changes, Information System support, and employee

training and empowerment. This view is narrower than the one proposed by Rosemann & vom

Brocke (2015) because it reflects only four of the six core elements leaving Culture and People

without attention.

Bandara et al. (2007) investigate the BPM scope from the opposite site and highlighted the BPM

implementation's main issues, as presented in Table 1.

Table 1: The major issues in BPM implementation

Strategic Tactical Operational

- Lack of governance

- Lack of employee buy-in

- Lack of common mind

share of BPM

- The broken link between

BPM efforts and organizational

strategy

- Lack of standards

- Weakness in the process

specification

- Lack of BPM education

- Lack of methodology

- Lack of tool support for

process visualization

- Perceived gaps between

process design and process

execution

- Miscommunication of tool

capabilities

Source: Bandara et al. (2007)

16

These issues arise from the insufficient development of the core capabilities distinguished by

Rosemann & vom Brocke (2015). On the strategic level, problems are caused by the inadequate

development of governance, strategic alignment, and culture; on the tactical and operational levels,

problems are caused by the lack of people, methods, and IT capabilities.

Each of the six core elements of BPM is described in more detail below, mainly using articles

included in “Handbook on Business Process Management” edited by Rosemann & vom Brocke

(2015) and aimed to develop their ideas on deeper levels.

Strategic Alignment

Morrison et al. (2012) define strategic alignment as “a method for understanding the nature of a

business through the correlation of business processes and strategies”. The study conducted by

Vugec et al. (2019) has shown that the alignment of BPM and Corporate Performance Management

(i.e., another name for strategic management) positively affects organizational performance.

David & David (2017) define strategic management as “the art and science of formulating,

implementing, and evaluating cross-functional decisions that enable an organization to achieve its

objectives”. According to Burlton (2015), the Enterprise level of BPTrends’ business process

management methodology can be used as a reference while describing how the strategic

management process is executed in BPM-oriented organizations. This level includes six

subsequent activities defined in Table 2.

Table 2: The six activities of business process strategic alignment

№ Activity Definition

1 Understand

Enterprise Context

An external environment analysis using various methods such as STEP-analysis,

SWOT-analysis, and Stakeholder Analysis followed by developing a business strategy

using Balanced Scorecard, Enterprise Architecture, or other methods.

2 Model Enterprise

Processes

A graphical representation of high-level processes that an organization executes to

reach its strategic goal. This representation is often called Process Landscape Model

and can be created using Reference Frameworks (e.g., ITIL, SCOR, PCF), Porter’s

Value Chain, or other methods.

3 Define Performance

Measures

According to Leyer et al. (2015), business processes' performance is “about how well

the executed processes work with regard to chosen indicators”. These indicators are

typically called Key Performance Indicators (KPIs) and should be measured for each

process presented in Process Architecture.

4 Establish Process

Governance

A set of vertical structures and lateral roles, relations, processes, and rules for

coordinating and controlling across business process activities (Lynne & Jakobson,

2015).

5 Align Enterprise

Capabilities

Determining the supporting capabilities and assets (strategic technologies, human

competencies, and physical facilities) needed to conduct the envisioned processes most

efficiently.

6 Manage Enterprise

Processes

Determining which processes are critical to the achievement of Strategic Business

Objectives and Stakeholder Value Creation.

Source: Compiled by the author based on Burlton (2015)

The perception of BPM Strategic Alignment described above is shared by Aitken et al. (2015),

who stresses that creation of the Process Architecture (i.e., the “Model Enterprise Processes”

activity) is an essential part of modeling organizational behavior (i.e., how an organization

implements its strategies). Moreover, Morrison et al. (2012) highlight the importance of aligning

strategic objectives with process performance measures.

17

Governance

The importance of process governance has previously been highlighted by Burlton (2015) as one

of the means of successful strategic implementation in BPM-oriented organizations. Scheer &

Hoffman (2015) define process governance as “the process of business process management”,

emphasizing its fundamental role as an enabler of BPM. According to Lynne & Jakobson (2015),

business process governance includes lateral relations and roles that enable coordination of BPM

implementation across the organization and assure that these activities are consistent between

various departments.

Lynne & Jakobson (2015) define informal process coordination as inefficient and propose three

formal process coordination levels. The first level is the designation of the liaison role with

responsibilities for coordinating across departments and allocating resources to execute process

redesign projects. The second level is creating a separate process coordination unit with the

responsibility to coordinate a business process, while the activities that make up the process

continue to be executed in other organizational units. The third level is to restructure the

organization so that each organizational unit is responsible for specific processes.

Sheer & Hoffmann (2015) distinguish eight business process governance roles associated with

coordination, decision-making, and support responsibilities, as presented in Table 3. By assigning

these roles to its employees, an organization assures the efficient implementation of the BPM

initiative.

Table 3: The eight business process government roles

№ Role Description

1 BPM Sponsor A senior-level manager who is committed to internally marketing BPM initiatives and

raise BPM awareness within the organization. She should also initiate, fund, and drive

BPM implementation within the organization.

2 Head of BPM A senior-level manager who is committed to the supervision and management of all BPM

activities. He/she typically leads the BPM Centre of Excellence and chairs the BPM

Steering Committee.

3 BPM Steering

Committee

Several people responsible for setting, monitoring, and directing the BPM strategy of the

enterprise.

4 BPM Centre of

Excellence

An organizational unit comprising of BPM experts responsible for developing the

organization’s BPM methodology and providing support in implementing this

methodology across organizational units (e.g., departments).

5 Business Process

Experts

Internal or external employees attached to the BPM Centre of Excellence who provide

BPM-oriented consultations to enhance the quality of business process management

activities (e.g., process redesign). Process Architect, Process Consultant, and Process

Analyst are the main sub-roles performed by Business Process Experts.

6 Process Owner An employee who is responsible for operating performance and continuous improvement

of a dedicated core process.

7 Process

Coordinator

An extended role of the Process Owner responsible for a group of business processes and

coordination between them.

8 Process Modeler An employee responsible for business process modeling and verification in compliance

with the defined BPM modeling standards (e.g., BPMN 2.0).

Source: Compiled by the author based on Sheer & Hoffmann (2015) and Lohmann & Muehlen (2015)

To sum up, business process governance's primary goal is to ensure smooth execution of BPM

activities within particular organizational units and across the organization. This goal is reached

by modifying the formal organizational structure and incorporating new roles and responsibilities

to support the execution of the BPM process.

18

Methods

Previously, BPM has been defined as an integrated management methodology, and therefore, it is

made up of a set of methods (i.e., tools and techniques). Harmon (2015) claimed that these methods

were evolving for several decades within the Quality Control Tradition, the Management

Tradition, and the IT Tradition, as presented in Appendix A. In the end, methods associated with

these traditions were integrated into the sole BPM methodology. Some methods presented in

Appendix A are described in more detail in respective parts of the 1.2 Business Process

Management Lifecycle section. Lean Six Sigma (LSS), the most recent methodology of the

Quality Control Tradition, and Theory of Constraints (TOC), which can be included in the

Management Tradition, are described in more detail below for several methods associated with

these methodologies support activities of BPM lifecycle. However, the IT Tradition methods are

given less attention because the thesis is devoted to the Business Management aspect of BPM.

Lean Six Sigma

LSS is an integrated managerial approach that combines tools and techniques commonly used

within Six Sigma and Lean manufacturing methodologies. Pioneered by Motorola in the 1980s

and embraced by General Electric in the 1990s the Six Sigma can be referred to as an improvement

method that aims to eliminate variation and defects in a wide array of processes (Schroeder et al.,

2008). The methodology's name arises from its goal to achieve 3.4 defects per one million

opportunities, which means that the defect-free process inputs comprise 99.99966% of all process

inputs and lie in the range of 6 standard deviations (i.e., six sigma) from the mean result.

Six Sigma is typically described through various process methodologies. The most common

process methodology for Six Sigma is DMAIC and consists of defining, measuring, analyzing,

improving, and controlling phases. Each of the DMAIC cycle stages operates by a set of tools &

techniques described in more detail in the respective sub-sections of the 1.2 Business Process

Management Lifecycle section.

Another improvement method included in LSS is Lean manufacturing. It was developed by Taichi

Ohno and Shigeo Shigo in the 1930s (Arnheiter & Maleyeff, 2005). The core idea of Lean

manufacturing is to reduce waste and maximize the weight of value-added activities in processes

through continuous or radical process improvement. Value Stream Analysis and Waste Analysis

are the primary tools of Lean manufacturing described in more detail in the 1.2.5 Process Analysis

section.

According to Arnheiner & Maleyoff (2005), an LSS organization combines and utilizes the

strengths of both methodologies. It incorporates DMAIC cycle tools and techniques for process

improvement from Six Sigma and waste reduction techniques used in Lean manufacturing in its

practice.

Theory of Constraints

Although Harmon (2015) does not consider the TOC as one of the Managerial Tradition methods,

it seems worthwhile to include this managerial approach invented by Goldratt (1990) in the

literature review because it applies to business process improvement. In contrast with Business

Process Reengineering (included in the Management Tradition), which strives to rebuild the entire

system to achieve a breakthrough result (Bhaskar, 2018) and therefore can be called “pessimistic”,

TOC aims to utilize the system’s potential to achieve the improvement of the same scale and

therefore can be called “optimistic”.

19

Theory of Constraints “seeks to strive towards the global objective, or goal, of a system through

an understanding of the underlying cause and effect dependency and variation of the system”

(Youngman, 2009). According to TOC, the main strategic goal shared by most commercial

companies is “to make money now as well as in the future” (Goldratt, 1990). This goal is impacted

by three main measurements of TOC as follows (Goldratt 1990):

- Throughput (T) is the rate at which the system generates money through sales.

- Inventory (I) is all the money that the system invests in purchasing things that it intends to

sell.

- Operating Expense (OE) is all the money the system spends to turn Inventory (I) into

Throughput (T).

The above-mentioned measurements are used to calculate the TOC’s metrics: Net Profit (NP),

Return on Investment (ROI), and Productivity (P) using the following formulas (Youngman,

2009):

NP = T − OE;

ROI = NP

I;

P =T

OE.

One of the main ideas of TOC is that the throughput of the whole system equals the throughput of

its bottleneck (i.e., constraint of a system) that can either be tangible (i.e., physical constraint) or

intangible (i.e., policy constraint). It means that managers have to increase the throughput in the

system’s bottleneck to raise its overall throughput. To do so, managers can implement the TOC

algorithm (i.e., Five Focusing Steps of TOC) presented in Table 4.

Table 4: The five focusing steps of the Theory of Constraints

№ Focusing Step Description

1 Identify the system’s

constraint(s).

The system’s constraint(s) can be found using various tools and techniques such

as interviews with responsible employees, Pareto Analysis, etc.

2 Exploit the system’s

constraint(s).

The exploitation of a constraint can be seen either as proper utilization of the

constraint’s capacity or reducing waste (see Lean Six Sigma).

3 Subordinate everything

else to the above decision.

It has to be ensured that the subsystems are subordinated to the system.

4 Elevate the system’s

constraint(s).

Additional resources are being brought to raise the capacity of the constraint.

This action aimed to increase throughput also increases inventory through

additional investments or operating expenses.

5 Go back to step 1. Don’t

stop.

Once a constraint has been broken, then another one will arise. Therefore, the

algorithm should be repeated.

Source: Compiled by the author based on Youngman (2009)

Focusing steps presented in Table 4 can be performed using three main thinking tools of TOC: the

Current Reality Tree (CRT) used to identify the constraints, the Evaporating Cloud used to find a

proper solution for exploiting/elevating the constraint, and the Future Reality Tree (FRT) used to

simulate changes that can occur after exploiting/elevating the constraint (Goldratt, 1990). These

tools are described in more detail in the respective parts of the 1.2 Business Process Management

Lifecycle section.

20

Information Technologies

Sidorova et al. (2015) argue that there are three main ICT capabilities related to BPM: information

management, information processing, and communication. Information management capability

includes capturing, storing, and providing access to information. Information processing includes

information manipulation, presentation, and decision and action support. Communication is

concerned with human-to-human and system-to-system interaction.

Sidorova et al. (2015) also highlight the critical role of information in BPM. They suggested

distinguishing four types of BPM-related information based on its level and domain, as presented

in Figure 3.

Figure 3: The four types of information used in BPM

Source: Sidorova et al. (2015), p. 427

The authors also describe connections between three types of ICT capabilities and four types of

information, as summarized in Table 5.

Table 5: ICT capabilities and process information types

ICT

Capabilities

Information types

Instance level

business

information

Instance level

process information

Reference level

business

information

Reference level

process information

Information

Management

ERP systems and

database applications

Database

Management

Systems (DBMS),

workflow

management systems

Requirements

tracking software

Process models,

workflow

management systems

Information

Processing

ERP and workflow

management systems

Workflow systems,

performance trackers,

dashboards

ERP system Process models and

Business Activity

Monitoring (BAM)

Communication Workflow

management systems,

Business Process

Management System

(BPMS)

Workflow systems,

ERP systems

Collaboration

software (e.g., video-

conferencing)

Process maps created

by modeling tools

Source: Compiled by the author based on Sidorova et al. (2015)

21

As seen in Table 5, Enterprise Resource Planning (ERP) and workflow management systems are

the main ICT capabilities that allow BPM to use all four types of information, and hence they

should be described in more detail.

Enterprise Resource Planning (ERP) system is “a business management software that is designed

to integrate data sources and processes of an entire organization into a combined system” (Bahsaas

et al., 2015). Moreover, “ERP systems have different modules that run various business activities

such as accounting, finance, supply chain, human resources, customer information, and many

others” (Bahsaas et al., 2015). It means that some of the activities that make up business processes

(e.g., human resource management, financial management) can be directly executed within the

ERP environment. Moreover, an ERP system might be a source of information about process

execution and enable monitoring and analyzing the selected business processes.

According to Ouyang et al. (2015), workflow management provides automated support for

business processes enabled by various business modeling languages (e.g., BPMN, EPC, Petri nets).

These languages offer different business process simulation, monitoring, and execution

opportunities. Nevertheless, the description of these opportunities is beyond the thesis's scope due

to its focus on the management side of the BPM.

People

Kokkonen & Bandara (2015) proposed the Model of Expertise in the Context of BPM to break

down the People core element. The model consists of five constructs as depicted in Figure 4:

Living System Construct, Knowledge Construct, Behavioral Characteristics Construct, Context

Construct, and Decision-Making Construct.

Figure 4: The Model of Expertise in the Context of BPM

Source: Kokkonen & Bandara (2015), p. 524

Living System Construct According to Kokkonen & Bandara (2015), expertise in BPM resides

at an individual person (I-PER) and individual organization (I-ORG) levels (i.e., also referred to

as collective expertise) that taken together form a living system.

Knowledge Construct Kokkonen & Bandara (2015) claim that knowledge (i.e., structured and

used information) is the central element in their model. It is made up of explicit (i.e., codifiable)

knowledge, which can be documented, and tacit knowledge contained only in its owner's mind

22

(Szelagowski, 2019). Another categorization of BPM-related knowledge consists of process

knowledge (Hrastnik et al., 2007; Seethamraju & Marjanovic, 2009; Antunes & Tate, 2019), and

BPM knowledge, which can be referred to as the knowledge of practices applied to specific stages

of the BPM lifecycle (Antonucci, 2015; Dumas et al., 2018).

Behavioral Characteristics Construct Kokkonen & Bandara (2015) claim that the behavioral

characteristics are “key to understanding the utilization of knowledge and interaction with the

environment in which the expertise occurs”. Behavioral characteristics allow making assumptions

about the process stakeholders’ reaction to the process redesign. Supporting assumptions are

“those that indicate strategic opportunities and favorable conditions” to process redesign project

implementation, while resisting assumptions are “those that indicate threats, give rise to adverse

and dangerous conditions” to process redesign project implementation (MacRae, 2020).

Context Construct According to Kokkonen & Bandara (2015), the Context Construct includes

interrelated conditions, facts, and circumstances in which the expertise exists. These facts might

arise from either the internal or external environment and influence the expertise either on the I-

PER or I-ORG level of the living system.

Decision-Making Construct Kokkonen & Bandara (2015) divide Decision-Making Construct

into four sub-constructs: situation awareness, decision, action, and the feedback loop. Situation

awareness describes the decision-maker’s comprehension of a current situation (i.e., as-is state)

and her ability to make a projection of the future (i.e., to-be state). The decision is based on

situation awareness and leads to moving a system from its as-is state to the desired to-be state.

Feedback loop transfers experience and knowledge derived from undertaken action into situation

awareness of a decision-maker.

In addition to the constructs mentioned above, Rosemann & vom Brocke (2015) also consider

process collaboration and communication and propensity to lead BPM as capability areas making

up the People factor. Process collaboration and communication refer to the approach chosen by

process stakeholders to collaborate and communicate to achieve process objectives. The

propensity to lead BPM refers to the level of senior management engagement in the BPM initiative.

Culture

Schmiedel et al. (2015) define BPM Culture as “a culture that supports achieving BPM objectives,

i.e., efficient and effective business processes,” which is mainly understood as a set of specific

values. These values are customer orientation, excellence, responsibility, and teamwork.

Definitions of each of the values mentioned above are presented in Table 6.

Table 6: The four primary values of BPM

№ Value Definition

1 Customer orientation

(external and internal)

The proactive and responsive attitude towards the needs of

process output recipients.

2 Excellence

(continuous improvement and innovation)

The orientation towards continuous improvement and

innovation to achieve superior process performance.

3 Responsibility

(accountability and commitment)

The commitment to process objectives and the accountability

for process decisions.

4 Teamwork

(formal and informal structures)

The positive attitude towards cross-functional collaboration.

Source: Compiled by the author based on Schmiedel et al. (2015)

23

1.2 Business Process Management Lifecycle

Another perspective to BPM is observing it in time as a sequence of interrelated stages (i.e.,

iterations, processes). This sequence is traditionally presented as a lifecycle model (van der Aalst,

2011; Kirchmer, 2017; Dumas et al., 2018; Weske, 2019), emphasizing its repetitive nature. This

section is devoted to a critical overview of existing models of the BPM lifecycle to choose the one

that can be used as a backbone for the thesis's research methodology. Figure 5 represents the BPM

lifecycle, according to Dumas et al. (2018).

Figure 5: Business Process Management Lifecycle (Dumas et al., 2018)

Source: Dumas et al. (2018), p. 23

As it follows from Figure 5, the BPM lifecycle consists of six sequential stages, and an output of

one stage is used as an input to the following one. Process Identification consists of three sub-

stages: (1) describing organization strategy, which is in line with the development part of the

“Understand Enterprise Strategy” activity of the BPTrends’ methodology (see Table 2); (2)

defining process architecture, which has the same meaning as the “Model Enterprise Processes”

activity of the BPTrends’ methodology (see Table 2); and (3) process selection that aims to choose

the most important processes to be discovered, analyzed and redesigned. Process Discovery

focuses on the development of the selected process’ as-is model. Process Analysis is devoted to

identifying problems in the execution of the selected process. Process Redesign aims to transform

the process to mitigate the identified issues. Process Implementation focuses on performing

changes requires to move the process from its as-is state to the to-be state defined in the previous

stage. Process Monitoring aims at collecting relevant data about newly implemented process

execution to determine how well the process performs according to its KPIs.

As follows from the definitions provided above, the Process Identification stage aims to align BPM

with organizational strategy. Therefore, it is consistent with the six core elements framework of

Rosemann & vom Brocke (2015). Another stage of the BPM lifecycle closely connected to

Strategic Alignment is Process Monitoring, which can only be conducted after the “Define

Performance Measure” activity of the BPTrends’ methodology is executed. This activity follows

“Understand Enterprise Strategy” and “Model Enterprise Processes” activities included in the

24

Process Identification. Therefore, it would be more precise to claim that Process Identification

should be followed by Process Monitoring. Moreover, Dumas et al. (2018) included the Process

Selection step, which utilizes Process Monitoring input into Process Identification, which might

lead to the logical contradiction after implementing the proposed rearrangement of the BPM

lifecycle. Therefore, Process Selection should be either distinguished as a separate stage or

included in Process Discovery.

Other stages of the BPM lifecycle are mainly supported by Methods and IT core elements.

Moreover, Process Discovery and Process Implementation are highly dependent on People and

Culture elements. The model of Dumas et al. (2018) does not consider Governance directly.

However, it can be assumed that this core element determines how the BPM lifecycle is

implemented in the particular organization (e.g., which methods are used, who is responsible for

delivering stage outputs, etc.).

Although other authors (van der Aalst, 2011; Kirchmer, 2017; Weske, 2019) use different names

for the BPM lifecycle stages mostly agree with the model proposed by Dumas et al. (2018), as

presented in Table 7.

Table 7: A comparison of different BPM lifecycle models

Author Dumas et al. (2018) van der Aalst (2011) Kirchmer (2017) Weske (2019)

Sta

ges

Identification - - -

Discovery (Re)design

Design

Design & Analysis

Analysis Diagnosis/requirements

Redesign (Re)design Evaluation

Implementation Configuration/impleme

ntation Implement Configuration

- Enactment/monitoring

Execute Enactment

Monitoring Control

- Adjustment - -

Source: Compiled by the author based on van der Aalst (2011), Kirchmer (2017), Dumas et al. (2018), and Weske

(2019)

Even though Kirchmer (2017) highlights the importance of Strategic Alignment in his model, the

Identification stage that aligns BPM with business strategy is distinguished only by Dumas et al.

(2018) and should be included in the lifecycle. All the authors agree on the need to have stages

from Discovery to Implementation in the BPM lifecycle. However, regarding stages that follow

Implementation, it seems more accurate to distinguish execution from control (monitoring) as

proposed by Kirchmer (2017). The more appropriate way for it would be to use the notation of

Weske (2019) and rename “monitoring” into “enactment”. Lastly, it seems reasonable not to

include the Adjustment stage proposed by van der Aalst (2011) into the integrated BPM Lifecycle

model since it represents a special case of the Process Redesign.

Figure 6 depicts the integrated BPM Lifecycle model that reflects the results of the above-

mentioned comparison. The model of Dumas et al. (2018) presented in Figure 5 is considered

fundament for the integrated BPM Lifecycle with the adjustments described above because other

models are less detailed. More specifically, Weske (2019) unites Analysis and Redesign into

Evaluation, van der Aalst (2011) does not make a distinction between Discovery and Redesign

and unites them into (Re)design, and Kirchmer (2017) unites Discovery, Analysis, and Redesign

25

into the Design stage. However, it would be more efficient to make a more detailed decomposition

of the BPM lifecycle stages to see what methods are associated with them.

Figure 6: The integrated BPM Lifecycle model

Source: The author’s own elaboration

Each stage of the integrated BPM Lifecycle model is described in more detail in Table 8.

Table 8: Stages of the integrated BPM Lifecycle model

№ Stage Definition

1 Process Identification This stage consists of two sub-stages that are:

1. Describing organizational strategy which is the same as the

strategic development part of the “Understand Enterprise Strategy”

activity of the BPTrends’ methodology (see Table 4);

2. Defining process architecture which is the same as the “Model

Enterprise Processes” activity of the BPTrends’ methodology (see Table

4)

2 Process Enactment Processes are executed, and relevant data about process execution is collected and

analyzed to determine how well the processes are performing concerning its

performance objectives expressed in KPIs.

3 Process Selection Processes are prioritized, taking into consideration performance insights obtained

during Process Enactment. Prioritization is needed to primarily focus on these

processes, which will bring the highest ROI from BPM.

4 Process Discovery Processes with the highest priority are discovered using various methods,

documented in process descriptions, and graphical as-is models created using

BPM-specific notations (e.g., BPMN).

5 Process Analysis An analysis is conducted to identify issues in processes that were previously

selected and discovered.

6 Process Redesign Problems identified in Process analysis are solved by redesigning the as-is process.

The redesigned process is depicted in the form of the to-be process model created

using the same approach to create the as-is model.

7 Process

Implementation

The changes required to transform the process are planned and implemented either

through organizational change management or automation.


26

Each stage presented in Figure 6 and described in Table 8 is associated with the set of methods

(i.e., tools and techniques) described in more detail in subsequent sections. The summary of these

associations is presented in Table 9, which does not include Process Implementation since it is

beyond the thesis’s scope.

Table 9: Stages of the BPM lifecycle and associated methods

№ Stage of BPM lifecycle Methods

1 Process Identification Balanced Scorecard, Porter’s Value Chain, Reference Models.

2 Process Enactment Managerial accounting cost measures, TOC measures and metrics, LSS

measures and metrics, churn rate, and net promoter score.

3 Process Selection Pareto Chart (LSS), Product Portfolio Matrix, TOC measures and

metrics, Voice of the customer (LSS), KPIs.

4 Process Discovery Document analysis, observation, automated process discovery,

interview, workshop, business process modeling.

5 Process Analysis Value Stream Analysis (LSS), Flow Analysis, Current Reality Tree

(TOC), Pareto Chart (LSS), Ishikawa Diagram (LSS), Regression

(LSS), ANOVA (LSS), Kruskal-Wallis test (LSS), Logistic Regression

(LSS), Chi-square test (LSS).

6 Process Redesign Evaporating Cloud (TOC), TRIZ, Heuristic Process Redesign,

Benchmarking (LSS), Future Reality Tree (TOC).


1.2.1 Process Identification

Process Identification is the first stage of the integrated BPM lifecycle model presented in Figure

6. Dumas et al. (2018) defined process identification as “management activities that aim to

systematically define the set of business processes of an organization”. As follows from Table 8,

this stage is divided into two sub-stages: (а) Describing Organizational Strategy, and (b) Defining

Process Architecture.

Describing Organizational Strategy

As mentioned above, the Describing Organizational Strategy sub-stage correlates with the

development part of the “Understand Enterprise Strategy” activity (see Table 2). Burlton (2015)

and Dumas et al. (2018) consider Balanced Scorecard and Enterprise Architectures main methods

used in this sub-stage. However, the description of the Enterprise Architectures associated with

the IT Tradition (see Appendix A) lies beyond the thesis’s scope.

Balanced scorecard

The balanced scorecard is an explicit representation of an organization’s strategy first introduced

by Kaplan & Norton (1992). Authors assumed a long-term shareholder value as a corporation's

generic goal broken down into sub-goals within four perspectives, presented graphically in the so-

called Strategy Map. It includes four interconnected perspectives, as shown in Figure 7. Learning

and Growth Perspective considers four core elements of BPM included in the framework of

Rosemann & vom Brocke (2015): People (i.e., Teamwork, Leadership), Culture, Strategic

Alignment, and IT. These elements influence the Internal Perspective that depicts a set of processes

executed in the organization (i.e., process architecture). Processes in Internal Perspective affect

the Customer Perspective, including non-financial performance measurements correspondent with

particular business processes, which influence financial performance measurements represented

by Financial Perspective.

27

Figure 7: An example of the strategy map


Defining Process Architecture

According to Dumas et al. (2018), a process architecture aims to “provide a representation of the

processes that exist in an organization”. The authors claimed that the process architecture

comprises three breakdown levels, as presented in Figure 8. The first level is represented by the

Process Landscape Model, which derives processes into three groups, as proposed in Porter’s

Value Chain concept. Sometimes, it is also useful to refer to various Process Frameworks such as

PCF.

Figure 8: A process architecture with three levels


28

Porter’s Value Chain The Value Chain concept developed by Porter (1985) in its current state

consists of three categories of processes involved in the company’s value creation as follows

(Dumas et al., 2018):

1. Core processes cover the essential value creation (i.e., production of goods and services

sold to the customer).

2. Support processes enable the execution of core processes.

3. Management processes provide rules and practices for core and support processes.

Process Frameworks According to Houy et al. (2015), Process Frameworks (also referred to as

Reference Process Models) are business process models derived from summarizing industry-

specific best practices and are usually reusable and universally applicable. Examples of reference

process models are Supply Chain Orientations Reference (SCOR) Model, Information Technology

Infrastructure Library (ITIL), and APQC Process Classification Framework (PCF). The primary

use of these models is to construct a business process architecture referring to industry-specific

benchmarks.

The second level of the process architecture is comprised of process models of business processes

of the first level using various process modeling languages (e.g., BPMN) as well as with

corresponding process profiles (see example in Appendix B) that include additional information

about processes such as process vision, associated process governance roles, resources, etc. The

third and further levels of the process architecture presented by sub-processes and tasks related to

the second level of the process architecture are developed using the approach applied to the second

level of the process architecture.

1.2.2 Process Enactment

Process enactment consists of two parallel activities: process execution and process monitoring.

Process execution is conducted according to the execution process model applied during the

Process Implementation and is managed (i.e., controlled) through process monitoring. Therefore,

process execution is not in the thesis's scope, while a more detailed description of process

monitoring is provided below.

Process monitoring is referred to as the usage of “data generated by the execution of a business

process [that typically takes the form of a collection of event records] to extract insights about the

actual performance of the process and to verify its conformance to norms, policies, and

regulations” (Dumas et al., 2018). Weske (2019) defines process monitoring as a process

controlling concerned with measurements of performance indicators. There are two approaches to

process monitoring: offline process monitoring and online process monitoring. Offline process

monitoring is concerned with analyzing historic process execution using statistical tools and

techniques. In contrast, online process monitoring is devoted to a real-time assessment of currently

running processes using process mining methods associated with the IT Tradition.

The concept of performance measures is central to process monitoring. Dumas et al. (2018)

distinguish four performance dimensions that form the so-called Devil’s Quadrangle presented in

Figure 9. These four dimensions are time, cost, quality, and flexibility. Franceschini et al. (2007)

suggested to also concern productivity as one of the process performance dimensions. Each of

these five dimensions includes several indicators described below.

29

Figure 9: The Devil’s Quadrangle


Time Measurements

According to Franceschini et al. (2007), time measurements “typically relate to the process of time

development”. Dumas et al. (2018) claim that the primary measurements of time are cycle time

(also called throughput time) and waiting time. Cycle time is “the time that it takes to handle one

case from start to end” (Dumas et al., 2018). It is composed of processing time (also called working

time), which is the time spent by resources (e.g., human resources, machines, information systems)

on handling the case, and waiting time during which resources are in idle mode.

Cost Measurements

Although Dumas et al. (2018) mentioned that revenue (i.e., throughput in terms of TOC) and other

cash inflow metrics could be used to measure process performance, they underlined the primary

role of metrics concerned with measuring cash outflow (i.e., costs). According to Drury (2017),

there are three major cost classifications: (1) direct and indirect costs; (2) product and period costs;

(3) variable and fixed costs.

According to Drury (2017), direct costs are those that “can be specifically and exclusively

identified within a particular cost object [i.e., any activity for which a separate measurement costs

are desired]”. In contrast, indirect costs “cannot be identified specifically and exclusively within

a given cost object”.

Product costs are manufacturing costs associated with goods purchased or produced for resale

(i.e., inventory, work in progress). Period costs are non-manufacturing costs that are not included

in the inventory valuation and treated as expenses in the period in which they are incurred. It seems

reasonable to say that product costs correspond with TOC’s inventory measure, while period costs

are the same as operating expenses in terms of TOC.

Variable costs “vary in direct proportion to the volume of activity”, while fixed costs “remain

constant over wide ranges of activity for a specified time period” (Drury, 2017). It can be said with

a high level of certainty that most of the product costs from the previous classification are variable,

and most of the period costs are fixed.

Another costs classification is provided by Krishnamoorthi et al. (2018), who distinguished six

categories of quality costs to express and measure quality in monetary terms. Costs of producing

quality (i.e., prevention cost and appraisal cost) and costs of not producing quality (i.e., internal

30

failure cost and external failure cost) are summed into total quality costs. Prevention costs are

presented by expenses incurred in preventing defectives’ production (e.g., quality planning,

training, process control). Appraisal costs are incurred in appraising a product or material

condition regarding requirements and are closely connected with quality inspections. Internal

failure costs arise from defective units produced but not shipped because of in-time detection (e.g.,

scrap, rework, retest, penalties for not meeting deadlines). External failure costs arise from

defective products that reached the customer (e.g., complaint adjustment, product returns, warranty

charges).

The cash inflow side of the process can be concerned in addition to the cash outflow side

represented by costs. Consideration of both sides of the cash flow generated by the process allows

comparing different processes using profitability measurements (e.g., Net Profit or ROI in terms

of TOC).

Quality Measurements

Quality measurements “investigate the product/service characteristic compared to customer

needs” (Franceschini et al., 2007). One of the TQM gurus, Joseph M. Juran, defined quality as

“fitness for use” (Martínez-Lorente et al., 1998). In application to BPM, the process output that

matches quality requirements can be categorized as acceptable, while one that does not fit them

can be referred to as defective.

One of the defect level measures commonly associated with the Six Sigma methodology is called

process yield (Krishnamoorthi et al., 2018). The yield of single process activity is calculated using

the algorithm depicted in Figure 10, while the yield of process-in-focus is the product of yields of

single process activities. Another measure of defect level is called “defect per unit”. It is calculated

as the total number of defects that occurred in the process divided by the total number of units

produced (Krishnamoorthi et al., 2018).

Figure 10: Calculation of a yield of single process activity


Another common approach described by Dumas et al. (2018) measures quality through the client’s

satisfaction with the process output. One such metric commonly used in e-commerce is called a

churn rate and estimates the share of customers who did not finish the customer journey in a total

number of customers. Another client’s satisfaction measure is a net promoter score that is often

defined in a range from 1 to 10 and captures how far customers would be willing to recommend a

product or service.

Flexibility Measurements

Flexibility measurements are used to evaluate the organization’s ability to respond to changes

(Franceschini et al., 2007; Dumas et al., 2018). Dumas et al. (2018) suggest considering two

flexibility measurements: runtime flexibility and build-time flexibility. Runtime flexibility is the

time needed to handle changes and variations during the process execution, while build-time

flexibility measures the time required to redesign the business process.

31

Productivity Measurements

Productivity measurements are defined as “the ratio of process outputs to process inputs”

(Franceschini et al., 2007). TOC's Productivity calculated as Throughput divided by Operating

Expenses is seen as the group's major metric.

1.2.3 Process Selection

According to Dumas et al. (2018), process selection aims to choose specific business processes for

further improvement. The choice is made because most companies do not have enough resources

to improve all their processes simultaneously. Therefore, they have to focus their attention only

on relevant ones. Dumas et al. (2018) suggested selecting high-priority processes based on three

criteria estimated by experts on a numerical scale: strategic importance, health, and feasibility.

However, it seems reasonable to improve the method proposed by authors and incorporate tools

and techniques used in TOC and LSS to assure higher estimation accuracy.

Strategic Importance

The strategic importance of a process is an “impact on the strategic goals of an organization”

(Dumas et al., 2018). The authors argued that the estimation of strategic importance should be

done by internal experts (i.e., senior managers). Nevertheless, this approach may lead to several

problems. Firstly, expert estimates are subjective and may be biased. For instance, the deputy of

finance may set high priorities to the processes that relate to her department, while the deputy of

operations may highlight only those processes that are involved in the production. Secondly, if

senior managers are not highly committed to the BPM initiative, it will be hard to persuade them

to conduct such an estimation. Thus, it seems reasonable to range process groups and then perform

a prioritization within each group to decrease subjectivity of estimation and problems associated

with it.

It seems self-evident to firstly consider core processes that directly impact the company’s value

proposition. Then the attention should be paid to support processes that enable the execution of

core processes. Finally, management processes that set rules and policies applied in core and

support processes should be considered.

Product Portfolio Matrix (PPM), depicted in Figure 11, is seen as an appropriate tool to range core

process groups. It aims to graphically portrait differences among products (or businesses) in terms

of competitive market share position and industry growth rate (MacRae, 2020). The relative

market share position is shown on the x-axis, ranging from 0 to the maximum value representing

the leading competitor's market share. The midpoint of the x-axis is typically given as 50% of the

leading competitor’s market share, yet it can be adjusted based on the research context. For

instance, if a market is divided into fragmented and specialized business segments based on the

Competitive Advantage Matrix described further, the midpoint can be presented by the market

share of the smallest competitor of the specialized business segment. The industry growth rate is

reflected in the y-axis, which typically ranges from -20 to +20 percent, with 0.0 being the midpoint.

32

Figure 11: The BCG’s Product Portfolio Matrix

Source: Adapted from MacRae (2020), p. 62

As seen in Figure 11, companies can be categorized into four categories depending on their

position on two axes: question marks, stars, cash cows, and dogs. According to Henderson (1970),

stars assure the future, while question marks can be converted into stars with the added funds

supplied by cash cows. Therefore, core process groups aligned with the star businesses are of the

highest strategic importance, followed by those associated with question marks and cash cows.

Another approach that can be used to range processes and process groups by their strategic

importance is proposed by Goldratt (1990). It aims to range processes within each process group

based on their weights that can be determined based on measurements of cash outflows (i.e.,

inventory and operating expenses), measurements of cash inflows (i.e., throughput), or metrics

derived from these measurements (i.e., net profit, ROI, and productivity). Moreover, this approach

can be implemented if, for instance, two or more core process groups are placed in the single

quadrant of the PPM (e.g., stars).

After weights were determined based on selected measurements or metrics, the process

prioritization can be depicted graphically using Pareto Chart, which is the commonly used tool

for prioritization causes (X variables) by their influence on the examined problem (Y variable).

Dumas et al. (2018) stressed that all the weights should be quantified and sorted (from highest to

lowest impact) according to the sole measurement approach. For instance, all the processes should

be estimated based on their cycle time. An example of the Pareto Chart containing a bar chart with

individual strategic impact of processes and curve presenting their cumulative impact is shown in

Figure 12. Due to the hierarchical principle of system organization (Beer, 1981), the Pareto Chart

can also be implemented to compare sub-processes and even tasks that comprise processes-in-

focus.

33

Figure 12: An example of the Pareto Chart (Process Selection)


Health

Dumas et al. (2018) defined health as a measure of trouble in a process based on either performance

assessment or customer evaluation. Performance assessment can be referred to as comparing

actual process performance against the planned one. Therefore, the process health ratio can be

calculated by dividing the achieved KPIs by the respective targets. The process can be considered

unhealthy if the ratio is less than 1.

Health assessed through customer evaluation can be referred to as customer satisfaction with the

process outputs. It can be evaluated using a set of tools and techniques of LSS to determine

customer needs, commonly referred to as “listening to the voice of the customer”. Krishnamoorthi

et al. (2018) claimed that there are several approaches to hear the customers’ voice as follows:

- Surveying of past and potential customers;

- Listening to the focus groups of customers;

- Collecting information from the history of complaints;

- Learning from the experiences of cross-functional team members.

A choice of approach that should be used in a particular case depends on the available historical

data. If there is a sufficient amount of historical data, it would be easier to calculate the process

health ratio. At the same time, customer estimation can be conducted if there is a need to collect

additional evidence to make the right decision.

Feasibility

Feasibility can be perceived as ease of implementing changes to the process. Dumas et al. (2018)

point out that “culture and policies involved in a particular process may be obstacles to achieving

results from [BPM] initiative”. Considering that organization members often resist change (Malek

& Yazdanifard, 2012), it can be said that this resistance can be incorporated into the corporate

culture. Moreover, in some cases, organizational policies can be intentionally created to resist

potential changes. However, it should not stop organizations from considering redesign

opportunities for unfeasible processes. If a process creates a constraint, it should be improved to

lift the performance of the whole system despite the degree of process feasibility. Therefore,

feasibility should be considered the last comparison criterion applied only if two processes have

the same strategic importance and health.

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Based on the information above, the process of process selection should have the structure

presented in Figure 13.

Figure 13: A process of process selection


1.2.4 Process Discovery

Dumas et al. (2018) define process discovery as “the act of gathering information about an existing

process and organizing it in terms of an as-is process model”. In other words, process discovery is

devoted to modeling business processes and, therefore, defining the second level of process

architecture. According to Dumas et al. (2018), there are four activities to be executed during the

process discovery stage: (1) Defining the setting, (2) Gathering the information, (3) Modeling the

business process, and (4) Assuring the process model quality.

Defining the setting

Defining the setting requires assembling a team responsible for a process discovery project

typically consisting of process analysts and domain experts. Process analyst is an employee with

a high degree of BPM knowledge. Domain experts are persons with a high degree of knowledge

regarding the specific process or set of processes.

Gathering the information

Dumas et al. (2018) distinguished three classes of information gathering methods: (1) evidence-

based discovery, (2) interview-based discovery, and (3) workshop-based discovery. The majority

of these methods are used in social sciences (e.g., observation, interview), while some methods

come from data science (e.g., process mining).

Evidence-based discovery

According to Dumas et al. (2018), evidence-based discovery includes document analysis,

observation, and automated process discovery. Document analysis is referred to as discovering

historical information about the process through process-related documentation such as process

descriptions, internal policies, organization charts, glossaries, handbooks, etc.

Observation refers to “following the processing of individual cases to get an understanding of how

the process works” (Dumas et al., 2018). A process analyst can either play the active role of a

customer or act as a passive observer. If an active customer role is performed, the process analyst

triggers the execution of the process and documents steps and choices made during the process

execution. The main disadvantage of this approach is that it allows observing only those tasks that

require interaction with the process customer. However, active observation is characterized by a

high degree of control possessed by the process analyst. It allows describing how the process works

in a general way instead of focusing on particular cases.

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When the passive observer role is performed, the execution of the whole end-to-end process might

be observed and documented if the required access is provided. The main disadvantage of such an

approach is the potential distortion of reality due to the Hawthorne effect when people change their

behavior in response to the awareness of being studied (McCambridge et al., 2014). However, this

approach reveals how a process is conducted in reality, in contrast to the documentation analysis

that typically captures the past (Dumas et al., 2018).

Automated process discovery is a method described by many authors (Camargo et al., 2020;

Halaška & Šperka, 2019; Puchovsky et al., 2016; van der Aalst, 2011) in recent years. This method

aims at extracting process knowledge from event logs (Puchovsky et al., 2016) by applying process

mining methods and tools (van der Aalst, 2011). Event logs can be referred to as process execution

data tracked by and stored in an information system (e.g., ERP system). Various algorithms and

tools of process mining proposed by van der Aalst (2011) are used to build process models based

on these data. Automated process discovery allows mitigating risks connected with the human

factor and obtain an objective representation of the process. However, since process mining is

associated with the IT Tradition, it will not be explained in more detail.

Interview-based discovery

According to Dumas et al. (2018), interview-based discovery “aims at interviewing [multiple]

domain experts [with a fragmented process knowledge] to inquire about how a process is

executed”. Saunders et al. (2019) distinguished structured, semi-structured, and unstructured types

of interviews. Structured interviews use questionnaires with a predefined set of questions, which

can also contain pre-coded answers. In semi-structured interviews, the researcher typically has a

list of themes and questions to be covered but may not stick to this list. During the unstructured

interviews, the researcher does not refer to any predetermined list of questions or themes, yet she

needs to have a clear idea about the aspects that have to be explored.

While structured and unstructured interviews present two extremes, it seems reasonable to use

semi-structured interviews while extracting process knowledge from domain experts. Such an

approach allows the researcher to combine the advantages of these types and mitigate their

disadvantages. The interview might start from a pre-defined question and then be expanded with

questions based on interviewee responses.

Workshop-based discovery

One technique that is used in workshop-based discovery is to ask workshop participants to

“collectively build a rough model of the process (a sketch) using sticky notes on the wall” (Dumas

et al., 2018). Therefore workshop-based discovery involves multiple domain experts

simultaneously and obtains a graphical rather than textual description of the process. One of the

main disadvantages of this class of methods is that it is hard to schedule such a workshop,

especially when domain experts work in different organizational units. However, the workshop

provides an opportunity to immediately resolve conflicts in responses that may arise due to the

fragmented process knowledge.

To sum up, it seems worthwhile to implement evidence-based methods to have a high-level

comprehension of how the process is executed and then use interviews or workshops to understand

the process structure more deeply.

36

Modeling the business process

Data gathered during the previous step is used as an input to the business process modeling. Weske

(2019) defines a process model as “a blueprint for a set of process instances with a similar

structure” that consists of nodes (i.e., activities, events, and gateways) and edges that express

relationships between nodes. Activities are units of work conducted in a business process, events

capture the occurrence of states relevant for a business process, and gateways represent points

where a decision about the further process execution is made. Dumas et al. (2018) propose the

following five-step algorithm that can be applied to complete this task:

1. Identify the process boundaries (i.e., events that trigger the process and those that signal

its completion);

2. Identify main process activities and intermediate events;

3. Match resources (i.e., anyone or anything involved in the performance of a processing

activity) with previously defined activities and identify process handoffs (i.e., points in the

process where work is handed over from one resource to another);

4. Identify the control flow that includes order dependencies, decision points ((X)OR

gateways), concurrent execution of activities and events (AND gateway), and potential rework

and repetition (loop structures);

5. Identify additional elements such as business objects (e.g., data objects, data stores, and

their relations to activities and events via data associations) and exception handlers (e.g.,

boundary events, exception flows, and compensation handlers) based on the purpose of the

model.

Other authors (e.g., Silver, 2011; Weske, 2019) share this algorithm with minor deviations.

Therefore, it can be used as a guideline for business process modeling.

Assuring the process model quality

Dumas et al. (2018) describe three quality aspects and three assuring activities corresponding to

these aspects as presented in Table 10. Verification can be undertaken within the process modeling

environment (e.g., Signavio), while validation and certification involve domain experts.

Table 10: Process model quality aspects and assurance activities

Quality aspects Assuring activities

Syntactic quality relates to the element level and

model level conformance of a process model to the

modeling language's syntactic rules.

Verification is the activity of checking that a

process model is syntactically correct.

Semantic quality deals with the adherence of a

process model to its real-world process.

Validation is the activity of checking the semantic

quality of a model by comparing it with its real-

world business process.

Pragmatic quality relates to the usability of a

process model in three aspects: understandability,

maintainability, and learning.

Certification is the activity of checking the

pragmatic quality of a process model by

investigating its use.

Source: Compiled by the author based on Dumas et al. (2018)

1.2.5 Process Analysis

The process chosen during the process selection and modeled during the process discovery should

be examined to identify root causes (i.e., process constraints) that influence the process

37

performance. Tools and techniques of process analysis the vase number of which are associated

with LSS and TOC are applied to achieve the following objectives:

1) Identify causal factors at the process and activity levels;

2) Identify process constraints;

3) Validate relationships between causes.

Identification of causal factors

The main methods applied to identify causal factors at the process level are Value Stream Analysis,

Waste Analysis, and Flow Analysis, while the Ishikawa Diagram is seen as the appropriate tool to

identify causal factors at the activity level.

Value Stream Analysis

Associated with LSS, Value Stream Analysis (VSA) focuses on analyzing and identifying different

kinds of waste (i.e., unnecessary activities) that might occur during the process execution.

According to Zahrotun & Taufiq (2018), process activities should be classified into three

categories: value-adding (VA), business-value-adding (BVA), and non-value-adding (NVA). VA

activities are those that produce value to the customer and thus cannot be eliminated. BVA activities

are required due to the existing regulations contained in external legislations and internal business

policies. These activities can only be changed after necessary changes to the regulations mentioned

above, which is rarely possible. NVA activities cannot be classified as VA or BVA activities.

Solutions should be developed to remove such activities from the process if possible. For instance,

activity elimination and automate activity heuristics presented in Appendix C can be used to

remove NVA activities from the process.

Waste Analysis

Waste Analysis is another technique widely used within the LSS initiative to increase process

execution efficiency by reducing sources of inefficiency (i.e., wastes). As shown in Table 11, seven

types of waste may occur during the process execution.

Table 11: The seven types of waste

№ Waste Type Definition Example

1 Overproduction Producing more than needed and excess stock. Execution of an entire process instance

that does not add value upon

completion.

2 Defect Rejected/ defective finished products that do

not fit for use.

All work performed to correct, repair, or

compensate for a defect in a process

mainly presented by process loops.

3 Waiting People waiting on material or equipment and

idle equipment.

Task waits for process participants to

become available or process

participants wait for a task to become

available (i.e., idleness).

4 Transportation Movement of people, tools, inventory,

equipment, or products further than necessary.

Handoffs between process participants

(i.e., message flows).

5 Overprocessing Doing more work, adding more components,

or having more steps in a product or service

than what is required by the customer.

The work that is performed is

unnecessarily given the outcome of a

process instance.

6 Motion Unnecessary movement of people, equipment,

or machinery.

Process participants (resources) moving

from one place to another during the

process execution.

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№ Waste Type Definition Example

7 Inventory Excess finished products, semifinished goods,

or components with inventory status

do not add value.

Work-in-process (i.e., the number of

cases that have started but have not yet

finished).

Source: Compiled by the author based on Zahrotun & Taufiq (2018) and Dumas et al. (2018)

Once waste was identified, solutions should be found to reduce it as much as possible. Apart from

heuristics mentioned in the previous sub-section, the empower heuristic implementation can

minimize process waste.

Flow Analysis

According to Dumas et al. (2018), Flow Analysis is “a family of techniques to estimate the overall

performance of a process given some knowledge about the performance of its tasks”. These

techniques can be used to calculate the cycle time and cost of the process.

Considering that process can consist of different types of fragments, as shown in Table 12, the

total cycle time (CT) and total cost (C) of a process can be calculated as a sum total of cost and

cycle time of its fragments. Formulas presented in Table 12 use T to indicate a task duration, c to

indicate the cost of a task, p for probability, and r for the probability of task repetition.

Table 12: Cycle time and cost calculation for different types of process fragments

№ Process

fragment type

Pattern Cycle time Cost

1 Sequential block

𝐶𝑇 = ∑ 𝑇𝑖

𝑛

𝑖=1

𝐶 = ∑ 𝑐𝑖

𝑛

𝑖=1

2 XOR-block

𝐶𝑇 = ∑ 𝑝𝑖 ∗ 𝑇𝑖

𝑛

𝑖=1

𝐶𝑇 = ∑ 𝑝𝑖 ∗ 𝑐𝑖

𝑛

𝑖=1

3 AND-block

𝐶𝑇 = 𝑀𝑎𝑥(𝑇1, 𝑇2, … , 𝑇𝑛) 𝐶 = ∑ 𝑐𝑖

𝑛

𝑖=1

4 Rework block

𝐶𝑇 =𝑇

1 − 𝑟 𝐶 =

𝑐

1 − 𝑟


The calculation of the cycle time of processes that contain several types of process fragments can

be complicated. However, it can be eased by adopting formulas provided in Table 12 to calculate

the probability of activity execution, as shown in Figure 14.

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Figure 14: Probability calculation for different types of process fragments


Once average durations of activities (or average costs of activity execution) are measured, and

probabilities are estimated, the individual cycle time (or cost) of the particular activities is

calculated by the multiplication of these variables. The process cycle time and cost can be reduced

by implementing different process redesign heuristics specified in Appendix C.

Ishikawa Diagram

Ishikawa Diagram can be used to identify causal factors at the activity level and classify them into

several categories. A well-known categorization is called 6M’s and includes Machine

(technology), Methods (process), Material, Man, Measurement, and Milieu, which is another word

for “environment” (Ishikawa, 1985). The template of a cause-effect diagram based on 6M’s is

presented in Figure 15. Nevertheless, this template should be tailored to the specifics of the

examined process.

Figure 15: A template of the Ishikawa Diagram


Identification of process constraints

Individual process activities can be prioritized based on the data obtained during the Flow Analysis

using Pareto Chart. The activity with the most significant influence can be referred to as a

40

bottleneck activity (i.e., process constraint). A process analyst should focus on solutions that

reduce the selected process measure (e.g., cycle time) of this activity to gain the most impact from

the process redesign. The causal factors identified from the Value Stream Analysis, Waste

Analysis, Flow Analysis, and Ishikawa Diagram are usually related. To identify relations between

these factors, the process analyst can use the Current Reality Tree.

Pareto Chart

Pareto Chart described in detail in the 1.2.3 Process Selection section can also be applied to

prioritize causes and determine the root cause of the problem. An example of the Pareto Chart

containing a bar chart with individual causes and curve presenting their cumulative effect on the

examined problem is shown in Figure 16.

Figure 16: An example of the Pareto Chart (Process Analysis)


Current Reality Tree

The Process Analysis stage of the BPM lifecycle corresponds with the first focus step of the Theory

of Constraints (i.e., Identify the constraint). The primary tool proposed by Goldratt (1990) to be

used during this step is the Current Reality Tree (CRT) example of which is presented in Figure

17. CRT is a cause-and-effect logic diagram used to establish a stream of logical relationships that

link the core cause with undesirable effects (UDEs) (Youngman, 2009). Core cause (i.e.,

constraint/bottleneck) does not have any predecessors and causes UDEs. The problem in the

process is the final UDE in chain cause-and-effect instances triggered by the core cause.

The CRT construction process contains the following steps (Scheinkopf, 1999):

1) Determine the scope of the analysis;

2) List between 5 to 10 pertinent entities;

3) Diagram the effect-cause-effect relationships that exist among the entities.

4) Review and revise for clarity and completeness;

5) Apply the "so what" test;

6) Identify the core cause(s).

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Figure 17: An example of the Current Reality Tree


The CRT construction process can be conducted using the five whys methodology developed by

Taichi Ohno (1978), who claimed that “Underneath the ‘cause’ of a problem, the real cause is

hidden. In every case, we must dig up the real reason by asking why, why, why, why, why”. In other

words, UDEs that led to the examined problem should be derived until the core cause is identified.

Validation of relationships between causal factors

Relationships between numerical and categorical causal factors identified in the CRT can be

validated using statistical techniques that are often implemented within the LSS initiative

presented in Figure 18. All these techniques are based on hypothesis testing. They aim to either

reject or accept the initial assumption of the correlation between variables (i.e., null hypothesis)

based on the determined p-value. According to Zwetsloot (n.d.), statistical methods should be

chosen according to types of the examined problem (i.e., Y-variable) and causal factor (i.e., X-

variable) that can either be numerical (i.e., quantitative) or categorical (i.e., qualitative).

Figure 18: Classification of LSS tools and techniques

Source: Zwetsloot (n.d.)

All the techniques presented in Figure 18 allow obtaining p-value and R-squared to test the initial

hypothesis. A p-value below 5% signalizes that X-variable has a significant influence on Y-

variable. At the same time, R-squared determines the share of variation in the Y-variable explained

42

by X-variable. In other words, the larger the value of R-square, the stronger the influence of causal

factors on the examined problem.

Regression analysis is the formal, mathematical approach to studying the relationship between a

numerical X-variable and a numerical Y-variable (Krishnamoorthi et al., 2018). This relation is

hypothesized to be defined by a line that can have different equations dependent on the type of

regression (i.e., linear or non-linear).

Analysis of Variance (ANOVA) tests whether the means of different groups are significantly

different, and therefore the categorical influence factor has a significant effect on the numerical

Y-variable. A p-value calculated during ANOVA indicates the chance that the mean difference

occurs due to random fluctuations. Thus, if the p-value is below 5%, it allows business process

analysts to conclude a significant influence of the categorical X-variable on numerical Y-variable

(Zwetsloot, n.d.).

Kruskal-Wallis test examines if the difference in each category's medians has a significant

influence on Y-variable (Zwetsloot, n.d.). This technique is applicable when Y-variable is

distributed nonnormally.

Logistic Regression is the appropriate technique to use when Y-variable is binominal. It requires

to convert categorical data into the numeric format (e.g., “yes” – 1, “no” – 0).

Chi-square analysis is a suitable method to analyze the influence of categorial X-variable on

categorical Y-variable. It requires to make a cross-tabulation of given variables.

1.2.6 Process Redesign

The Process Redesign stage aims to find solutions to weaken the influence of the root causes

identified during the process analysis on the chosen process performance measures (e.g., cycle

time) and estimate the efficiency of the proposed solutions. Redesign methods aimed to develop

the solution are represented by Evaporating Cloud (i.e., TOC thinking tool), the Theory of

Inventive Problem Solving (TRIZ), Heuristic Process Redesign, and Benchmarking. Future

Reality Tree (i.e., TOC thinking tool) is seen as an appropriate tool to estimate the efficiency of

the proposed solutions. These methods are described in more detail below.

The output of process redesign in the to-be process model representing the desired structure of the

process. Quality of the to-be process model should be assured using the approach previously

described in the respective part of the 1.2.4 Process Discovery section.

Dumas et al. (2018) distinguish transactional (evolutionary) methods that resolve problems

identified during process analysis incrementally from transformational (revolutionary) methods

that aim to achieve fundamental process changes. However, it seems more accurate to distinguish

between changes themselves. As shown below, redesign methods can help to develop solutions of

a different scale of influence to the process measures.

It also seems important to establish a criterium to choose between transactional and

transformational process changes. The stage of the industry lifecycle can be perceived as this

criterium. According to Beer (1981), companies can shift from decline to the new rise by

introducing new technology in the production process (i.e., implementing fundamental process

change). Therefore, incremental changes are best to implement while the industry is growing. In

43

contrast, fundamental changes are preferable when the industry has reached its top and is close to

the decline stage, as presented in Figure 19.

Figure 19: Dependencies between required process changes and industry lifecycle stage


Evaporating Cloud

The Evaporating Cloud (see example in Figure 20) is a diagram that helps to resolve conflict either

between mutually exclusive conditions or different alternatives (Youngman, 2009). The method

of conflict resolution is based on the idea that all conflicts arise from erroneous assumptions.

Therefore, it aims to identify invalid assumptions that lead to the conflict and replace them with

valid assumptions that resolve it (Goldratt, 1990).

Figure 20: An example of the Evaporating Cloud

Source: Compiled by the author based on Youngman (2009)

The common rule is that for n mutually exclusive alternatives, there should be developed (n-1)

evaporating clouds. For instance, if there are only two alternatives, then one evaporating cloud is

enough to resolve the conflict. When there are three options, two evaporating clouds should be

(a) Before the solution is found (b) After assumptions are validated

44

developed: the first to resolve the contradiction between the first two alternatives, and the second

one to resolve the conflict between the solution derived from the first evaporating cloud and the

third alternative.

The Theory of Inventive Problem Solving (TRIZ)

The Theory of Inventive Problem Solving (TRIZ), developed by the Soviet scientists in the 1950s,

is “rated among the most articulated and effective sets of techniques for supporting the initial

stages of engineering design” (Chechurin & Borgianni, 2016). TRIZ systematic approach

presented in Figure 21 demands that a specific factual problem identified during the process

analysis should be reformulated in a conceptual format. A conceptual solution can then be chosen

from the set considered in TRIZ and further be transformed into a specific factual solution

(Ilevbare et al., 2013).

Figure 21: TRIZ systematic approach to problem-solving

Source: Ilevbare et al. (2013), p. 31

According to TRIZ, all the specific factual problems arise from contradictions (i.e., inventive

problems arising from the apparent incompatibility) that can either have technical or physical

nature (Ilevbare et al., 2013). A technical contradiction occurs when an attempt to improve specific

attributes or functions of a system leads to the deterioration of other system attributes. A physical

contradiction arises when there are inconsistent requirements for the physical condition of the

same system. Evaporating Cloud is seen as an appropriate tool to identify the contradictions

mentioned above.

Conceptual solutions to contradictions are mainly derived from 40 inventive principles1 or 76

standard solutions that aim to improve the system without or little change (13 standard solutions),

by changing the system (23 standard solutions), through system transition (6 standard solutions),

detection and measurement (17 standard solutions), and simplification and improvement (17

standard solutions) (Domb et al., 1999). The contradiction matrix2 (i.e., a matrix of 39 technical

parameters arranged on the vertical and horizontal axis to interact with one another) is used to

point out the inventive principles that can be applied to solve technical contradictions. Physical

contradictions are mostly solved by applying separation principles, including separation in time,

space, upon the condition, and between parts and the whole (Hipple, 1999).

1 http://www.triz40.com/aff_Principles_TRIZ.php 2 http://www.triz40.com/aff_Matrix_TRIZ.php

http://www.triz40.com/aff_Principles_TRIZ.php

http://www.triz40.com/aff_Matrix_TRIZ.php

45

Heuristic Process Redesign

Dumas et al. (2018) claim that there are 29 redesign heuristics derived from successful process

redesign projects that allow improving process performance in some of the four dimensions of the

Devil’s Quadrangle (i.e., time, cost, quality, flexibility). These heuristics can be perceived as TRIZ

inventive principles Adapted to the business context (e.g., Merging principle of TRIZ is

reformulated as Activity composition heuristic). These heuristics are derived into seven groups

presented in Appendix C. The highest number of heuristics can be used to improve time (23) and

quality (14) dimensions of performance, while only five can be applied to improve process

flexibility. Moreover, several heuristics deals with more than one performance dimension (e.g.,

25. Activity Automation).

Benchmarking

Krishnamoorthi et al. (2018) define benchmarking as an emulation of the best-in-class performers'

methods (i.e., benchmarks). The benchmarks might either be internal (e.g., another department

within the same organization) or external (e.g., another organization). The point is to find out

already developed solutions to solve the problem-in-focus and implement them to redesign the

selected business process.

Future Reality Tree

The Future Reality Tree (FRT) example of which is presented in Figure 22 is a tool for logically

visualizing the to-be state through the systematic transformation of the CRT by incorporating

certain injections in the business process and identifying positive as well as negative effects caused

by this incorporation.

Figure 22: An example of the Future Reality Tree


Negative (i.e., undesirable) effects (UDEs) of injection arise according to the rule that when one

dimension of Devil’s Quadrangle (see Figure 9) is improved, it causes the decrease in another

dimension. For instance, an increase in quality also lead to a cost increase; an increase in

throughput leads to an increase in inventory (i.e., investment).

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2 Research Methodology

This chapter is devoted to developing the research methodology based on the methods described

in the 1 Theoretical Overview chapter. The chapter’s first section is dedicated to articulating the

primary goal and secondary objectives of research coupled with the identification of BPM lifecycle

stages that should be performed to achieve those goals. The next section, Research Design, is

devoted to describing the purpose, strategy, method, and time horizons of the research. The final

section describes data collection techniques and data analysis procedures that should be used to

achieve the research’s secondary objectives.

2.1 Research Objectives

The research’s primary goal is to improve the overall performance of the XYZ Group’s Payments

Domain by redesigning its bottleneck business process. The secondary objectives that allow

achieving the primary goal are supported by activities executed during several stages of the

integrated BPM lifecycle model (see Figure 6), as presented in Table 13.

Table 13: Stages of the BPM Lifecycle and secondary research objectives

№ Stages of the BPM Lifecycle Secondary Objectives

1 Process Selection SO1: Select the bottleneck process

2 Process Analysis SO2: Identify root causes that influence the process performance

3 Process Redesign SO3: Develop solutions to improve process performance

SO4: Estimate the effect of the proposed solutions


Although Table 13 includes only three stages of the BPM Lifecycle, activities within Process

Identification and Process Discovery stages should also be performed to collect the information

needed to select and analyze the bottleneck business process. Therefore, the research project's

scope should include activities of all the stages of the integrated BPM Lifecycle model except

Process Implementation.

2.2 Research Design

The research design definition is based on the framework proposed by Saunders et al. (2019). It

concerns several aspects derived from the research objectives: purpose, strategy, method, time

horizons, data collection techniques, and data analysis procedures.

Research Purpose Based on the research objectives described in the respective section of the

thesis, the research purpose can be referred to as explanatory because the development of the

solution is based on previously established relationships between variables (i.e., the problem and

its root cause; Peng & Matsui, 2015; Saunders et al., 2019).

Research Strategy A case study is seen as an appropriate strategy to reach the research purpose.

It means that the research is focused on an empirical investigation of a particular phenomenon

(i.e., a business process) within its real-life context (i.e., the organizational context) using multiple

sources of evidence (Saunders et al., 2019).

Research Method The research utilizes quantitative (e.g., Flow Analysis) and qualitative (e.g.,

Interview) data collection techniques and data analysis procedures presented in the 2.3 Data

Collection and Analysis section of the thesis. Therefore, the research method can be referred to as

mixed using the notation of Saunders et al. (2019).

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Time Horizons The research is focused on studying a particular business process at a specific time

and, therefore, can be referred to as cross-sectional (Saunders et al., 2019). However, the research

methodology can be applied in organizations to improve their overall performance by redesigning

bottleneck business processes.

2.3 Data Collection and Analysis

The secondary research objectives can be achieved only through the consistent implementation of

data collection techniques and data analysis procedures conducted in the integrated BPM lifecycle

model's respective stages. Methods chosen to reach these objectives most efficiently are presented

in the Prerequisite Tree depicted in Appendix D. The detailed specification of data collection and

analysis methods used to achieve goals shown in Appendix D is presented in Table 14.

Table 14: Research objectives and associated methods

№ Research objective Associated methods

Data collection Data analysis and

interpretation

3 Industry and Company Overview

1 Develop Process Architecture Document Analysis Strategy map, Process Landscape

Model, Process Frameworks

2.1 Consider Strategic Importance Document Analysis, Interview PPM, Flow Analysis, Pareto Chart

4 Analysis

2.2.1 Consider KPIs Document Analysis -

2.2.2 Consider process performance Document Analysis -

2.2 Consider Health Document Analysis Process Health Ratio

2.3 Consider Feasibility Document Analysis, Interview -

2 SO1: Select the bottleneck process Document Analysis -

3 Develop the as-is process model Document Analysis, Interview,

Observation

-

4 SO2: Identify root causes that

influence the process performance

Document Analysis,

Observation

Flow Analysis, Pareto Chart,

VSA, Waste Analysis, Ishikawa

Diagram, Regression, CRT

5 Recommendations

5 SO3: Develop solutions to

improve process performance

Benchmarking Evaporating Cloud

6 Develop the to-be process model - -

7 SO4: Estimate the effect of the

proposed solutions

- FRT, Factor Analysis


As seen in Table 14, the main methods of data collection are Document Analysis, Observation,

and Interview are previously defined in the 1.2.4 Process Discovery section. Data analysis tools

and techniques are mainly covered in the 1.2.1 Process Identification, 1.2.3 Process Selection,

1.2.5 Process Analysis, and 1.2.6 Process Redesign sections.

48

3 Industry and Company Overview

This chapter is devoted to the overview of the XYZ Group, with special attention given to the

description of its strategic context and process architecture. The XYZ Group is an international

bank-insurance group headquartered in Belgium with core foreign markets presented by the Czech

Republic, Slovakia, Hungary, Bulgaria, and Ireland (XYZ, 2020a). Therefore, the group operates

in the EU-28 market that includes states from the euro and non-euro areas of the European Union.

As of 2019, the XYZ Group had a global presence totaling over 12 million clients and about 1,300

bank branches. The XYZ Group's insurance network was presented by 355 agencies in Belgium

and various distribution channels in Central and Eastern Europe.

The chapter begins with analyzing the XYZ Group’s external environment presented by the EU-

28 banking and insurance industries. This analysis aims to describe the XYZ Group's strategic

context using Competitive Advantage Matrix, Market Potential Evaluation, and Industry Lifecycle

Analysis.

The overview of the XYZ Group starts with a definition of its strategy using the Strategy Map.

Then the first level of the XYZ Group process architecture is presented using the Process

Landscape Model. The competitive market position for each core process group included in the

process architecture is determined based on the industry overview and insights on the XYZ

Group’s financial performance.

The chapter finishes with an overview of the XYZ Group’s Payments Domain, which focuses on

describing the domain strategy with the emphasis on its alignment with the corporate strategy, and

the domain process architecture that represents the second level of the company’s Process

Landscape Model.

3.1 Industry Overview

As follows from the chapter introduction, the XYZ Group competes in the banking and insurance

markets of the EU-28 area. Therefore, these markets should be described based on the unified

approach, later enabling to objectively estimate the strategic importance of core process groups

included in the XYZ Group’s process architecture and determine process redesign methods.

As was previously claimed in the description of the Process Selection stage of the BPM lifecycle,

the strategic importance can be estimated based on the Product Portfolio Matrix that should be

developed for each market segment the company operates in. To perform market segmentation, it

is essential to carefully examine its business model using various tools and techniques such as

Porter’s Value Chain and Process Frameworks. The Competitive Advantage Matrix and evaluation

of market potential have to be conducted to define PPM axes' parameters for each market segment.

Moreover, as follows from the 1.2.6 Process Redesign section, the scale of required process

changes is influenced by the industry lifecycle stage, which leads to the need to conduct the

Lifecycle Analysis.

3.1.1 Banking Industry

The banking industry overview contains the business model's description, the Competitive

Advantage Matrix examination, the evaluation of the market potential, and the industry lifecycle

analysis

49

Business Model

Porter’s Value Chain is seen as the most suitable method to describe the bank business model

because it allows us to look at the companies’ value proposition and conduct the market

segmentation based on the main groups of products and services that make up the customer’s

value. Figure 23 represents the typical value chain for the commercial bank developed by

Lamarque (2000).

Figure 23: The value chain of the commercial bank

Source: Lamarque (2000), p. 10

Freixas & Rochet (2008) define a bank as “an institution whose current operations consist of

granting loans and receiving deposits from the public”. In other words, banks raise funds mainly

through interest-bearing liabilities (e.g., deposits) to later rent them by selling debt instruments

(e.g., loans and mortgages) to clients. The difference between the revenue from a bank’s interest-

bearing assets and expenses associated with paying its interest-bearing liabilities is called net

interest income (Tuovila, 2020). It is considered the primary source of the bank’s total revenue.

Except for net interest income, banks' total revenue is also generated from account-related charges

(e.g., overdraft charges, monthly service charges, wire transfer charges) gained through

transactional operations management.

Therefore, the banking industry market can be divided into debt instruments and transactional

operations segments associated with the bank's value chain's respective core business process

groups. This segmentation is also supported by the Banking Process Classification Framework

(APQC, 2019a), presented in Figure 24.

According to APQC (2019a), the “5.0 Deliver Services” category includes the “5.1 Deliver

banking services to customers” process group, which is further divided into the following

processes:

- 5.1.1 Open accounts;

- 5.1.2 Maintain accounts (including 5.1.2.2 Manage fees/interest/commission);

- 5.1.3 Close accounts;

- 5.1.4 Manage store cash;

- 5.1.5 Service bank customers (including 5.1.5.5 Review and extend credit);

- 5.1.6 Manage transfer transactions.

50

Figure 24: Banking Process Classification Framework

Source: APQC (2019a), p.1

Competitive Advantage Matrix

According to the European Banking Federation (2020), there were 6,088 credit institutions in the

EU holding €43,3 trillion in assets in 2019. About 58.7% of these financial institutions were

concentrated in the United Kingdom, France, Germany. According to Ali (2020), around 71% of

assets belong to the 50 largest EU banks, as partially presented in Table 15. Therefore, the rest

29% of total assets are shared among other 6,038 financial institutions.

Table 15: The largest banks of the EU in 2019

Rank Company Headquarters Total assets, € billion

1 HSBC Holdings PLC UK 2,419.47

2 BNP Paribas SA France 2,164.71

3 Crédit Agricole Group France 2,010.97

4 Banco Santander SA Spain 1,517.27

5 Société Générale SA France 1,356.30

10 Intesa Sanpaolo SpA Italy 942.63

15 Crédit Mutuel Group France 852.56

20 DZ Bank AG Germany 559.00

28 XYZ Belgium 292.17

40 Nykredit A/S Denmark 215.5

49 Banka Monte dei Paschi di Siena SpA Italy 132.2

50 Bank of Ireland Group PLC Ireland 131.8

Source: Compiled by the author based on Ali (2020)

Based on the evidence above, the banking industry market can be divided into two strategic

segments using the Competitive Advantage Matrix presented in Figure 25: fragmented business

and specialized business. Banks with assets exceeding €100 billion, including the 50 largest banks

of the EU-28 area, can be referred to as specialized businesses with a high number of approaches

51

to achieving competitive advantage and large potential size of the advantage. Financial institutions

with assets less than €100 billion can be considered fragmented businesses with a high number of

approaches to achieving advantage and small potential size of advantage.

Figure 25: Competitive Advantage Matrix of the EU-28 banking industry


The banking market division into specialized and fragmented business segments should also be

reflected in the x-axis of the Product Portfolio Matrix. The market share of the leading competitor

has to be taken as the maximum value of the x-axis. Simultaneously, the midpoint should be

defined as 95% of the smallest specialized business competitor considering a random error of

estimation and representing the barriers to entry for fragmented businesses that strive to compete

in the specialized business segment.

Market Potential

As was previously described, the banking market of the EU-28 can be divided into two segments:

(1) debt instruments and (2) transactional operations. The evaluation of the market potential sticks

to this division and considers market sizes and market growth rates for these segments.

The primary goal of the market potential evaluation is to define the maximum value and midpoint

of the Product Portfolio Matrix's x-axis. It is necessary and sufficient to determine the market

shares of the largest and the smallest competitors in the specialized business segment to achieve

this goal. It was decided to evaluate the first two and the last two banks presented in Table 15 to

raise the estimations' accuracy by considering strategical differences in the companies’ strategy.

Table 16 shows shares of the assets controlled by the selected companies.

Table 16: Total market assets shares of the specialized business segment competitors

Rank Institution name Total market

assets, € billion Assets, € billion

Share in total

market assets

1 HSBC Holdings PLC

43,348.8

2,419.5 5.581%

2 BNP Paribas SA 2,164.7 4.994%

49 Banka Monte dei Paschi di Siena SpA 132.2 0.305%

50 Bank of Ireland Group PLC 131.8 0.304%

Source: Calculated by the author based on Table 15

52

Debt instruments

According to the European Banking Federation (2016-2020), the total amount of loans in 2019

was equal to €25.115 trillion exceeding the level of 2018 by 2.08%, which is 0.15% less than the

mean growth rate of 2.33% during the last five years as presented in Figure 26. Thus, the debt

instruments segment can be referred to as a growing one.

Figure 26: Dynamics of loans in the EU-28 from 2015 to 2019, € trillion

Source: Compiled by the author based on European Banking Federation (2016-2020)

The calculation of the selected companies’ market shares in the debt instruments segment is based

on the information derived from their financial statements as of December 31, 2019. The results

of the calculation are presented in Table 17.

Table 17: The selected companies’ market shares in the debt instruments segment

Rank Institution name Total market

loans, € billion Loans, € billion

Market segment

share

1 HSBC Holdings PLC

25,115.8

1,036.7 4.128%

2 BNP Paribas SA 805.8 3.208%

49 Banka Monte dei Paschi di Siena SpA 74.9 0.298%

50 Bank of Ireland Group PLC 79.5 0.316%

Source: Calculated by the author based on HSBC (2020), BNP Paribas (2020), Banka Monte dei Paschi di Siena SpA

(2020), and Bank of Ireland Group PLC (2020)

As seen in Table 17, the largest competitor in the debt instruments segment is HSBC Holdings

PLC controlled 4.128% of the market. The smallest competitor is Banka Monte dei Paschi di Siena

SpA had a segment market share of 0.298%. Therefore, the x-axis for the debt instrument market

segment should have the following characteristics:

- Maximum value = 4.128%;

- Midpoint = 0.298%*0.95 = 0.238% (according to the above-mentioned methodology);

- Minimum value = 0.00% (by definition).

Transactional operations

Unlike loans, account-related charges are not directly reflected in the financial statements.

Therefore, the transactional operations market size can only be determined indirectly by

multiplying total market assets’ value by the standard ratio of net fee income to total income. This

ratio can be estimated as the average for the four banks considered in the analysis.

The market segment growth rate is considered to be equal to the market assets growth rate.

According to the European Banking Federation (2016-2020), market assets' mean growth rate

22.9123.56 23.57

24.6025.12

2015 2016 2017 2018 2019

53

during the last five years was equal to -0.05%, as presented in Figure 27. Therefore, the

transactional operations market segment is characterized by a negative growth rate.

Figure 27: Dynamics of assets in the EU-28 from 2015 to 2019, € trillion

Source: Compiled by the author based on European Banking Federation (2016-2020)

Calculation of the market segment shares conducted based on the above-mentioned methodology

for the companies considered in Table 16 is based on the information derived from their financial

statements as of December 31, 2019. The results of the calculation are presented in Table 18.

Table 18: The selected companies’ market shares in the transactional operations segment

Rank Institution name Share in

total market

assets

Total

income,

€ billion

Net fee

income,

€ billion

Net fee

income (%

of total

income)

Market

segment

share

1 HSBC Holdings PLC 5.58% 71.024 12.023 16.93% 0.945%

2 BNP Paribas SA 4.99% 44.597 9.365 21.00% 1.049%

49 Banka Monte dei Paschi

di Siena SpA 0.30% 2.285 1.388 60.74% 0.185%

50 Bank of Ireland Group

PLC 0.30% 5.557 0.305 5.49% 0.017%



The market segment's total size can be estimated as 25.9% of the total assets on the market and

therefore was equal to about €11.5 trillion in 2019. The largest competitor in the transactional

operations segment was BNP Paribas SA, which controlled 1.049% of the market segment. The

smallest competitor was Bank of Ireland Group PLC, which owned the market segment share of

0.017%. Therefore, the x-axis for the transactional operations market segment should have the

following characteristics:




Industry Lifecycle Analysis

The lifecycle analysis considers the industry's division into specialized business and fragmented

business segments as determined in the Competitive Advantage Matrix and based on the

methodology proposed by MacRae (2020), which aims to define the stage of the industry lifecycle

according to the ten characteristics presented in Appendix E.

43.4443.38

43.19

42.89

43.35

2015 2016 2017 2018 2019

54

As described in Appendix F, all ten characteristics signalize that the banking industry is on the

maturity stage of the industry lifecycle. Moreover, considering the positive growth rate in the debt

instruments segment, which is the major segment of the market, it can be concluded that the

banking industry has not reached its peak yet and is relatively far from the decline stage as

presented in Figure 28.

Figure 28: The banking industry lifecycle


3.1.2 Insurance Industry

The insurance industry's overview shares the approach implemented for the discovery of the

banking industry. The overview contains the description of the insurance industry’s business

model, the Competitive Advantage Matrix examination, the evaluation of the market potential, and

the industry lifecycle analysis.

Business Model

Ross (2019) claims that insurance companies in their majority have two ways of revenue

generation: (a) charging premiums in exchange for insurance coverage, and (b) reinvesting those

premiums into other interest-generating assets. Therefore, insurance companies act similarly to

banks raising funds and getting income from their utilization. However, instead of renting the

money for people in the form of debt instruments, insurance companies mainly invest those funds

into securities and derivatives to later receive a speculative income.

The Insurance Process Classification Framework (APQC, 2019b) is identical to the one depicted

in Figure 24 on its categorical level. However, differences arise on the lower level starting from

the process group level. The main difference is seen in the 5.0 Deliver Service category that

includes 5.1 Deliver insurance services to customers (18644) process group in cased of insurance

PCF (APQC, 2019b) instead of Deliver banking services to customers (17416) process group

55

included in the banking PCF (APQC, 2019a). The 5.1 Deliver insurance services to customers

process category is further divided into the following processes (APQC, 2019b):

- 5.1.1 Manage and administer policies;

- 5.1.2 Manage and administer claims;

- 5.1.3 Manage policy and claim information record.

Unlike in the banking industry, there are no significant reasons to divide the insurance market into

segments based on the value proposition. Therefore, it should be observed in its wholeness during

the evaluation of the market potential.

Competitive Advantage Matrix

According to Insurance Europe (2020), the total amount of insurance premiums received by the

companies operating in the EU-28 market in 2018 was equal to €1.31 trillion distributed between

1,167 companies (Crunchbase, 2020). According to MAPFRE (2020), the 15 largest European

insurance groups (see Appendix G) received over €570 billion worth of insurance premiums,

which is 43.48% of the total amount received by all the companies operating on the market.

Therefore, similarly to the banking market, the insurance market can be divided into fragmented

business and specialized business segments using the Competitive Advantage Matrix, as presented

in Figure 29.

Figure 29: Competitive Advantage Matrix of the EU-28 insurance industry


The insurance market division into specialized and fragmented businesses should be reflected in

the x-axis of the Product Portfolio Matrix based on the assumptions applied to the banking market.

Market Potential

According to Insurance Europe (2016 – 2020), the total amount of insurance premiums in the EU-

28 market was averagely increasing by 2.58% per year starting from €1.18 trillion in 2014 and

resulting in €1.31 trillion in 2018, as presented in Figure 30. Therefore, the insurance market can

be referred to as a growing one with the growth rate exceeding the value for the banking market's

debt instruments segment by 0.25%.

56

Figure 30: Dynamics of insurance premiums in the EU-28 from 2014 to 2018, € trillion

Source: Compiled by the author based on Insurance Europe (2016-2020)

The distribution of the market shares of the companies mentioned in Appendix G is presented in

Figure 31.

Figure 31: Distribution of specialized segment companies’ shares in the insurance market

Source: Compiled by the author based on Appendix G (MAPFRE, 2020)

As seen in Figure 31, the largest competitor in the insurance market was AXA Group, with a

market share of 7.346%, while the smallest competitor was Ergo, which controlled 1.281% of the

market. Therefore, the x-axis of PPM for the insurance market should have the following

characteristics:




It is worth mentioning that the largest competitor of the banking industry, HSBC Holdings PLC,

in 2018 had an insurance premium income of €11.34 billion, meaning that the company controlled

0.865% of the insurance market and operated in its fragmented segment. In contrast, the second-

largest banking industry’s competitor, BNP Paribas SA, had the insurance market’s share of

1.831% and therefore operated in the specialized business segment.

Industry Lifecycle Analysis

The insurance industry lifecycle analysis shares the approach applied to the banking industry. As

described in Appendix H, the insurance industry dwells on the maturity stage of the lifecycle. This

statement is also proved by the insurance market’s mean annual growth of 2.58%. Thus, it can be

1.18 1.22 1.18 1.24 1.31

2014 2015 2016 2017 2018

1.281%

1.298%

1.356%

1.473%

1.719%

1.831%

2.465%

2.471%

2.558%

2.661%

2.949%

3.041%

5.087%

5.936%

7.346%

Ergo

Poste Vita

Covéa

Aegon

MAPFRE

BNP Paribas Cardif

CNP

Aviva

Crédit Agricole Assurance

Talanx

Prudential

Zurich

Generali

Allianz

AXA

57

concluded that the industry has not reached its peak yet. Moreover, the insurance industry is farther

from the decline stage than the banking industry, as shown in Figure 32.

Figure 32: The insurance industry lifecycle


3.2 Company Overview

This section is devoted to the overview of the XYZ Group with an emphasis on the BPM-related

areas. It can be contingently divided into two sub-sections: (1) the overview of the internal

environment based on the Strategy Map, and (2) the overview of the company’s performance

expressed in financial results and competitive position on the banking and insurance markets.

3.2.1 Internal Environment

This sub-section is devoted to the overview of the XYZ Group’s internal environment through

four perspectives reflected in its Strategy Map (see Appendix I). The overview starts with defining

the XYZ Group's strategic direction expressed in its vision, mission, and strategic principles. Then

Financial and Customer Perspectives of the Strategy Map are described based on the group’s

strategic objectives defined in KPIs. The Internal Perspective of the Strategy Map (i.e., process

architecture) is described based on the Process Landscape Model.

Vision, Mission, Strategic Principles and Objectives

The vision of the XYZ Group is “to be the reference for bank-insurance in all [its] core markets”

(i.e., Belgium, the Czech Republic, Slovakia, Hungary, Bulgaria, and Ireland). The company's

mission statement is formulated in the following way: “Through our activities, we want to help

our clients to both realize and protect their dreams and projects” (XYZ, 2020a). The strategy of

the XYZ Group is based on the four strategic principles as follows (XYZ, 2020a):

1) Client centricity We place our clients at the center of everything we do.

58

2) Bank-insurance We look to offer our clients a unique bank-insurance experience.

3) Sustainable, profitable growth We focus on sustainable and profitable growth.

4) Role in society We meet our responsibility to society and local economies.

From mission, vision, and strategic principles, it can be concluded that the XYZ Group is highly

customer-oriented and applies a differentiation strategy defined by Porter (1985) as a strategy

aimed at producing products and services considered unique industry-wide. Moreover, it can be

said that due to the corporate form of the XYZ Group’s organization, its main goal can be

perceived as the maximization of the long-term shareholders’ value, which is in line with the

concept of a balanced scorecard. Moreover, the goal can be expressed as making money now as

well as in the future, which corresponds with the ideas of TOC.

The XYZ Group's strategic objectives expressed in KPIs are derived into four groups associated

with the strategic principles stated above. The three first groups taken together can be used as

inputs for XYZ’s strategy map, while the fourth group reflects the company’s responsibilities to

fulfill sustainability requirements set by the United Nations and is out of the thesis’s scope.

Sustainable profitable growth KPIs

The sustainable profitable growth KPIs represent the financial perspective of the XYZ Group’s

strategy map (see Appendix I). These KPIs are presented by the compound annual growth rate

(CAGR) of total income, cost/income ratio, combined ratio, and innovation index. CAGR of total

income may be referred to as CAGR of throughput in TOC terms and therefore is the closest to

the organization's primary goal of making money now as well as in the future than all other KPIs.

The cost to income ratio measures financial performance regarding XYZ’s banking activities and

is calculated using the following formula (XYZ, 2020a):

Cost to income ratio =Operating expenses of the total banking activities

Total income of the banking activities

The combined ratio measures the financial results of XYZ’s insurance activities and is calculated

based on the formula below (XYZ, 2020a):

Combined ratio = Technical insurance charges

Earned insurance premiums+

Operating expenses

Written insurance premiums

The innovation index reflects the Group’s ability to continuously launch innovative solutions faster

than competitors to improve client experience and exceed clients’ expectations (XYZ, 2020a).

Targets and results regarding the sustainable growth KPIs are presented in Table 19.

Table 19: Sustainable profitable growth KPIs of the XYZ Group in 2019

KPI Target and result Dynamics of KPI from 2017 to 2019

CAGR of

total income - Target 2016-2020: ≥ 2.25%

- 2016-2019 result: +2.32%

6.8%

-1.7%2.0% 2.3%

16-17 17-18 18-19 CAGR 16-19

59


Cost to

income ratio - Target: ≤ 54% in 2020

- 2019 result: 57.9%

Combined

ratio - Target: ≤ 94% in 2020

- 2019 result: 90%

Innovation - Target: achieve the same or a

higher score than the peer group

average per country.

- 2019 result: the scores in

Belgium and Ireland were above

the peer group average. Those in

Slovakia and Hungary were in line

with the peer group average. The

scores in Bulgaria and the Czech

Republic were below the peer

group average.

Source: Compiled the author based on XYZ (2020), p. 42

As follows from Table 19, the average CAGR of total income exceeds the target by 0.07% as of

December 31, 2019. It can also be concluded that banking activities are executed not as well as

planned since the cost/income ratio in 2019 was 3.9% above the target for 2020. As for insurance

activities, the target of at least 94% in 2020 is not yet achieved, and considering the dynamics of

the KPI during the last three years will not be achieved in a business-as-usual way. Finally, the

innovation index results vary from country to country, and the Czech Republic and Bulgaria

innovation indexes are less than the industry average.

Client centricity KPIs

Three client centricity KPIs are reflected in the customer perspective of the XYZ Group’s strategy

map (see Appendix I). The reputation index reflects the overall public attitude towards the

company and is measured against the company’s competitors (i.e., peer groups) in respective

geographical markets. The client experience indicator is estimated based on the methodology

similar to the net promoter score described in the 1.3.2 Process Enactment section and compared

with competitors. The reputation index and client experience indicator are calculated for the XYZ

Group's six geographical markets (i.e., Belgium, Czech Republic, Slovakia, Hungary, Bulgaria,

and Ireland). The digital interaction is expressed as the proportion of clients who interact with

XYZ via at least one of the non-physical channels. Unlike the two previous KPIs, it does not

concern the competitors' results. As shown in Table 20, the XYZ Group had achieved all its client-

centricity goals in 2019.

54.2% 57.5% 57.9%

2017 2018 2019

88% 88% 90%

2017 2018 2019

1 2 22

2 23 2 2

2017 2018 2019

Higher Same Lower

60

Table 20: Client centricity KPIs of the XYZ Group in 2019


Reputation

index - Target: achieve the same or a



- Result: all 6 countries scored

in line with the peer group

average.

Client

experience - Target: achieve the same or a



- Result: all 6 countries scored

in line with the peer group

average.

Digital

interaction - Target: ≥ 80% in 2020

- Result 2019: 81%

Source: Compiled by the author based on XYZ (2020), p. 36

Bank-insurance KPIs

Similar to client centricity KPIs, two bank-insurance KPIs are also included in the customer

perspective of the XYZ Group’s strategy map (see Appendix I). The CAGR of bank-insurance

clients is the share of clients holding at least one banking and one insurance product of the

company in the total number of clients. In comparison, the CAGR of stable bank-insurance clients

is the share of clients holding at least two banking and two insurance products (3 and 3 for

Belgium) in the total number of clients. Targets for both above-mentioned KPIs are set for the

period from 2016 to 2020. They are divided into three main geographical areas: Belgium, Czech

Republic, and International Markets (i.e., Slovakia, Hungary, Bulgaria, and Ireland). Figure 33

represents targets and intermediate results for both bank-insurance KPIs.

Figure 33: Bank-insurance KPIs of the XYZ Group in 2019

(a) CAGR of bank-insurance clients

46 6

2

2017 2018 2019

Lower Same Higher

5 6 6

1

2017 2018 2019

Lower Same Higher

74% 78% 81%

2017 2018 2019

1%

12%

22%

2%

15%

10%

Belgium Czech Republic International Markets

Result 16-19

Target 16-20

61

(b) CAGR of stable bank-insurance clients

Source: Compiled the author based on XYZ (2020), p. 39

As seen from Figure 33a, in 2019, the target for CAGR of bank-insurance clients is achieved for

international markets, while for Belgium and the Czech Republic, it is not reached yet. As follows

from Figure 33b, the level of CAGR of stable bank-insurance clients has exceeded the target by

200% in Belgium, while not yet achieved for the Czech Republic and International Markets.

Process Architecture

As mentioned above, XYZ is an international bank-insurance group. Therefore, the first level of

XYZ’s process architecture should its banking and insurance activities. As mentioned in the 3.1.1

Banking Industry sub-section, two core process groups that make up the typical business model of

commercial banks are “Manage Debt Instruments” and “Manage Transactional Operations”, and

XYZ does not make an exception. Insurance activities can be reflected in the core process group

called “Manage Insurance Products”. Processes that make up the above-mentioned core process

groups, as well as support and management processes, are in their majority similar to those that

make up the Banking Process Classification Framework previously presented in Figure 24.

Moreover, the responsibility for efficient execution of management, core, and support processes

of the XYZ Group is spread among organizational units (also referred to as ‘domains’) that make

up the group's organizational structure shown in Appendix J.

Figure 34: The Process Landscape Model of the XYZ Group


2%

15% 15%

1%

17%

25%

Belgium Czech Republic International Markets

Result 16-19

Target 16-20

62

Thus, the process landscape model of the XYZ Group can be presented in the way depicted in

Figure 34. Management, core, and support processes that make up the model and represent the

internal perspective of the XYZ Group’s strategy map (see Appendix I) are described in more

detail below.

Management Processes

As mentioned before, management processes provide rules and practices for core and support

processes. According to Figure 34, the XYZ Group executes six management processes as follows.

Develop Vision and Strategy This process includes strategic management activities undertaken

in the company. It mainly concerns articulating its vision and mission statements and formulating

strategic goals and objectives to implement them.

Manage Quality The aim of this process is to ensure that the company's products and services are

delivered according to the quality requirements. In other words, this process includes activities

within the quality management initiative undertaken in the company.

Manage Change This process includes project management activities aimed at implementing

changes in the company.

Manage Risks This process includes activities that make up the risk management lifecycle:

identify risks, analyze risks, plan risk response, monitor and control risks.

Manage Innovation This process includes activities that make up the scope of knowledge and

innovation management initiatives and enhance the company's innovative potential and increase

the number of innovations introduced by the company’s employees.

Communicate in and out This process aims to maintain and increase the company’s goodwill

through efficiently managing public relations and communications with external stakeholders

(e.g., clients, governments, etc.).

Core Processes

As claimed above, core processes cover the essential value creation of the company. The XYZ

Group executes eight core processes defined below.

Manage Accounts This process consists of activities such as open accounts, maintain accounts,

close accounts. An account is a prerequisite for conducting any bank-related operations.

Manage Transactions This process aims to make sure that transactions conducted by clients fit

legal regulations (e.g., embargo check), and doesn’t contain any errors (e.g., wrong beneficiary

account), and therefore can be processed as soon as possible.

Manage Deposits This process aims to raise funds through interest-bearing liabilities (i.e.,

deposits) and fulfill obligations gained after a client has opened the deposit account (i.e., pay

interest).

Develop Debt Instruments This process aims at creating a unique configuration of debt

instruments features (e.g., the value of interest payment) to increase the chances of winning the

competition.

Market and Sell Debt Instruments This process consists of promoting the bank's debt

instruments to create a maximum product awareness that will later result in the selling of these

instruments through various channels (e.g., bank branches, bank’s applications).

63

Develop Insurance Products This process aims at creating a unique configuration of insurance

products’ features (e.g., the value of interest payment) to increase the chances of winning the

competition.

Market and Sell Insurance Products This process consists of promoting the bank's insurance

products to create a maximum product awareness that will later result in selling these instruments

through various channels (e.g., insurance agencies, bank’s applications).

Manage Claims This process includes different actions such as facilitate claim reporting, liaise

with claimants, investigate and evaluate claims, negotiate and settle claims, recover money paid

out, and close claims. These actions are aimed at fulfilling the terms of the insurance contract at

best possible level.

Support Processes

As mentioned above, support processes enable the execution of core processes. According to

Figure 34, the XYZ Group executes six support processes described below in more detail.

Develop Applications This process includes activities aimed at developing (i.e., adding new or

improving existing features) and maintaining various bank’s applications (e.g., online banking,

mobile banking). These applications enable the digital interaction between customers and the XYZ

Group in multiple fields (e.g., execution of transactions).

Manage Human Resources This process consists of attraction, recruitment, onboarding,

enablement, development, retention, and separation of personnel to assure the best possible quality

of human resources involved in the company’s processes.

Manage Information This process is aimed to ensure a smooth flow of information within the

organization while following internal policies and external regulations. It also concerns with

implementing and developing ICT capabilities to ensure high efficiency of process execution.

Manage Financials This process aims to increase the amounts gained from selling the bank’s

products (i.e., debt instruments, insurance products) to multiply incomes by earning speculative

income from investments and other ways.

Manage Incidents This process assures business continuity through the timely elimination of

emerging incidents (e.g., fire in the office).

Manage Customer Service This process aims to consult customers regarding the questions they

have and resolve their particular issues during interaction with the bank’s products and services.

3.2.2 Company Performance

The description of the XYZ Group’s performance from 2015 to 2019 is two-fold. Firstly, the

dynamics of the XYZ Group’s financial indicators are presented to estimate its financial

performance over the observed period. Secondly, the company's competitive market position is

defined for debt instruments, transactional operations, and insurance markets based on the Product

Portfolio Matrix. Results obtained in the 3.1 Industry Overview section are used as inputs to PPM

and, therefore, set a linkage between the XYZ Group's external and internal environments.

Financial Performance

In 2019, over 90% of XYZ's total income had come from three sources: net interest income, net

fee, and commission income, and insurance income. Moreover, around 3.5% of the group’s total

64

income came from financial banking, mostly concerned with handling financial assets (e.g.,

securities and derivatives) and managing mutual funds. The dynamics of XYZ’s main financial

indicators for the last five years are presented in Table 21.

Table 21: Financial indicators of the XYZ Group from 2015 to 2019, € million

Financial Indicator As of December 31, Growth rate, %

2015 2016 2017 2018 2019 19/15 Mean 19/18

Total income, including 7,146 7,210 7,700 7,511 7,628 6.75 1.65 1.56

Net interest income 4,311 4,258 4,121 4,543 4,618 7.12 1.73 1.65

Net fee income 1,678 1,450 1,707 1,719 1,734 3.34 0.82 0.87

Net insurance income 381 438 640 701 725 90.29 17.45 3.42

Financial banking income 479 806 1,118 322 269 -43.84 -13.43 -16.46

Other net income 297 258 114 226 282 -5.05 -1.29 24.78

Operating expenses -3,890 -3,948 -4,074 -4,234 -4,303 10.62 2.55 1.63

Operating income 3,256 3,262 3,626 3,277 3,325 2.12 0.53 1.46

Operating margin, % 45.56 45.24 47.09 43.63 43.59 -4.33 -1.10 -0.09

Net income 2,639 2,427 2,575 2,570 2,489 -5.68 -1.45 -3.15

Source: Compiled by the author based on XYZ (2017 - 2020)

Over the last five years, the company's total income has been stably increasing on average by

1.65% per annum. From its value of about €7.51 billion in 2018, the total income has risen to

almost €7.63 billion in 2019, showing a 1.56% growth rate, which is slightly below the mean

growth rate over the observed period. The net interest income, which made up about 60.5% of the

total XYZ’s income in 2019, has grown by 1.65% in 2019 compared to its level of 2018, which is

slightly less than the mean yearly growth rate of 1.73% observed over the last five years. The

second-largest income source, the net fee income, has made up about 22.7% of XYZ’s total income

in 2019 and increased by 0.87% compared to its level in 2018, slightly exceeding the mean growth

rate over the last five years.

The net insurance income has grown from €381 million in 2015 to €701 million in 2019,

representing an increase of about 90.3% and is considered as the XYZ Group’s fastest-growing

business. In contrast, financial banking income had dramatically decreased in 2018 compared to

2017 by over 70% and continued to decline in 2019. However, this decline has been caused by a

reconsideration of XYZ Group’s strategy in reaction to increased volatility in the financial

markets.

The average yearly growth rate of the XYZ Group’s operating expenses exceeded the growth rate

of total income by about 0.9% resulting in a 1.1% average decrease in operating margin during the

observed period. Given the constant corporate tax rate, the trend mentioned above has resulted in

a mean net income decrease of 1.45% per year over the examined period. However, the growth

rate of net income in 2019 compared to its level in 2018 has exceeded its mean value by over 2.17

times and has been equal to 3.15% representing the absolute decline of €81 million.

Competitive Market Position

The competitive market position of the XYZ Group is determined for debt instruments,

transactional operations, and insurance markets that were closely examined in the 3.1 Industry

Overview section of the thesis. The market share determination is based on the methodology earlier

applied to competitors.

65

Debt instruments

As presented in Figure 35, the value of loans in the XYZ Group’s balance sheet has increased from

€128.23 billion in 2015 to €155.6 billion in 2019, showing the mean annual growth rate of 4.95%,

which is 2.12 times more than the market segment’s growth rate of 2.33% during the same period.

Figure 35: Dynamics of the XYZ Group’s loans from 2015 to 2019, € billion

Source: Compiled by the author based on XYZ (2017-2020A)

Given the total value of loans of 25,115.8 billion, the share of the XYZ Group in the debt

instruments segment was equal to 0.62% exceeding the PPM’s x-axis midpoint of 0.238%.

Considering the debt instruments market's positive growth rate, it can be concluded that the XYZ

Group should be placed in the quadrant II of the debt instruments market segment’s PPM, as shown

in Figure 36. Therefore, the XYZ Group’s business on the debt instruments market is referred to

as a star.

Figure 36: A PPM of the debt instruments market segment


Transactional operations

As shown in Figure 37, the value of assets in the XYZ Group’s balance sheet has increased from

€252.36 billion in 2015 to €290.74 billion in 2019, demonstrating the mean annual growth rate of

3.6%. Moreover, the net fee income was on average annually increasing by 0.82% from 2015.

128.23133.23

141.00146.95

155.60

2015 2016 2017 2018 2019

66

Figure 37: Dynamics of the XYZ Group’s assets from 2015 to 2019, € billion

Source: Compiled by the author based on XYZ (2017-2020a)

Given the market’s total value of assets of 43,348.8 billion and 22.73% share of net fee income in

the total income of the company, the XYZ Group controlled about 0.152% of the transactional

operations segment exceeding the x-axis midpoint of 0.016%. Moreover, the transactional

operations segment’s growth rate was previously referred to as negative. Therefore, it can be

concluded that the XYZ Group should be placed in quadrant III of the transactional operations

market segment’s PPM, as shown in Figure 38. Therefore, the XYZ Group’s business on the

transactional operations market is referred to as a cash cow.

Figure 38: A PPM of the transactional operations market segment


Insurance

As shown in Figure 39, the value of insurance premiums received by the XYZ Group has increased

from €2.62 billion in 2015 to €3.04 billion in 2019, demonstrating the mean annual growth rate of

3.82%, which is 1.2% higher than the market’s mean yearly growth rate.

252.36

275.20

292.34283.81

290.74

2015 2016 2017 2018 2019

67

Figure 39: Dynamics of the XYZ Group’s insurance premiums from 2015 to 2019, € billion

Source: Compiled by the author based on XYZ (2017-2020A)

Given the market’s total value of insurance premiums of €1,311 billion, the share of the XYZ

Group in the insurance market was equal to 0.232%, which is less than the PPM’s x-axis midpoint

of 1.217%. Moreover, the insurance premiums were growing over the last five years. Thus, it can

be concluded that the XYZ Group’s insurance business should be placed in quadrant I of the

insurance market’s PPM, as shown in Figure 40. Therefore, the XYZ Group’s insurance business

is referred to as a question mark.

Figure 40: A PPM of the insurance market


3.3 Payments Domain Overview

Payments Domain is placed in Brno and includes three teams that interact to provide the best

payment solutions to the whole XYZ Group. These teams are Payments Processing, Claims &

Investigations, and Payments Design. The first two are involved in the Manage Transactions core

process, as presented in the XYZ Group’s process landscape model (see Figure 34).

Simultaneously, the Payments Design team is committed to the continuous improvement of the

bank's internal applications to increase the other two teams' operational efficiency.

Domain Strategy

The so-called strategy house of Payments Domain that follows the ideas of the balanced scorecard

(Kaplan & Norton, 1992) is presented in Figure 41.

2.62

2.99

2.692.94 3.04

2015 2016 2017 2018 2019

68

Figure 41: A strategy house of the Payments Domain

Source: XYZ (2020b)

As seen in Figure 41, the Payments Domain aims to maintain a good reputation and increase client

satisfaction through in-time and on-cost processing of the transactions initiated by clients.

Therefore, Payments Domain impacts the successful fulfillment of Client experience and

Reputation index KPIs of the XYZ Group by executing the Manage Transactions core process

described in more detail in the next sub-section. It also can be seen from Figure 41 that the

Payments Domain shares the values that can be found in the BPM-oriented culture.

Domain Process Architecture

The Payments Domain is involved in two processes from the XYZ Group’s Process Landscape

Model. The Payments Processing and the Claims & Investigations teams execute two sub-

processes that make up the Manage Transactions core process, while the Payment Design Team

contributes to the Develop Applications support process. As concluded in the 1.2.3 Process

Selection section, the core processes are given the most significant attention while selecting a

process for a future redesign. Therefore, the “Manage Transactions” process should be described

in more detail, while the description of the “Develop Applications” support process can and would

be omitted.

Figure 42: A “Manage Transactions” process

Source: Elaborated by the author based on XYZ (2020b)

69

As depicted in Figure 42, the “Manage Transactions” process consists of two sub-processes:

“Process Payments” and “Investigate Claims”. The process profile presented in Table 22 is

compiled based on interviews with the Payments Domain’s team leaders, documents from the

XYZ (2020b), and observation. It describes the Manage Transactions process in more detail.

Table 22: Process profile of the “Manage Transactions” process

Name of Process: Manage Transactions

Vision: The objective of the Manage Transactions process is to make sure that transactions conducted by clients

fit legal regulations (e.g., embargo check), and does not contain any errors (e.g., wrong beneficiary account), and

therefore can be processed as soon as possible.

Process Owner: Payments Domain

Process Customer: The XYZ Group’s retail or professional clients

Customer Expectations: The payment should be processed as soon as possible and not require unnecessary

commission payments.

Outcome: Payment processed OR Problem solved

Trigger: Payment initiated

First activity (sub-process) Process Payments

Second activity (sub-process) Investigate Claims

Interface inbound: Manage Accounts

Interface outbound: Manage Deposits, Market and Sell Debt Instruments, Market and Sell Insurance Products

Required resources:

- Human resources: Payments Domain’s Officers

- Information, documents, know-how: Request for payment, process algorithms, claim form

- Work environment, materials, infrastructure: Payments Engine, Intranet Tools

Process Performance Measures:

- Cycle Time

- Operational Costs

- Error Rate


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4 Analysis

This chapter is devoted to describing actions performed to achieve the first two secondary

objectives of the research presented in the 2.1 Research Objectives section and follows the BPM

lifecycle stages associated with these objectives: Process Selection, Process Discovery, and

Process Analysis. “Process Payments” and “Investigate Claims” sub-processes selected in the

previous chapter are compared based on strategic importance, health, and feasibility criteria in the

4.1 Process Selection section to choose the bottleneck process and therefore achieve the first

secondary objective of the research. 4.2 Process Discovery section is devoted to the development

of the as-is model of the selected process. The model is later examined in the 4.3 Process Analysis

section to identify root causes that influence the process performance.

4.1 Process Selection

Following the process of process selection presented in Figure 13, we should begin the process

selection by prioritizing the “Process Payments” and “Investigate Claims” sub-processes by

strategic importance. Then these sub-processes should be compared by health and feasibility (if

process health ratios are equal).

Strategic Importance

Process performance measures presented in Table 22 are logically derived from the Reputation

Index and Client experience KPIs of the XYZ Group in the way shown in Figure 43.

Figure 43: The process performance measures and the XYZ Group’s KPIs


As follows from Figure 43, the decrease in error rate and the reduction of cycle time positively

influence the customer experience and increase the reputation index. Raise in customer experience

and reputation index KPIs leads to the increase of the XYZ Group’s clientele, which positively

correlates with the group’s income. Simultaneously, a decrease in the operational costs caused by

the execution of the “Manage Transactions” process impacts the overall costs and reduces the Cost

to Income Ratio.

However, as follows from the Devil’s Quadrangle (see Figure 9), a parallel decrease of all three

performance measures of the process is impossible. Since the reduction of error rate (i.e., quality

dimension) typically achieved by the more extended observation of the particular case inevitably

leads to the increase of the cycle time and raises the operational costs associated with the process

71

execution. In other words, cycle time links the error rate representing the health of the processes

and operating costs that impact the strategic importance. Therefore, it seems reasonable to consider

the cycle time as the primary process measure to identify the “Manage Transactions” process's

constraints using the Flow Analysis technique.

As seen in Figure 42, the “Manage Transactions” process consists of one XOR-block, and

therefore its cycle time (CT) should be estimated based on the following formula:

𝐶𝑇 = ∑ 𝑝𝑖 ∗ 𝑇𝑖

𝑛

𝑖=1

The probability, 𝑝1, of the “Investigate Claims” sub-process execution, can be estimated as the

share of payments that were transformed into claims after the check of restrictive conditions, while

the probability, 𝑝2, of the “Process Payments” sub-process execution is calculated as (1 – 𝑝1). The

average cycle time of both sub-processes is estimated based on the historical data about the process

execution during 2019, as presented in Table 23.

Table 23: An average cycle time of the “Manage Transactions” process in 2019

Process Quantity of process

instances, thousand

𝒑𝒊 𝑻𝒊, sec 𝒑𝒊 ∗ 𝑻𝒊, sec

Process Payments 13,134.74 0.9996 4.468 4.466

Investigate Claims 5.26 0.0004 1300.000 0.520

Manage Transactions 13,140.00 1.0000 CT = 4.9865

Source: Compiled by the author based on XYZ (2020b)

According to XYZ (2020b), 13.14 million payments were executed by the Payments Domain in

2019. More than 96% of them were Straight Through Process (STP) payments executed without

human intervention, while about 1% of Non-STP payments were investigated as claims. Since

STP payments are processed almost immediately (i.e., within 0.02 sec), the average cycle time of

the “Process Payments” sub-process equals 4.468 sec. In contrast, the “Investigate Claims” sub-

process can be executed only by human resources. Therefore, its average execution, excluding idle

time caused by waiting for responses while communicating with external stakeholders, equals

21.67 min (i.e., 1,300 sec).

As follows from the pie chart presented in Figure 44, almost 90% of the average cycle time of the

“Manage Transactions” process is impacted by the “Process Payments” sub-process. Therefore,

the “Process Payments” sub-process strategic importance is higher than that of the “Investigate

Claims” sub-process.

Figure 44: Weights of the “Manage Transactions” process’ sub-processes in its cycle time


Process Payments, 89.57%

Investigate Claims, 10.43%

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Health

As mentioned in the respective part of the 1.3.3 Process Selection section of the thesis, the process's

health is estimated through the process health ratio calculated by dividing actual process

performance by its target performance. Both examined processes have their KPIs expressed in

terms of error rate and, therefore, can be compared using this metric as an input to the process

health ratio.

The calculation of the process health ratio presented in Table 24 follows the algorithm described

in Figure 10. Since the above-mentioned algorithm is used in the LSS methodology, the process

yield's target values are set based on the LSS goal of achieving 3.4 defects per million

opportunities.

Table 24: A process health ratio of the “Manage Transactions” process’ sub-processes

Sub-process # of process

inputs,

thousands

# of defective

outputs

Error

rate

Yield Process

Health

Ratio Target Actual

Process Payments 13,134.74 520 0.0000396 0.9999966 0.9999604 99.9964%

Investigate Claims 5.26 126 0.0239726 0.9999966 0.9760274 97.6031%

Source: Calculated by the author based on XYZ (2020b)

Table 24 shows that the process health ratio for the “Investigate Claims” is slightly less than for

the “Process Payments” sub-process. It leads to the conclusion that the “Investigate Claims” sub-

process is less healthy than the “Process Payments” one. However, the difference is not enough to

select the “Investigate Claims” sub-processes for a future redesign. Therefore, the Process

Payments sub-process is considered a bottleneck sub-process of the “Manage Transactions”

process and should be discovered in more detail.

4.2 Process Discovery

This section is devoted to developing the as-is process model of the “Process Payments” business

process that should meet syntactic, semantic, and pragmatic quality requirements. Four activities

described in the 1.2.4 Process Discovery section of the thesis are conducted to achieve this goal.

Setting Definition

The process discovery project was conducted in close collaboration with the Payments Processing

Team of Payments Domain, including the Team Leader, Payments Processing Officer, and

Authorization Officer, who acted as the domain experts.

Information Gathering

The method of information gathering implemented for the selected process discovery consisted of

evidence-based and interview-based techniques. More specifically, the general description of the

process was provided by the Payments Processing Team Leader. Then, the observation of the

Payments Processing Officer and the Authorization Officer's work was conducted to delve into the

details of the process flow followed by a short interview with the Team Leader aimed to eliminate

misunderstandings that left after previous steps.

Process Description

The process description given by the Payments Processing Team Leader is provided below:

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There are two kinds of payments in the XYZ Group initiated by our clients: STP payments processed without

any human intervention, and Non-STP payments that require manual changes performed by our Officers.

STP payments are processed by Payments Engine (PE), which is our ICT environment. It scans payments for

errors, and if no errors are found, then the payment is processed automatically and is considered STP.

However, if PE finds an error, then the payment becomes available for our Payments Processing Officers,

who perform some manual changes according to the type of error that appeared in a particular payment. Our

company follows the policy of four-eye control, and every payment is authorized by another person who can

have a fresh look at the payment and notice mistakes that were not noticed by the system. When the

Authorization Officer finds some mistakes, the process starts again until the payment does not contain any

errors.

Following process elements can be distinguished from the description above:

Process boundaries The process is triggered when payment is initiated by the client, while the

payment execution signals the process completion.

Main process activities and intermediate events No intermediate events were noticed in the

process description, while the following process activities presented in its sequential order can be

distinguished from it:

- Scan for errors;

- Correct errors;

- Authorize payment;

- Execute payment.

Resources Process is performed by Payments Engine (PE), Payments Processing Officer, and

Authorization Officer.

Decision points XOR-decisions are made after “Scan for errors” and “Authorize payment”

activities.

Potential rework The process contains the “Authorize payment” – “Check for restrictions” loop

structure.

Additional elements Not identified.

Observation

After process elements were distinguished from the process description provided above, the

decision was made to perform a passive observation over two Officers mentioned in the

description. The results of the observation are provided below.

Payments Processing Officer (PPO) After the PPO starts her work on “to complete” payment,

she firstly checks for restrictions that may they occur should be investigated by the Claims &

Investigations Team. If the payment contains a restrictive condition, then the PPO initiates an

investigation by creating a case in either the Pega IT System or directly in PE. If the investigation

is initiated in Pega, Officer assigns the “problem-solving” status to the payment, while if the

investigation is initiated in PE, this action is performed automatically. Then the investigation is

authorized by the Authorization Officer (AO), and if some errors are found, PPO updates the case

and sends it to authorization once again.

When payment contains mistakes, the Officer corrects them based on her tacit knowledge or

referring to one or several documents (i.e., MS Word and MS Excel documents) containing

supporting information depending on a type of error. After the PPO corrected the mistake, she

74

presses the “process” button, and the payment changes its status to “to authorize” and goes to the

Authorization Officer.

Authorization Officer After the AO starts her work on “to authorize” payment, she checks

whether the Payments Processing Officer dealt with the error correctly. To do so, the AO performs

all the tasks conducted earlier by the PPO. If she comes to the same result, the payment is

authorized and sent to the system to be executed. Similar to the PPO, the AO uses either her tacit

knowledge or consults with a set of supporting documents and external data sources to conduct

her task. The AO also authorizes investigations, and if no issues are found, the investigation goes

under the Claims & Investigations Team's responsibility. If a problem is found, the case is sent

back to PPO for revision.

The list of earlier identified process elements can be extended based on the observation results as

described below.

Process boundaries The process might finish after the investigation was initiated when the

payment contains any restrictive conditions.

Main process activities and intermediate events The following process actions can be identified

in addition to the previously identified ones:

- Check for restrictions;

- Initiate Investigation;

- Assign “Problem-solving” status;

- Authorize investigation.

Resources Claims & Investigations Team was identified as an additional external process

stakeholder.

Decision points Two additional decision points identified are as follows:

- XOR-decision after Check for restrictive conditions activity;

- XOR-decision after Initiate investigation activity.

Potential rework It would be more accurate to redefine the boundaries of the “Authorize payment

– Correct error” repetition loop to “Authorize payment – Check for restrictions”.

Additional elements Pega IT System and Set of supporting documents.

Interview

The information-gathering process has finished with a semi-structured interview with the

Payments Processing Team Leader presented in Appendix K that contained some pre-coded

questions to specify the process boundaries. After the interview, it was decided to name the process

trigger as “Payment order received”.

Business process modeling

Business process modeling activity was performed based on the five-step algorithm presented in

the respective sub-section of the 1.3.4 Process Discovery section of the thesis using the information

obtained during the information gathering as input. Elements of the process included in the scope

of the above-mentioned algorithm are presented in the as-is process model shown in Appendix L

that was successfully verified in the Signavio modeling environment and validated by the

75

Payments Processing Team Leader. The process elements are also described in the process profile

presented in Table 25.

Table 25: A process profile of the “Process Payments” process

Name of Process: Process Payments

Vision: The objective of the “Process Payments” process is to make sure that payments initiated by clients do not

contain any errors, and therefore can be processed as soon as possible.

Process Owner: Payments Processing Team




Outcome: Payment processed OR Investigation Initiated

Trigger: Payment order received

Activity 1 Scan for errors

Activity 2 Check for restrictions

Activity 3 Initiate investigation

Activity 4 Assign “Problem-solving” status

Activity 5 Authorize investigation

Activity 6 Correct error

Activity 7 Authorize payment

Activity 8 Execute payment


Interface outbound: Investigate Claims

Required resources:

- Human resources: Payments Engine, Payments Processing Officer, Authorization Officer

- Information, documents, know-how: Payment order, Set of supporting documents

- Work environment, materials, infrastructure: Pega IT-System


- Cycle Time

- Operational Costs

- Error Rate


4.3 Process Analysis

The analysis of the “Process Payments” process aims to reach the research’s secondary objective

of identifying root causes that influence the process performance. It is necessary to develop a

Current Reality Tree to achieve this objective. Causal factors to be inserted into the CRT can be

identified using Flow Analysis, Value Stream Analysis, Waste Analysis, and Ishikawa Diagram.

Relationships between the identified factors can be validated using the statistical methods chosen

depending on the type of the examined variables described in the respective part of the 1.3.5

Process Analysis section.

4.3.1 Flow Analysis

Table 26 presents the cycle time calculation of the “Process Payments” process based on the

individual process activities’ probability of occurrence and average duration. It is worth to mention

that since Payments Engine (PE) conducts tasks almost immediately, their duration (Ti) was

estimated to be equal to 0.01 sec.

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Table 26: Cycle time of the “Process Payments” process activities, sec

№ Activity Resource T, sec p CT, sec

1 Scan for errors PE 0.01 1.000000 0.0100

2 Check for restrictions PPO 10 0.044444 0.4444

3 Initiate investigation PPO 55 0.000494 0.0272

4 Assign "Problem-solving" status PPO 5 0.000370 0.0019

5 Authorize investigation AO 30 0.000494 0.0148

6 Correct error PPO 50 0.044000 2.2000

7 Authorize payment AO 40 0.044000 1.7600

8 Execute payment PE 0.01 1.000000 0.0100

TOTAL X X X 4.4683


Pareto Chart depicted in Figure 45 shows that “Correct error”, “Authorize payment”, and “Check

for restrictions” activities constitute over 95.5% of the process cycle time and thus should be

investigated more thoroughly.

Figure 45: Pareto Chart for “Process Payments” process


4.3.2 Value Stream Analysis

Table 27 presents the classification of the “Process Payments” process activities. Five activities

are referred to as value-added since they support the achievement of the process vision (i.e., to

make sure that payments initiated by clients do not contain any errors, and therefore can be

processed as soon as possible). “Authorize investigation” and “Authorize Payment” activities are

considered business-value added because they are executed to implement the four-eye policy.

Table 27: A value stream analysis of the “Process Payments” process

№ Activity Resource Classification

1 Scan for errors PE VA

2 Check for restrictions PPO VA

3 Initiate investigation PPO VA

4 Assign "Problem-solving" status PPO NVA

5 Authorize investigation AO BVA

6 Correct error PPO VA

7 Authorize payment AO BVA

8 Execute payment PE VA


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The “Assign ‘Problem-solving’ status” activity currently executed by the Payments Processing

Officer increases the process cycle time by 0.0019 sec. The activity can be eliminated from the

business process since it is referred to as a non-value-added one.

4.3.3 Waste Analysis

Motion waste does not appear in the process because all the process participants do not have to

change locations to perform process activities. There is also no overprocessing waste because all

the work is performed by the client's order. Since the WIP level at the end of the day equals zero

due to the process execution's specifics, the inventory waste is considered absent in the process.

From the rest four waste types, overproduction waste occurring when a client cancels the payment

cannot be dealt with because clients have the right to do so based on the existing regulations. Three

other types of waste (i.e., transportation, defect, and waiting) are described in more detail below.

Transportation waste

According to Dumas et al. (2018), every message flow present in a process can be referred to as a

potential transportation waste. Table 28 shows all the process’ message flows and contains

assumptions regarding the possibility of their elimination.

Table 28: Message flows in the “Process Payments” process

№ Preceding

activity (PA)

Resource Succeeding

activity (SA)

Resource Elimination

possibility

Comment

1 Scan for errors PE Check for

restrictions

PPO No Only PPO can perform

the SA

2 Initiate

investigation

PPO Authorize

investigation

AO No Four-eye policy

3 Authorize

investigation

AO Initiate

investigation

PPO Yes PA can do rework

4 Correct error PPO Authorize payment AO No PE cannot process the

payment if it contains

an error

5 Authorize

payment

AO Check for

restrictions

PPO Yes PA can do rework

6 Authorize

payment

PA Execute payment PE No Payments execution is

only done in PE


As seen in Table 28, not all the transportation waste can be eliminated due to active business rules

and configuration of Payments Engine. However, message flows occurring after payment or

investigation were not authorized can be removed from the process since there are no strict rules

forbidding Authorization Officers to correct mistakes they identified. According to Payments

Processing Team Leader, these message flows occur because “Officers learn from their mistakes

when payments they did wrongly go back to them”.

Defect waste

As mentioned in Table 11, defects in a process mainly appear in the form of repetition loops. As

shown in Table 29, there are three repetition loops (i.e., rework blocks) in the process. Although

the chance of rework is equal for both listed activities, the “Check for restrictions” activity is

executed before the “Initiate investigation” one, and thus rework in the first activity inevitably

increases rework in the second activity.

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Table 29: Influence of rework the selected activities’ cycle time

Activity Without rework With rework Change

Check for restrictions 0.400 0.444 11.11%

Initiate investigation 0.022 0.027 23.46%

Total 0.422 0.472 11.75%


Defect waste increases the overall cycle time of a process by 16.45%, from 4.06 sec to 4.51 sec.

As it was mentioned regarding transportation waste, rework loops can be eliminated by

transferring the responsibility of correcting mistakes identified while authorization from Payments

Processing Officers to Authorization Officers.

Waiting waste

It is necessary to encounter the number of resources occupied in process execution and an average

number of process inputs during the working day to estimate the daily idle time. The ‘Process

Payments’ process is executed by one PE, five Payments Processing Officers (PPOs), and three

Authorization Officers (AOs). Since there were 13,140 thousand inputs in the process in 2019

during the 355 working days in Belgium, it can be concluded that the average amount of process

inputs per day was equal to 37,014. Table 30 represents the estimation of a daily cycle time for

each activity in the ‘Process Payments’ process in hours considering the number of resources

occupied in process execution.

Table 30: A daily cycle time of the “Process Payments” process activities, hrs

№ Activity Resource CT, sec Total CT, hr Total CT, hr

(per resource)

1 Scan for errors PE (1) 0.0100 0.10 0.10

2 Check for restrictions PPO (5) 0.4444 4.57 0.91

3 Initiate investigation PPO (5) 0.0272 0.28 0.06

4 Assign "Problem-solving" status PPO (5) 0.0019 0.02 0.00

5 Authorize investigation AO (3) 0.0148 0.15 0.05

6 Correct error PPO (5) 2.2000 22.62 4.52

7 Authorize payment AO (3) 1.7600 18.10 6.03

8 Execute payment PE (1) 0.0100 0.10 0.10


Given the information presented in Table 30, it is possible to calculate the idle time per resource

as a share of active cycle time per resource in a total time of resource occupation during the

working day. As seen in Table 31, the Payments Engine stays in idle mode for 97.43% of the time

during the working day; nevertheless, this situation cannot be characterized either as negative or

positive since the idle time of software does not cost anything to the company.

Table 31: A daily working and idle time per process participant

Resource Quantity Working time per day Idle time per day

hr % hr %

Payments Engine 1 0.21 2.57% 7.79 97.43%

Payments Processing Officer 5 5.50 68.72% 2.50 31.28%

Authorization Officer 3 6.08 76.03% 1.92 23.97%


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In contrast, the idle time of the workforce can be considered as a loss. Authorization Officers have

an idle time of 23.20% during the working day. However, the number of them cannot be reduced

because if there will be only two Authorization Officers involved in process execution, the working

time per day per each of them will be equal to 9.22 hrs exceeding the available time of 8 hours.

Reducing the number of PPOs from 5 to 4 is possible, yet it is not recommended because they will

be working 86.61% of the available time. This situation leaves little time reserves for potential

increases in the number of process inputs, not mentioning other undesirable effects of such a

reduction.

4.3.4 Analysis of factors that influence process activities

As shown in Flow Analysis, the cycle time of the individual process activity (𝐶𝑇𝑖) is calculated

as a product of the probability of its occurrence ( 𝑝𝑖) and its average duration ( 𝑇𝑖) as presented in

the following formula:

𝐶𝑇𝑖 = 𝑝𝑖 ∗ 𝑇𝑖

The probability of the process activity occurrence (𝑝𝑖) is calculated as the product of probabilities

of branch occurrence in XOR-gateways (𝑝𝑗):

𝑝𝑖 = ∏ 𝑝𝑗

𝑚

𝑗=1

Therefore, the formula for the activity cycle time calculation can be reformulated in the following

way:

𝐶𝑇𝑖 = ∏ 𝑝𝑗

𝑚

𝑗=1

∗ 𝑇𝑖

The above-mentioned general formula is specified for value-added and business-value-added

process activities executed by the workforce (i.e., by PPOs or AOs) in Table 32.

Table 32: A cycle time of the process activities

№ Activity Resource CT, sec Formula

1 Correct error PPO 2.2000 CT𝑐𝑒 = T𝑐𝑒 ∗ p1 ∗

1

1 − p2∗ p3

2 Authorize payment AO 1.7600 CT𝑎𝑝 = T𝑎𝑝 ∗ p1 ∗

1

1 − p2∗ p3

3 Check for restrictions PPO 0.4444 CT𝑐𝑓𝑟 = T𝑐𝑓𝑟 ∗ p1 ∗

1

1 − p2

4 Initiate investigation PPO 0.0272 CT𝑖𝑖 = T𝑖𝑖 ∗ p1 ∗

1

1 − p4∗ (1 − 𝑝3)

5 Authorize investigation AO 0.0148 CT𝑖𝑖 = T𝑖𝑖 ∗ p1 ∗

1

1 − p4∗ (1 − 𝑝3)


The meaning of the symbols used in Table 32 is explained below:

𝐓𝒄𝒆 = 50 sec is the average duration of the “Correct error” activity;

𝐓𝒂𝒑 = 40 sec is the average duration of the “Authorize payment” activity;

80

𝐓𝒄𝒇𝒓 = 10 sec is the average duration of the “Check for restrictions” activity;

𝐓𝒊𝒊 = 55 sec is the average duration of the “Initiate investigation” activity;

𝐓𝒂𝒊 = 30 sec is the average duration of the “Authorize investigation” activity;

𝒑𝟏 = 0.04 is the probability of payment to be classified by PE as one containing an error;

𝒑𝟐 = 0.1 is the probability of payment to be returned for revision after not passing the

authorization;

𝒑𝟑 = 0.99 is the probability of payment not to contain restrictive conditions.

𝒑𝟒 = 0.1 is the probability of the investigation to be returned for revision after not passing

the authorization.

Sensitivity Analysis

It also seems worthwhile to conduct a sensitivity analysis and estimate how the process cycle time

(CT) will reduce after decreasing these factors by 1%. The results of the sensitivity analysis are

presented in Table 33. The process cycle time is most sensitive to changes in factors such as 𝑝1,

𝑝3, 𝑇𝑐𝑒, and 𝑇𝑎𝑝.

Table 33: A sensitivity analysis

Factors As-is state 1% decrease CT’, sec ΔCT, %

𝑝1 0.04 0.0396 4.40196 -1.000%

𝑝3 0.99 0.9801 4.40682 -0.891%

T𝑐𝑒 , sec 50 49.5 4.42442 - 0.495%

T𝑎𝑝, sec 40 39.6 4.42882 -0.396%

𝑝2 0.1 0.099 4.44148 -0.111%

T𝑐𝑓𝑟 , sec 10 9.9 4.44198 -0.100%

T𝑖𝑖 , sec 55 54.45 4.44615 -0.006%

T𝑎𝑖 , sec 30 29.7 4.44627 -0.003%

𝑝4 0.1 0.099 4.44642 -0.001%

CT of the selected activities 4.44637 X X X


The relationships between the process cycle time (CT) and factors presented in Table 33 together

with the cycle time of the “Assign ‘Problem-solving’ status” activity (CT𝑎𝑝𝑠𝑠), “Scan for errors”

activity (CT𝑠𝑓𝑒), and “Execute payment” activity (CT𝑒𝑝) are presented in the Current Reality Tree

depicted in Appendix M. The further analysis aims to expand the CRT by identifying factors that

influence the probability and the average duration of process activities using the Ishikawa Diagram

and validating relationships between them using statistical methods described previously.

Ishikawa Diagram

Factors presented in Table 33 can be influenced by characteristics of other process elements such

as resources, artifacts, and data objects. The features of PPOs and AOs should be classified under

the Manpower category of the Ishikawa Diagram, while characteristics of PE are to be put into the

Machine category. Process artifacts (i.e., Pega IT-System) and data objects (i.e., Set of supporting

documents) are categorized under the Method category. Finally, the need for authorization is most

suitable for the Measurement category. The Material category is out of the process scope because

process input changes itself during the process execution and does not require any additional

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consumables. Second-level factors categorized under Milieu (i.e., environment) cannot be changed

by implementing the process redesign project and should also be ignored. The Ishikawa Diagram,

which considers the four categories mentioned above, is presented in Figure 46.

Figure 46: The Ishikawa Diagram (process cycle time)


Assumptions presented in Figure 46 are explained in more detail below:

1. Error rate refers to the share of defectives in the total amount of outcomes of the “Correct

error” and “Initiate investigation” activities. The error rate leads to rework.

2. Average duration of the activity execution refers to the average time a particular human

resource (i.e., PPO or AO) spends on one payment and the number of payments he processes

during the day.

3. Process knowledge refers to the tacit knowledge of a process owned by a particular human

resource.

4. Work experience refers to the number of months a particular PPO or AO was involved in

the process execution.

5. Authorization refers to the “Authorize payment” and “Authorize investigation” activities

included in the process execution to reduce the number of defective process outcomes.

6. Four-eye policy refers to the internal business policy that aims to decrease the number of

defective process outcomes by incorporating authorization activities into the process.

7. Supporting documents refer to a set of data objects that contain explicit process

knowledge.

8. Content refers to errors and ways of managing them described in supporting documents.

There are whole algorithms for dealing with only 10% of errors described in the supporting

documents in the as-is state.

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9. Pega IT-System refers to the need for execution part of the activities in the software

different from PE.

10. Settings of Payments Engine refers to a set of functions performed by the PE. In the as-

is state, the PE only scans for errors and do not process payments that contain them.

The influence of work experience on the average duration of the activity execution and error rate

are valid as follows from the regression analysis presented in Appendix N.

In the next step, it is essential to identify relationships between the factor groups. While Machine

and Measurement factor groups can be referred to as independent, relationships can be found

between Method and Manpower factors. In their work, PPOs and AOs use tacit process knowledge

obtained with the work experience and explicit process knowledge coded in a set of supporting

documents. Some of these documents contain straightforward instructions regarding the particular

process cases (i.e., error types), and no experience is needed to successfully execute process

activities following these instructions. Therefore, it can be concluded that the share of explicit

process knowledge in the overall process knowledge is negatively correlated with the impact of

the work experience as presented in Figure 47.

Figure 47: A process knowledge and the influence of the work experience


Finally, it is essential to reformulate neutral factors into problems, as presented in Table 34.

Table 34: Identification of problems

Process element Factor Problem

Payments Engine Settings of Payments Engine Payments Engine only scans for errors

Payments Processing Officer

Work experience Insufficient work experience of PPOs

Process knowledge Insufficient process knowledge of PPOs

Pega IT-System PPOs have to interact with Pega IT-

System

Set of supporting documents Content Supporting documents contain a low

share of process knowledge


83

Authorization officers are not included in Table 34 because they are responsible for the

authorization of payments and investigations, which means that their work experience and process

knowledge are perceived as sufficient for these tasks. In contrast, PPOs do not have work

experience and process knowledge that would be sufficient not to make errors or execute activities

as fast as AOs.

4.3.5 Current Reality Tree

Since the relationships between factors identified during the Ishikawa Diagram construction were

validated (see Appendix N), all these factors coupled with assumptions derived from the Value

Stream Analysis and Waste Analysis can be used to extend the CRT presented in Appendix M.

The extended CRT is shown in Appendix O. Cycle time of “Scan for errors” and “Execute

payment” activities performed by PE were excluded from the CRT since they cannot be further

improved.

As seen in the extended CRT, the “Process Payments” process is affected by the seven root causes

classified under method problems and execution problems categories, as presented in Table 35.

Method problems can be mitigated by redesigning the process, while execution problems can be

weakened by influencing process resources' characteristics (i.e., PE, PPOs, and AOs).

Table 35: Root causes influencing the process cycle time

№ Root cause Category

1 The “Authorize payment” – “Check for restrictions” rework loop Method problem

2 Payments Engine only scans for errors Execution problem

3 Insufficient work experience of PPOs Execution problem

4 Supporting documents contain a low share of process knowledge Execution problem

5 PPOs have to interact with Pega IT-System Method problem

6 The “Authorize investigation” – “Initiate investigation” rework loop Method problem


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5 Recommendations

This chapter is devoted to developing solutions to improve process performance by mitigating the

negative effects of root causes identified in the previous chapter. This objective is achieved by

implementing the Process Redesign methods described in the respective section of the thesis.

Moreover, the proposed solutions should be analyzed to estimate possible effects from their

implementation on the process performance.

As mentioned before, root causes identified in the previous chapter can either arise from the

process structure (i.e., method problems) or characteristics of the process resources (i.e., execution

problems). Since method problems can be mitigated by redesigning the process (i.e., changing the

method), solutions to mitigate these problems can be characterized as those that exploit the

constraints. Therefore, these solutions have to be considered first and implemented before the

solutions aimed at mitigating the execution problems that elevate the constraints.

5.1 Exploit Constraints

The following root causes identified during the Value Stream Analysis and Waste Analysis can be

categorized as those that originated from the process structure:

1. The “Authorize payment” – “Check for restrictions” rework loop;

2. PPOs have to interact with Pega IT-System;

3. The “Authorize investigation” – “Initiate investigation” rework loop.

Solutions for each of these problems are provided below in order of descending influence on the

process cycle time. Then the synergic effect from the simultaneous implementation of these

solutions on the process cycle time is estimated.

Solution 1: Remove the “Authorize payment” – “Check for restrictions” rework loop

The negative effects from the “Authorize payment” – “Check for restrictions” rework loop are

presented in the current reality tree shown in Figure 48.

Figure 48: The Current Reality Tree (Solution 1)


As mentioned in the Waste Analysis, the “Authorize payment” – “Check for restrictions” rework

loop is built in the process structure to make PPOs learn from their mistakes to reduce an error rate

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and decrease the process's cycle time in the future. However, the rework loop leads to

transportation waste and increases particular process activities' duration by increasing their

execution probability. The assumptions mentioned above are presented in the evaporating cloud

(see Figure 49).

Figure 49: The Evaporating Cloud for rework loop (as-is state)


Although the rework loop has to reduce the error rate and decrease the probability of the process

activities’ execution, rework leads to increased probability. Therefore, the conflict is based on the

assumption that seems correct, yet it creates obstacles to achieving the objective. Thus, the rework

loop should be removed from the process flow. However, mistakes have to be fixed, and if PPOs

do not fix them, then the responsibility of mistakes correction goes to AOs. It can be achieved by

incorporating the additional activity, that can be called “Correct mistakes” into the process flow.

Positive effects

Exclusion of the rework loop will lead to the decline in execution probability of the “Check for

restrictions” activity and all activities that are executed afterward. Therefore, the positive effects

of the rework loop removal are as follows:

1. Reduction of the probability of the “Check for restrictions” activity execution by 10%;

2. Reduction of the probability of the “Correct error” activity execution by 10%;

3. Reduction of the probability of the “Authorize payment” activity execution by 10%;

4. Reduction of the probability of the “Initiate investigation” activity execution by 10%;

5. Reduction of the probability of the “Authorize investigation” activity execution by 10%;

Taken together, these changes lead to a 9.96% reduction of the process cycle time from 4.468 sec

to 4.024 sec.

Negative effects

As mentioned above, removing the repetition loop leads to incorporating the “Correct mistakes”

activity into the process flow. Since the work needed to define appropriate actions is done during

86

the “Authorize payment” activity, the duration of the “Correct mistakes” activity can be estimated

as 20% of the time needed to authorize the payment (i.e., 8 sec) applying the Pareto Principle. This

activity's probability will be equal to the probability of the previous activity multiplied by the error

rate of 10% (i.e., 0.00396). Therefore, incorporating the “Correct mistakes” activity will increase

the process cycle time by 0.0317 sec.

To sum up, the process cycle time will be reduced by 0.413 sec (i.e., 9.25%), from 4.468 sec to

4.055 sec, after removing the “Authorize payment” – “Check for restrictions” rework loop from

the process flow and incorporating the “Correct mistakes” activity to compensate this removal.

The effects of implementing the proposed solution are summarized in the Future Reality Tree,

depicted in Figure 50.

Figure 50: The Future Reality Tree (Solution 1)


Solution 2: Automate interactions with Pega IT-System

As seen in the CRT presented in Figure 51, the Pega IT-system leads to the need to execute the

non-value-added “Assign ‘Problem-solving’ status” activity in the process flow and increases the

duration of the “Initiate investigation” activity.



87

As mentioned above, 25% of the as-is process model cases do not require the execution of the

"Assign Problem-solving status" task. The reason behind that is the PE configuration that allows

PPO not to interact with Pega IT-System when dealing with certain types of errors. Therefore, the

PE should be reprogrammed so that PPOs can process all types of errors during the “Initiate

investigation” activity directly in PE. In other words, interactions with Pega should be automated.

This solution is in line with the “Automate activity” heuristic.

Positive effects

The solution would bring two benefits. Firstly, the “Assign ‘Problem-solving’ status” activity

would be removed from the process flow leading to the process cycle time reduction by 0.0019

sec (i.e., 0.04%). Secondly, the average duration of the “Initiate investigation” activity would be

reduced from 55 sec to 10 sec, as presented in Table 36. This change would reduce the cycle time

of the “Initiate investigation” activity and the process cycle time by 0.022 sec (i.e., 0.50%). Thus,

the solution's overall effect is a 0.54% reduction of the process cycle time from 4.468 sec to 4.444

sec.

Table 36: An average duration of the “Initiate investigation” activity

Does the activity require to

interact with Pega?

Probability Average duration of the activity, sec

as-is to-be as-is to-be

yes 0.75 0.00 70 70

no 0.25 1.00 10 10

𝐓𝒊𝒊 55 10


Negative effects

This solution will cause no additional costs since the reprogramming of the PE can be done by

internal resources who receive a monthly salary.

The effects of implementing the proposed solution are seen in the Future Reality Tree, depicted in

Figure 52.



Solution 3: Remove the “Authorize investigation” – “Initiate investigation” rework

loop

The negative effects from the “Authorize investigation” – “Initiate investigation” rework loop are

presented in the current reality tree shown in Figure 53.

88



Based on the argumentation provided regarding the “Authorize payment” – “Check for

restrictions” rework loop, the “Authorize investigation” – “Initiate investigation” rework loop

should also be removed from the process flow. However, to correct mistakes that might be made

by PPOs during the “Initiate investigation” activity, the “Correct investigation case” activity

should be incorporated in the process flow to move the responsibility for correction of mistakes

from PPOs to AOs.

Positive effects

Exclusion of the rework loop will lead to the decline in execution probability of the “Initiate

investigation” and “Authorize investigation” activities by 10% (i.e., error rate). Taken together,

these changes will decrease the process cycle time by 0.005 sec (i.e., 0.10%), from 4.468 sec to

4.463 sec.

Negative effects

Incorporating the “Correct investigation case” activity into the process flow will increase the

process cycle time by this activity's cycle time. Since the work needed to define appropriate actions

is done during the “Authorize investigation” activity, the duration of the “Correct investigation

case” activity can be estimated as 20% of the time needed to authorize investigation (i.e., 6 sec)

applying the Pareto Principle. This activity's probability will be equal to the probability of the

previous activity multiplied by the error rate of 10% (i.e., 0.000044). Therefore, incorporating the

“Correct investigation case” activity will increase the process cycle time by 0.0003 sec.

To sum up, the removal of the “Authorize investigation” – “Initiate investigation” rework loop

will reduce the process cycle time by 0.004 sec (i.e., 0.09%), from 4.468 sec to 4.464 sec. The

effects of implementing the proposed solution are seen in the Future Reality Tree, depicted in

Figure 54.



89

5.2 Elevate Constraints

The following root causes identified during the creation of the Ishikawa Diagram can be

categorized as execution problems:

1. Supporting documents contain a low share of process knowledge;

2. Insufficient work experience of PPOs;

3. Payments Engine only scans for errors;

As seen in the CRT presented in Appendix O, the first two root causes lead to PPOs' insufficient

process knowledge. The work experience allows Officers to obtain tacit process knowledge, while

a set of supporting documents contains explicit process knowledge. Therefore, the above-

mentioned root causes should be examined altogether.

As for the last execution problem, the solution to it is out of the thesis's scope because it will

concern broadening PE’s functions through Artificial Intelligence. Such a solution cannot be

accurately analyzed because it is more IT-oriented than Management-oriented.

Solution 4: Create a knowledge base

The negative effects of the Insufficient process knowledge of PPOs are presented in the current

reality tree shown in Figure 55.



Therefore, to reduce the influence of work experience on task execution duration, it is necessary

to increase the share of explicit process knowledge. Before designing a brand-new solution to

reach this aim, it would be wise to see if there are any solutions already implemented in the

organization. In other words, it is necessary to conduct internal benchmarking.

In other organizational units of the XYZ Group (e.g., T-Hub), there is a practice to create and

maintain a knowledge base within the corporate IT-environment called “Confluence”. Such

knowledge bases contain all the information necessary for efficient process execution. This

practice can be Adapted in the Payments Domain.

90

Positive effects

As shown in Appendix O, the process knowledge influences the average duration of execution and

error rate of the “Check for restrictions”, “Correct error”, and “Initiate investigation” activities

executed by PPOs. Therefore, the creation and maintenance of the knowledge base can lead to a

decrease in these factors.

The average duration of the task execution Since the cycle time of manual activities (i.e., those

executed by workforce) makes up 99.5% of the process cycle time, a 1% decrease in the duration

of the execution of the manual tasks will lead to a 0.995% decrease in the process cycle time. In

the realist scenario, the influence of work experience will be decreased the way that it will allow

PPOs to spend the same time on the execution of the “Correct error” activity as needed for AOs to

execute the “Authorize payment” activity. Therefore, creating the knowledge base will decrease

the process cycle time by at least 0.44 sec (i.e., 9.85%), from 4.468 sec to 4.028 sec.

Error rate Apart from time economy, creating a knowledge base can also decrease an error rate

during the “Correct error” and “Initiate investigation” activities. A 1% decrease in the error rate

will cause a 0.08% decrease in the to-be process cycle time. It is hard to predict the exact extent

to which the error rate will be decreased, but if assumed that the errors due to insufficient process

knowledge will be eliminated, leaving space only for random errors, then the error rate of the

“Correct error” and “Initiate investigation” activities might decrease at least by 5% (from 10% to

5%). It will lead to the process cycle time decrease by 0.213 sec, from 4.028 sec to 3.815 sec.

Overall, the knowledge base's creation will decrease the cycle time of the “Process Payments”

process by at least 0.653 sec (i.e., 14.62%), from 4.468 sec to 3.815 sec.

Negative effects

The solution will not lead to any additional costs because the knowledge base will be created in

the already established “Confluence” environment by AOs in their idle time.

The effects of implementing the proposed solution are seen in the Future Reality Tree, presented

in Figure 56.



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5.3 To-be State of the “Process Payments” Process

This section describes the to-be process model and the effects of the process redesign from the

simultaneous implementation of all the solutions mentioned above.

To-be process model

The as-is process model presented in Appendix L has been redesigned, considering all the changes

needed to implement the solutions mentioned above. The process redesign resulted in the process

to-be model shown in Appendix P. The redesigned process profile is presented in Table 37.

Table 37: A process profile of the “Process Payments” process (to-be state)

Name of Process: Process Payments

Vision: The objective of the “Process Payments” process is to make sure that payments initiated by clients do not

contain any errors, and therefore can be processed as soon as possible.

Process Owner: Payments Processing Team




Outcome: Payment processed OR Investigation Initiated

Trigger: Payment order received

Activity 1 Scan for errors

Activity 2 Check for restrictions

Activity 3 Initiate investigation

Activity 4 Authorize investigation

Activity 5 Correct investigation case

Activity 6 Correct error

Activity 7 Authorize payment

Activity 8 Correct mistakes

Activity 9 Execute payment


Interface outbound: Investigate Claims

Required resources:

- Human resources: Payments Engine, Payments Processing Officer, Authorization Officer

- Information, documents, know-how: Payment order, Knowledge base

- Work environment, materials, infrastructure: None


- Cycle Time

- Operational Costs

- Error Rate


The overall effect of process redesign

The positive and negative effects from simultaneous implementation of all the four proposed

solutions are reflected in the Future Reality Tree shown in Appendix Q. The process redesign will

decrease the “Process Payments” process’ cycle time by 1.064 sec (i.e., 22.71%), from 4.684 sec

to 3.620 sec, as presented in Figure 57.

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Figure 57: A factor analysis of the simultaneous implementation of the proposed solution


The 22.71% reduction in the cycle time of the “Process Payments” process will decrease the

“Manage Transactions” process cycle time by 0.848 sec (i.e., 17.01%), from 4.9865 sec to 4.1385

sec, as presented in Table 38.

Table 38: An average cycle time of the “Manage Transactions” process (to-be state)

Process Quantity of process

instances, thousand

𝒑𝒊 𝑻𝒊, sec 𝒑𝒊 ∗ 𝑻𝒊, sec

Process Payments 13,134.74 0.9996 3.620 3.619

Investigate Claims 5.26 0.0004 1300.000 0.520

Manage Transactions 13,140.00 1.0000 CT = 4.1385

Source: Compiled by the author based on XYZ (2020b)

Moreover, the process redesign will allow reducing the number of PPOs involved in the process

execution from 5 to 3, which will bring a yearly economy of CZK840 thousand. The working time

of resources, in this case, will be distributed the way presented in Table 39.

Table 39: A working time distribution between resources of the process

Resource Quantity Working time per day Idle time per day

hr % hr %

Payments Engine 1 0.21 2.57% 7.79 97.43%

Payments Processing Officer 5 6.81 85.17% 1.19 14.83%

Authorization Officer 3 5.52 69.06% 2.48 30.94%


93

Conclusion

In the 2 Research Methodology chapter, the primary research goal of improving the overall

performance of the XYZ Group’s Payments Domain by redesigning its bottleneck business process

has been broken down into four secondary objectives as follows:

1) To select the bottleneck process;

2) To identify root causes that influence the process performance;

3) To develop solutions to improve process performance;

4) To estimate the effect of the proposed solutions.

These objectives were achieved as described in the 3 Industry and Company Overview, 4 Analysis,

and 5 Recommendations chapters.

In the 3 Industry and Company Overview chapter, it was concluded that the Payments Domain’s

“Manage Transactions” core process that impacts the achievement of Client experience,

Reputation index, and Cost to Income Ratio KPIs of the XYZ Group has to be redesigned in the

first place. In the 4 Analysis chapter, the sub-processes of the “Manage Transactions” process were

analyzed based on strategic impact and health criteria. The “Process Payments” sub-process has

been selected as the bottleneck process because it influenced about 90% of the “Manage

Transactions” process cycle time, which was chosen as the primary process performance measure

connecting all the KPIs stated above.

Six root causes that influence the cycle time of the “Process Payments” process were identified at

the end of the 4 Analysis chapter based on Flow Analysis, Value Stream Analysis, Waste Analysis,

Ishikawa Diagram, and Current Reality Tree tools and techniques. Three root causes, including

rework loops and non-value-adding interactions with the external software, were referred to as

method problems creating constraints that can be exploited. Another three root causes, including

the configuration of the Payments Engine (it was decided not to solve this problem because the

solution of it lies in the field of IT and therefore is out of the thesis’s scope), insufficient work

experience of Payments Processing Officers (PPOs), and incomplete process knowledge in a set

of supporting documents, were referred to as execution problems creating constraints that have to

be elevated.

In the 5 Recommendations chapter, four solutions were developed to reduce the “Process

Payments” process cycle time. Three of them concerned method problems eliminating rework

loops and unnecessary interactions with external software from the process structure. The last

solution was devoted to improving the PPOs' process knowledge by creating a knowledge base.

The simultaneous implementation of all the proposed solutions will reduce the “Process Payments”

process cycle time by 22.7%. It will decrease the cycle time of the “Manage Transactions” process

will decrease by about 17% and save CZK840 thousand per year by reducing the number of PPOs

involved in the process execution.

List of Sources Used

1. Aitken, C., Stephenson, C. & Brinkworth, R. (2015). A Framework for Classifying and

Modeling Organizational Behavior. In J. vom Brocke & M. Rosemann (Eds.), Handbook

on Business Process Management II (pp. 177-201). Springer Berlin Heidelberg.

2. Ali, Z. (2020, October 15). Europe's 50 largest banks by assets, 2020. S&P Global.

https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-

headlines/europe-s-50-largest-banks-by-assets-2020-57901087

3. Allianz. (2020). Annual Report 2019. Allianz.

https://www.allianz.com/content/dam/onemarketing/azcom/Allianz_com/investor-

relations/en/results-reports/annual-report/ar-2019/en-AR-Group-Annual-Report-Allianz-

2019.pdf

4. Antonucci, Y. (2015). Business Process Management Curriculum. In J. vom Brocke & M.

Rosemann (Eds.), Handbook on Business Process Management II (pp. 547-572). Springer

Berlin Heidelberg.

5. Antunes, P., Tate, M. (2019). Eliciting Process Knowledge Through Process Stories.

Information System Frontiers, 22(2), 2-40.

6. APQC. (2019). APQC Process Classification Framework (PCF) - Banking PCF- PDF

Version 7.2.1. APQC. https://www.apqc.org/system/files/resource-file/2020-

04/Banking_v721_040920.pdf

7. APQC. (2019). APQC Process Classification Framework (PCF) - Property and Casualty

Insurance - PDF Version 1.0.0. APQC. https://www.apqc.org/system/files/resource-

file/2020-04/Property%20and%20Casualty%20Insurance_v100_2.pdf

8. Arnheiter, E.D., & Maleyeff, J. (2005). The integration of lean management and Six Sigma.

The TQM Magazine, 17(1), 5-18.

9. AXA SA. (2020). 2019 Annual Report. AXA.

https://www.axa.com/en/press/publications/2019-annual-report

10. Bahsaas, D. M., Hoque, M. R., Albar, A. (2015). Enterprise Resource Planning (ERP)

Systems: Design, Trends and Development. The International Technology Management

Review, 5(2), 72-81.

11. Bandara, W., Indulska, M., Chong. S., & Sadiq, S. (2007). Major Issues in Business

Process Management: An Expert Perspective. In Proceedings ECIS 2017 – The 15th

European Conference of Information Systems (pp. 1240-1251), St Gallen.

12. Beer, S. (1981). Brain of the Firm (2nd ed.). John Wiley & Sons.

13. Bhaskar, H.L. (2018). Business process reengineering framework and methodology: a

critical study. International Journal of Services and Operations Management, 29(4), 527-

556.

14. BNP Paribas SA. (2020). Consolidated Financial Statements. BPN Paribas.

https://invest.bnpparibas.com/en/consolidated-financial-statements

15. Burlton, R. T. (2015). Delivering Business Strategy Through Process Management. In J.

vom Brocke & M. Rosemann (Eds.), Handbook on Business Process Management II (pp.

45-76). Springer Berlin Heidelberg.

16. Camargo, M., Dumas, M., & González-Rojas, O. (2020). Automated discovery of business

processes simulation models from event logs. Decision Support Systems, 134(1), 1-13.

https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/europe-s-50-largest-banks-by-assets-2020-57901087

https://www.spglobal.com/marketintelligence/en/news-insights/latest-news-headlines/europe-s-50-largest-banks-by-assets-2020-57901087

https://www.allianz.com/content/dam/onemarketing/azcom/Allianz_com/investor-relations/en/results-reports/annual-report/ar-2019/en-AR-Group-Annual-Report-Allianz-2019.pdf



https://www.apqc.org/system/files/resource-file/2020-04/Banking_v721_040920.pdf

https://www.apqc.org/system/files/resource-file/2020-04/Banking_v721_040920.pdf

https://www.apqc.org/system/files/resource-file/2020-04/Property%20and%20Casualty%20Insurance_v100_2.pdf

https://www.apqc.org/system/files/resource-file/2020-04/Property%20and%20Casualty%20Insurance_v100_2.pdf

https://www.axa.com/en/press/publications/2019-annual-report

https://invest.bnpparibas.com/en/consolidated-financial-statements

17. Chechurin, L., Borgianni, Y. (2016). Understanding TRIZ through the review of top cited

publications. Computers in Industry, 82(1), 119-134.

18. Covea Insurance plc. (2020). 2019 Annual Report. Covea.

https://www.covea.eu/sites/default/files/2020-

07/Cove%CC%81a_group_RA_EN_2019.pdf

19. Crunchbase. (2020). European Union (EU) Insurance Companies. Crunchbase.

https://www.crunchbase.com/hub/european-union-insurance-companies

20. David, F. R., & David, F. R. (2017). Strategic Management Concepts and Cases: A

Competitive Advantage Approach (16th ed.). Pearson Education.

21. Day, G., Montgomery, D. (1983). Diagnosing the Experience Curve. Journal of Marketing,

47(2), 44-58.

22. Domb, E., Terninko, J., Miller, J., & MacGren, E. (1999). The Seventy-Six Standard

Solutions: How They Relate to the 40 Principles of Inventive Problem Solving. The TRIZ

Journal. https://triz-journal.com/seventy-six-standard-solutions-relate-40-principles-

inventive-problem-solving/

23. Drury, C. (2017). Management and Cost Accounting (10th ed.). Cengage Learning EMEA.

24. Dumas, M., La Rosa, M., Mendling, J., and Reijers, H. A. (2018). Fundamentals of

Business Process Management (2nd ed.). Springer Berlin Heidelberg.

25. European Banking Federation. (2016). Facts and Figures Banking in Europe 2015. EBF.

https://www.ebf.eu/wp-content/uploads/2017/01/FF2015-resized.pdf


https://www.ebf.eu/wp-content/uploads/2018/07/EBF-Facts-Figures-2016.pdf




https://www.ebf.eu/wp-content/uploads/2018/09/Banking-in-Europe-2018-EBF-Facts-

and-Figures.pdf


https://www.ebf.eu/wp-content/uploads/2020/01/EBF-Facts-and-Figures-2019-Banking-

in-Europe.pdf

30. Franceschini, F., Galetto, M., Maisano, D. (2007). Management by Measurement:

Designing Key Measurements and Performance Management System. Springer Berlin

Heidelberg.

31. Frankenfield, J. (2020). Capital Intensive. Investopedia.

https://www.investopedia.com/terms/c/capitalintensive.asp#:~:text=The%20term%20%2

2capital%20intensive%22%20refers,%2C%20and%20equipment%20(PP%26E).

32. Freixas, X., Rochet, J. C. (2008). Microeconomics of Banking. 2nd ed. The MIT Press.

33. Goldratt, E.M. (1990). Theory of constraints. North River Press.

34. Halaška, M., Šperka, R. (2019). Performance of an automated process model discovery –

the logistics process of a manufacturing company. Engineering Management in Production

and Services, 11(2), 106-118.

35. Hao, M., Macdonald, A., Tapadar, P., & Thomas, G. (2018). Insurance loss coverage and

demand elasticities. Insurance: Mathematics and Economics, 79(1), 15-25.

https://www.covea.eu/sites/default/files/2020-07/Cove%CC%81a_group_RA_EN_2019.pdf

https://www.covea.eu/sites/default/files/2020-07/Cove%CC%81a_group_RA_EN_2019.pdf

https://www.crunchbase.com/hub/european-union-insurance-companies

https://triz-journal.com/seventy-six-standard-solutions-relate-40-principles-inventive-problem-solving/

https://triz-journal.com/seventy-six-standard-solutions-relate-40-principles-inventive-problem-solving/

https://www.ebf.eu/wp-content/uploads/2017/01/FF2015-resized.pdf



https://www.ebf.eu/wp-content/uploads/2018/09/Banking-in-Europe-2018-EBF-Facts-and-Figures.pdf

https://www.ebf.eu/wp-content/uploads/2018/09/Banking-in-Europe-2018-EBF-Facts-and-Figures.pdf

https://www.ebf.eu/wp-content/uploads/2020/01/EBF-Facts-and-Figures-2019-Banking-in-Europe.pdf

https://www.ebf.eu/wp-content/uploads/2020/01/EBF-Facts-and-Figures-2019-Banking-in-Europe.pdf

https://www.investopedia.com/terms/c/capitalintensive.asp#:~:text=The%20term%20%22capital%20intensive%22%20refers,%2C%20and%20equipment%20(PP%26E)

https://www.investopedia.com/terms/c/capitalintensive.asp#:~:text=The%20term%20%22capital%20intensive%22%20refers,%2C%20and%20equipment%20(PP%26E)

36. Harmon, P. (2015). The Scope and Evolution of Business Process Management. In J. vom

Brocke & M. Rosemann (Eds.), Handbook on Business Process Management I (pp. 37-

80). Springer Berlin Heidelberg.

37. Henderson, B. (1970, January 1). The Product Portfolio. BCG.

https://www.bcg.com/publications/1970/strategy-the-product-portfolio

38. Hense, F. (2015). Interest rate elasticity of bank loans: The case for sector-specific capital

requirements. CFS Working Paper Series, 504(1), 1-24.

39. Hipple, J. (1999). The Use of TRIZ Separation Principles to Resolve the Contradictions of

Innovation Practices in Organizations. The TRIZ Journal. https://triz-journal.com/use-triz-

separation-principles-resolve-contradictions-innovation-practices-organizations/

40. Houy, C., Fettke, P., & Loos, P. (2015). Business Process Frameworks. In J. vom Brocke

& M. Rosemann (Eds.), Handbook on Business Process Management II (pp. 153-175).

Springer Berlin Heidelberg.

41. Hrastnik, J., Cardoso, J., & Kappe, F. (2007). The Business Process Knowledge

Framework. ICEIS 2007 - Proceedings of the Ninth International Conference on

Enterprise Information Systems, Volume EIS, Funchal, Madeira, Portugal, June 12-16,

2007, 1-8.

42. HSBS Holdings PLC. (2020). Annual Report. HSBS.

https://www.hsbc.com/investors/results-and-announcements/annual-report

43. Hung, R. (2006). Business process management as competitive advantage: a review and

empirical study. Total Quality Management & Business Excellence, 17(1), 21-40.

44. IBM. (2007). The differentiation challenge in changing insurance markets. IBM.

ftp://public.dhe.ibm.com/software/uk/itsolutions/leveraginginformation/clarity/08-

0890_ext_pressure_final_hrcr.pdf

45. Ilevbare, I. M., Probert, D., & Phal, R. (2013). A review of TRIZ, and its benefits and

challenges in practice. Technovation, 33(1), 30-37.

46. Insurance Europe. (2017). European Insurance in Figures: 2015 data. Insurance Europe.

https://www.insuranceeurope.eu/european-insurance-figures-2015-data





49. Insurance Europe. (2020). European Insurance in Figures – 2018 data. Insurance Europe.


50. Ishikawa, K. (1985). What is total quality control – The Japanese Way. Prentice Hall.

51. Kaplan, R.S., Norton, D.P. (1992). The balanced scorecard – measures that drive

performance. Harvard Business Review, 70(1), 71-79.

52. Kirchmer, M. (2017). High Performance Through Business Process Management:

Strategy Execution in a Digital World (3rd ed.). Springer Berlin Heidelberg.

53. Kokkonen, A., Bandara, W. (2015). Expertise in Business Process Management. In J. vom

Brocke & M. Rosemann (Eds.), Handbook on Business Process Management II (pp. 517-


54. Krishnamoorthi, K.S., Krishnamoorthi V.R., Pennathur A. (2018) A First Course in

Quality Engineering: Integrating Statistical and Management Methods to Quality (3rd

ed.). CRC Press.

https://www.bcg.com/publications/1970/strategy-the-product-portfolio

https://triz-journal.com/use-triz-separation-principles-resolve-contradictions-innovation-practices-organizations/

https://triz-journal.com/use-triz-separation-principles-resolve-contradictions-innovation-practices-organizations/

https://www.hsbc.com/investors/results-and-announcements/annual-report

ftp://public.dhe.ibm.com/software/uk/itsolutions/leveraginginformation/clarity/08-0890_ext_pressure_final_hrcr.pdf

ftp://public.dhe.ibm.com/software/uk/itsolutions/leveraginginformation/clarity/08-0890_ext_pressure_final_hrcr.pdf





55. Lamarque, E. (2000). Key Activities in The Banking Industry: An Analysis By the Value

Chain. SSRN. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=208668

56. Leyer, M., Heckl, D., Moormann, J. (2015). Process Performance Measurement. In J. vom



57. Lohmann, P., Muehlen, M. Z. (2015). Business Process Management Skills and Roles: An

Investigation of the Demand and Supply Side of BPM Professionals. International

Conference in Business Process Management, 13(1), 317-332.

58. Lynne, M., Jacobson, D. (2015). The Governance of Business Processes. In J. vom Brocke

& M. Rosemann (Eds.), Handbook on Business Process Management II (pp. 311-331).

Springer Berlin Heidelberg.

59. MacRae, T. L. (2020). Strategic Management Tools and Applications. Masaryk University

Press.

60. Malek, R., Yazdanifard, R. (2012). Overview of Change Management and Its

Implementation. Business, Economics, Financial Sciences, and Management, 1(1), 149-

153.

61. MAPFRE. (2019). 2019 Ranking of the Largest European Insurance Groups. MAPFRE.

https://www.fundacionmapfre.org/documentacion/publico/es/catalogo_imagenes/grupo.d

o?path=1107225

62. Martínez-Lorente, A. R., Dewhurst, F., & Dale, B. G. (1998). Total quality management:

origins and evolution of the term. The TQM Magazine, 10(5), 378-386.

63. McCambridge, J., Witton, J., & Elbourne, D.R. (2014). Systematic review of the

Hawthorne effect: New concepts are needed to study research participation effects. Journal

of Clinical Epidemiology, 63(3), 267-277.

64. Montgomery, D. C. (2018). Design and Analysis of Experiments (10th ed.). John Wiley &

Sons.

65. Morrison, E. D., Ghose, A. K., Hoa, K. D., Hinge, K. G., & Hoesh-Klohe, K. (2012).

Strategic Alignment of Business Processes. In Service-Oriented Computing – ICSOC 2011

Workshops (pp. 9-22). Springer Berlin Heidelberg.

66. Munich RE. (2020). Annual Report 2019. Munich RE.

https://www.munichre.com/content/dam/munichre/mrwebsiteslaunches/2019-annual-

report/MunichRe-Group-Annual-Report-2019-

en.pdf/_jcr_content/renditions/original./MunichRe-Group-Annual-Report-2019-en.pdf

67. Ohno, T. (1978). The Toyota production system: beyond large-scale production. English

Translation 1988, Productivity Press.

68. Ouyang, C., Adams, M., Wynn, M.T., & Hofstede, A.H.M. (2015). Workflow

Management. In J. vom Brocke & M. Rosemann (Eds.), Handbook on Business Process

Management I (pp. 475-505). Springer Berlin Heidelberg.

69. Peng, R., Matsui, E. (2015). The Art of Data Science: A Guide for Anyone Who Works with

Data. Leanpub.

70. Porter, M.E. (1985). Competitive Advantage – Creating a Sustaining Superior

Performance, The Free Press.

71. Puchovsky, M., Di Ciccio, C., & Mendling, J. (2016). A Case Study on the Business

Benefits of Automated Process Discovery. SIMPDA, 1757(1), 35-49.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=208668

https://www.fundacionmapfre.org/documentacion/publico/es/catalogo_imagenes/grupo.do?path=1107225

https://www.fundacionmapfre.org/documentacion/publico/es/catalogo_imagenes/grupo.do?path=1107225

https://www.munichre.com/content/dam/munichre/mrwebsiteslaunches/2019-annual-report/MunichRe-Group-Annual-Report-2019-en.pdf/_jcr_content/renditions/original./MunichRe-Group-Annual-Report-2019-en.pdf



72. Reijers, H. A., van Wijk, S., Mutschler, B., & Leurs, M. (2010). BPM in Practice: Who Is

Doing What? International Conference in Business Process Management, 8(1), 45-60.

73. Rosemann, M., vom Brocke, J. (2015). The Six Core Elements of Business Process

Management. In J. vom Brocke & M. Rosemann (Eds.), Handbook on Business Process

Management I (pp. 105-126). Springer Berlin Heidelberg.

74. Ross, S. (2019, June 25). What Is the Main Business Model for Insurance Companies?

Investopedia. https://www.investopedia.com/ask/answers/052015/what-main-business-

model-insurance-companies.asp

75. Saunders, M., Lewis, P., & Thornhill, A. (2019). Research methods for business students

(3rd ed.) Pearson Education Limited.

76. Scheer, A., Hoffmann, M. (2015). The Process of Business Process Management. In J. vom



77. Scheinkopf, L. (1999). Thinking for a change: putting the TOC thinking processes to use.

CRC Press.

78. Schmiedel, T., vom Brocke, J., Recker, J. (2015). Culture in Business Process

Management: How Cultural Values Determine BPM Success. In J. vom Brocke & M.

Rosemann (Eds.), Handbook on Business Process Management II (pp. 649-663). Springer

Berlin Heidelberg.

79. Schroeder, R.G., Linderman, K., Liedtke, C., & Choo, A.S. (2008). Six Sigma: Definition

and underlying theory. Journal of Operations Management, 26(4), 536-554.

80. Seethamraju, R., Marjanovic, O. (2009). Role of process knowledge in business process

improvement methodology: a case study. Business Process Management Journal, 15(6),

920-936.

81. Sidorova, A., Torres, R., & Beayeyz, A. A. (2015). The Role of Information Technology

in Business Process Management. In J. vom Brocke & M. Rosemann (Eds.), Handbook on

Business Process Management I (pp. 421-443). Springer Berlin Heidelberg.

82. Silver, B. (2011). BPMN Method and Style with BPMN Implementer’s Guide. (2nd ed.).

Cody-Cassidy Press.

83. Skrinjar, R., Bosilj-Vuksic, V., and Indihar-Stemberger, M. (2008). The impact of business

process orientation on financial and non-financial performance. Business Process

Management Journal, 14(5), 738-754.

84. Skrinjar, R., Trkman, P. (2013). Increasing process orientation with business process

management: Critical practices. International Journal of Information Management, 33(1),

48-60.

85. Szelagowski, M. (2019). Dynamic Business Process Management in the Knowledge

Economy. Cham, Springer Nature Switzerland.

86. Tuovila, A. (2020, March 19). Net Interest Income. Investopedia.

https://www.investopedia.com/terms/n/net-interest-income.asp

87. Türkcan, Z. (2018). Financial Failure Prediction in Banks: The Case of European Union

Countries. Journal of Business Research, 10(2), 554-559.

88. Van der Aalst, W. (2011). Process Mining: Discovery, Conformance and Enhancement of

Business Processes. Springer Berlin Heidelberg.

https://www.investopedia.com/ask/answers/052015/what-main-business-model-insurance-companies.asp

https://www.investopedia.com/ask/answers/052015/what-main-business-model-insurance-companies.asp

https://www.investopedia.com/terms/n/net-interest-income.asp

89. Vugec, D. S., Ivančić, L., & Glavan, L. M. (2019). Business Process Management and

Corporate Performance Management: Does Their Alignment Impact Organizational

Performance. Interdisciplinary Description of Complex Systems, 17(2), 368-384.

90. Weske, M. (2019). Business Process Management: Concepts, Languages, Architectures

(3rd ed.). Springer Berlin Heidelberg.

91. XYZ. (2017). XYZ Group Annual Report 2016. XYZ. https://www.xyz.com/en/investor-

relations/reports/annual-reports.html







95. XYZ. (2020). XYZ Internal Wiki. XYZ. xyz.sharepoint.com

96. Youngman, K.J. (2009). A Guide to Implementing the Theory of Constraints (TOC).

http://www.dbrmfg.co.nz/

97. Zahrotun, N., & Taufiq, I. (2018). Lean Manufacturing: Waste Reduction Using Value

Stream Mapping. E3S Web Conf., 73(1), 1-6.

98. Zwetsloot, I. (n.d.). Data Analytics for Lean Six Sigma [MOOC]. Coursera.

https://www.coursera.org/learn/data-analytics-for-lean-six-sigma

https://www.xyz.com/en/investor-relations/reports/annual-reports.html








http://www.dbrmfg.co.nz/

https://www.coursera.org/learn/data-analytics-for-lean-six-sigma

100

List of Appendices

Appendix A: A Historical Development of BPM Methodology

Appendix B: An Example of Process Profile

Appendix C: Process Redesign Heuristics

Appendix D: Prerequisite Tree for Achieving the Primary Goal of the Research

Appendix E: Characteristics of the Industry Lifecycle Stages

Appendix F: Lifecycle Analysis of the Banking Industry

Appendix G: 2019 Ranking of the Largest European Insurance Groups by Premium Volume

Appendix H: Lifecycle Analysis of the Insurance Industry

Appendix I: Strategy Map of the XYZ Group

Appendix J: Organizational Chart of the XYZ Group

Appendix K: Interview with Payments Processing Team Leader

Appendix L: “Process Payments” Process As-Is Model

Appendix M: Current Reality Tree

Appendix N: Validation of the Relationships Between Identified Factors

Appendix O: Current Reality Tree (Extended)

Appendix P: “Process Payments” Process To-Be Model

Appendix Q: Future Reality Tree

Appendix A

A Historical Development of BPM Methodology

Source: Compiled by the author based on Harmon (2015), p. 42-50

Appendix B

An Example of Process Profile


Appendix C

Process Redesign Heuristics

Group Heuristic Applicable to

Time Cost Quality Flexibility

Customer

Heuristics

1. Control relocation: moving controls towards the customer; +

2. Contact reduction: reduce the number of contacts with customers and third parties; + +

3. Integration: consider the integration with a business process of the customer or a supplier. + +

Business

Process

Operation

Heuristics

4. Case types: determine whether activities are related to the same type of case and, if necessary,

distinguish new business processes;

+ +

5. Activity elimination: eliminate unnecessary activities from a business process; + +

6. Case-based work: remove batch-processing and periodic activities; +

7. Triage: split an activity into alternative versions; +

8. Activity composition: combine small activities into composite activities. +

Business

Process

Behavior

Heuristics

9. Resequencing: move activities to their appropriate place; + +

10. Parallelism: put activities in parallel; +

11. Knock-out: order knock-outs in increasing order of effort and in decreasing order of

termination probability;

+

12. Exception: design business processes for typical cases and isolate exceptional cases from the

normal flow.

+ +

Organizational

Heuristics

13. Case assignment: let participants perform as many steps as possible; + +

14. Flexible assignment: keep generic participants free for as long as possible; + + +

15. Centralization: let geographically dispersed participants act as if they are centralized; + +

16. Split responsibilities: avoid shared responsibilities for tasks by people from different

functional units;

+ +

17. Customer teams: consider composing work teams of people from a different department that

will take care of the complete handling of specific sorts of cases;

+ +

18. Numerical involvement: minimize the number of departments, groups, and persons involved

in a business process;

+ +

19. Case manager: appoint one person to be responsible for the handling of each type of case; +

20. Extra resources: if capacity is not sufficient, increase the available number of resources; + +

21. Specialize: consider deepening the skills of participants; + +

Group Heuristic Applicable to

Time Cost Quality Flexibility

22. Empower: give workers decision-making authority instead of relying on middle management. + + +

Information

Heuristics

23. Control addition: check the completeness and correctness of incoming materials and check

the output before it is sent to customers;

+

24. Buffering: instead of requesting information from an external source, buffer it, and subscribe

to updates.

+

Technology

Heuristics

25. Activity automation: consider automating activities; + +

26. Integral technology: elevate physical constraints in a business process by applying new

technology.

+ +

External

Environment

Heuristics

27. Trusted party: use the insights of a trusted party (i.e., benchmarking); + +

28. Outsourcing: consider outsourcing a business process completely or parts of it; +

29. Interfacing: consider a standardized interface with customers and partners. + +

TOTAL 23 8 14 5


Appendix D

Prerequisite Tree for Achieving the Primary Goal of the Research


Appendix E

Characteristics of the Industry Lifecycle Stages

Source: MacRae (2020), p. 40

Appendix F

Lifecycle Analysis of the Banking Industry

Lifecycle Analysis of the Banking Industry based on Appendix E is provided below.

Fixed to variable cost ratio

Fixed to variable costs ratio, also referred to as operating leverage, is calculated to indicate whether

the industry is capital intensive (Frankenfield, 2020). In the case of the banking industry, this ratio

is calculated by the following formula considering the specific way of financial results

representation in the companies’ financial statements:

Operating leverage = Total operating expenses ∗

Net interest income + Net fee incomeTotal income

Interest expense + Fee expense

Fixed costs are represented by total operating expenses multiplied by the share of income from

banking activities (i.e., net interest income and net fee income) in total income. Variable costs are

determined as a sum of interest expense and fee expense. Table 40 represents the dynamics of

operating leverage in companies representing the banking industry's specialized business segment.

Table 40: An operating leverage dynamics in the banking industry (specialized businesses)

Financial indicator HSBC Holdings

PLC

BNP Paribas SA Banka Monte dei

Paschi di Siena

SpA

Bank of Ireland

Group PLC

2018 2019 2018 2019 2018 2019 2018 2019

Fixed costs/variable

costs

1.04 0.92 1.18 1.08 3.11 2.43 2.00 1.54

Fixed costs, € billion 23,497 25,332 21,773 21,679 2,653 2,152 1,249 888

Total operating

expenses, € billion

34,659 42,349 30,583 31,337 2,647 2,383 1,941 2,006

Share of income from

banking activities in

total income

67.80% 59.82% 71.19% 69.18% 100.24

%

90.33% 64.34% 44.27%

Total income, € billion 63,587 71,024 42,516 44,597 3,037 2,913 3,747 5,557

Net interest income, €

billion

30,489 30,462 21,062 21,127 1,522 1,243 2,134 2,155

Net fee income, €

billion

12,620 12,023 9,207 9,725 1,522 1,389 277 305

Variable cost, € billion 22,544 27,649 18,379 20,100 853 887 623 575

Interest expense, €

billion

19,120 24,233 14,661 16,200 665 698 379 370

Fee expense, € billion 3,424 3,416 3,718 3,900 188 189 244 205



As seen in Table 40, in most cases, operating leverage exceeds 1.0, which means that fixed costs

exceed variable cost and therefore banking industry is considered capital-intensive, highly

dependent on the demand to reach the break-point, and is on the maturity stage of the lifecycle.

Barriers to entry

To enter the capital-intensive banking industry, companies should have a significant amount of

initial investments. Although these barriers are higher in the specialized business segment where

companies have to own at least €100 billion of assets to be considered competing in this field, they

are also high in the fragmented business segment. Thus, it can be concluded that in the industry as

a whole, there are increasing barriers to entry as capital intensity increases. Therefore, the industry

is in the maturity stage of the lifecycle.

Concentration of competitors

As was mentioned regarding Competitive Advantage Matrix, 71% percent of the market is

controlled by the 50 largest banks, while over 6,000 financial institutions hold the rest 29% of it.

Therefore, competitors' concentration in the specialized business segment is high (on average,

1.42% market share per competitor). In the fragmented business segment, competitors’

concentration strives to zero (on average, 0.0035% market share per competitor). For the industry

as a whole, the concentration of competitors increases with the increase of capital intensity.

Therefore, the industry can be placed in the maturity stage of the lifecycle.

Barriers to exit

Barriers to exit, among other things, are determined by the liquidity of industry-specific assets. In

the banking industry, these assets are mainly presented by real estate and low liquidity equipment

used in branches. It would be fair to conclude that companies operating in the more capital-

intensive specialized business segment have a higher number of branches. Therefore, barriers to

exit for them are higher than for companies operating in the less capital-intensive fragmented

business segment. Thus, in the banking industry as a whole, barriers to exit are considered

increasing as the value of companies’ assets increases meaning that the industry is in the maturity

stage of the lifecycle.

Product differentiation

As follows from the annual reports of many banks (e.g., HSBC, 2020; BNP Paribas, 2020; XYZ,

2020), most of the banking industry’s competitors persuade customer-oriented strategies, which

by definition lead to a high degree of product differentiation. Another evidence for the high degree

of differentiation is that fragmented businesses mainly concentrate on those segments that are

ignored by the specialized businesses (e.g., consumer credits), signalizing the increasing

segmentation of the market. Therefore, it can be concluded that the banking industry is in the

maturity stage of the lifecycle.

Vertical integration of competitors

As follows from the bank’s business model, competitors, by definition, own a procurement part of

the value chain. Moreover, all banks control their distribution by creating branches or through the

internet. The facts mentioned above are sufficient to conclude that the degree of vertical integration

in the banking industry is high, which is typical for industries on the lifecycle's maturity stage.

Price elasticity of demand

In the banking industry's debt instruments segment, price is expressed in interest terms, meaning

that the loan interest rate presents a loan price. Hense (2015) has empirically proved that “in the

long run, the interest rate increases lead to a fall in demand for credit”. In other words, demand in

the debt instruments sector can be characterized as highly-elastic. The transactional operations

sector is characterized by the low price elasticity of demand mainly because customers’ expenses

on changing the provider exceed the possible benefits they can gain from the transition. Thus, the

price elasticity of demand in the banking industry as a whole is inelastic only in selected segments

(i.e., transactional operations), which leads us to the conclusion about the industry’s maturity.

Experience-curve effects

Experience-curve constitutes that the direct costs per unit decrease as cumulative production

increases (Day & Montgomery, 1983). In application to the banking industry, this rule can be

reformulated in the following way: “direct costs per loan decrease as the number of loans

increases”. According to Drury (2017), direct costs include fixed as well as variable costs. Thus,

experience-curve effects can be mathematically expressed through Cost to Income Ratio (CIR)

calculated by the following formula:

CIR = Direct costs

Gross income

Direct costs of banks are composed of the share of total operating expenses directly associated

with selling debt instruments business process (i.e., direct fixed costs) and income expense (i.e.,

direct variable costs). In contrast, gross income is represented by interest income. The dynamics

of CIR in four companies representing the specialized business segment of the banking industry

are presented in Table 41.

Table 41: A CIR dynamics in the banking industry (specialized businesses)

Financial indicator HSBC Holdings

PLC

BNP Paribas SA Banka Monte dei

Paschi di Siena

SpA

Bank of Ireland

Group PLC

2018 2019 2018 2019 2018 2019 2018 2019

CIR 72.04% 77.51% 53.70% 53.38% 91.07% 88.35% 59.07% 45.46%

Interest income 49,609 54,695 35,723 37,327 2,187 1,940 2,513 2,525

Direct costs 35,738 42,396 19,183 19,927 1,991 1,714 1,484 1,148

Direct fixed costs 16,618 18,163 4,522 3,727 1,327 1,016 1,105 778

Total operating

expenses

34,659 42,349 9,129 7,867 2,647 2,383 1,941 2,006

Total income 63,587 71,024 42,516 44,597 3,037 2,913 3,747 5,557

Net interest income 30,489 30,462 21,062 21,127 1,522 1,243 2,134 2,155

Net interest income (%

of total income)

47.95% 42.89% 49.54% 47.37% 50.12% 42.65% 56.95% 38.78%

Direct variable costs 19,120 24,233 14,661 16,200 665 698 379 370

Interest expense 19,120 24,233 14,661 16,200 665 698 379 370



As seen in Table 51, in most cases, CIF exceeds 50%, signalizing the decreasing magnitude of the

experience-curve effects. Therefore, the banking industry is in the maturity stage of the lifecycle.

Risks involved in business

According to Freixas & Rochet (2008), the four main risks affecting banks are credit risk, interest

rate risk, liquidity risk, and off-balance-sheet operations risk. These risks taken together might

lead to bankruptcy (Türkcan, 2018) and therefore should be referred to as high, leading to the

conclusion that the banking industry as a whole is on the maturity stage of the lifecycle.

Appendix G

2019 Ranking of the Largest European Insurance Groups by Premium

Volume

Source: MAPFRE (2020), p. 13

Appendix H

Lifecycle Analysis of the Insurance Industry

Lifecycle Analysis of the Insurance Industry based on Appendix E is provided below.

Fixed to variable cost ratio

The calculation of the operating leverage for the insurance industry doesn’t apply activity-based

costing like in the banking industry but concerns the insurance companies' overall performance.

Thus, the operating leverage is calculated based on the following formula:

Operating leverage = Total operating expenses

Insurance charges

Table 42 shows the operating leverage dynamics for the two largest and the two smallest

companies included in Appendix G. In all the observed cases operating leverage is less than 1.0,

signalizing that variable costs exceed fixed costs. However, the decrease in the ratio is correlated

with a reduction of capital intensity. Therefore, the insurance industry can be referred to as a

growing one.

Table 42: An operating leverage dynamics in the insurance industry (specialized businesses)

Financial indicator AXA Allianz Ergo Covéa

2018 2019 2018 2019 2018 2019 2018 2019

Fixed costs/variable

costs

0.39 0.25 0.47 0.47 0.36 0.33 0.06 0.39

Fixed costs, € billion 29.55 25.79 24.60 26.25 5.42 5.81 0.38 3.65

Variable costs, € billion 75.07 101.48 52.16 55.85 15.12 17.39 6.21 9.32

Source: Calculated by the author based on AXA (2020), Allianz (2020), Ergo (2020), and Munich Re (2020)

Barriers to entry

The amount of capital companies should invest to enter the insurance industry increase alongside

capital intensity, which is higher in the specialized business segment than in the fragmented

business segment. As it follows from the insurance company’s business model, companies'

primary income source is insurance premiums. The total value of premiums increases alongside

the number of clients, which grows in reaction to the rise of brand awareness. However, significant

money should be invested to reach a sufficient level of brand awareness. Therefore, in the industry

as a whole, there are increasing barriers to entry as capital intensity increases, indicating the

industry's maturity.

Concentration of competitors

As was mentioned in the Competitive Advantage Matrix, almost 43.5% of the insurance market’s

revenue is generated by the 15 largest companies operating in the specialized segment, while the

1,152 companies gain the rest 56.5%. Therefore, competitors' concentration in the specialized

business segment is high (on average, 2.9% market share per competitor). In the fragmented

business segment, the average market share is less than 0.05% per competitor. Thus, for the

insurance industry as a whole, the concentration of competitors increases with capital intensity.

Therefore, the industry can be placed in the maturity stage of the lifecycle.

Barriers to exit

Similar to the banking industry, barriers to exit are determined by the liquidity of industry-specific

assets. In the insurance industry, these assets are mainly presented by real estate and low liquidity

equipment used in insurance agencies. It would be fair to conclude that companies operating in the

more capital-intensive specialized business segment have a higher number of agencies. Therefore,

barriers to exit for them are higher than those operating in the less capital-intensive fragmented

business segment. Thus, for the insurance industry as a whole, barriers to exit increase in parallel

with companies’ assets meaning that the industry is in the maturity stage of the lifecycle.

Product differentiation

According to IBM (2007), companies should differentiate themselves whether by price, product,

focus or spread, delivery, availability, flexibility, service, or quality to stand out in the crowded

insurance market. Therefore, it can be concluded that product differentiation in the insurance

market is high, which means that the industry as a whole is on the maturity stage of the lifecycle.

Vertical integration of competitors

Similar to the banking industry, competitors raise funds themselves and therefore own a

procurement part of the value chain. Moreover, all insurance companies control their distribution

by opening insurance agencies or through the internet. Thus, it can be concluded that the degree

of vertical integration in the insurance industry is high. Therefore, the industry is in the maturity

stage of the lifecycle.

Price elasticity of demand

In the insurance industry, price is expressed in interest terms meaning that the insurance premium

value is equal to a certain percent of the insurance payment in case of the occurrence of the

insurance event. According to Hao et al. (2018), the price elasticity of demand for insurance

services exceeds 1.0. It can be referred to as high, signalizing that the insurance industry is in the

maturity stage of the lifecycle.

Experience-curve effects

In application to the insurance industry, the experience-curve rule (Day & Montgomery, 1983) can

be reformulated in the following way: “direct costs per insurance contract decrease as the number

of contracts increases”. As in the banking industry, experience-curve effects can be mathematically

expressed through CIR as a ratio of direct costs to the gross income. The dynamics of CIR in four

companies representing the insurance industry's specialized business segment are presented in

Table 43. In all the cases, CIF exceeds 50% signalizing the decreasing magnitude of the

experience-curve effects. Thus, the insurance industry can be referred to as mature.

Table 43: A CIR dynamics in the insurance industry (specialized businesses)

Financial indicator AXA Allianz Ergo Covéa

2018 2019 2018 2019 2018 2019 2018 2019

CIR 98.30% 95.61% 71.44% 70.49% 97.89% 96.48% 93.93% 95.24%

Insurance premiums 106.43 133.11 107.44 116.47 20.98 24.04 7.02 13.63

Direct costs 104.62 127.27 76.76 82.10 20.54 23.20 6.59 12.98

Direct fixed costs 29.55 25.79 24.60 26.25 5.42 5.81 0.38 3.65

Direct variable costs 75.07 101.48 52.16 55.85 15.12 17.39 6.21 9.32

Source: Calculated by the author based on AXA (2020), Allianz (2020), Ergo (2020), and Munich Re (2020)

Risks involved in business

AXA (2020) distinguishes two main groups of risks faced by insurance companies: financial risks

and company-specific risks. Financial risks contain market, credit, and liquidity risks, while

company-specific risks comprise insurance pricing, operational, and regulatory risks. These risks

taken together might significantly influence the insurance market competitors' financial

performance and thus should be referred to as high signalizing of the insurance industry’s maturity.

Appendix I

Strategy Map of the XYZ Group


Appendix J

Organizational Chart of the XYZ Group

Source: Adapted by the author from XYZ (2020b)

Appendix K

Interview with Payments Processing Team Leader

A record of the interview with the Payments Processing Team Leader is provided below. Questions

asked by the author of the thesis who performed the Interviewee's role are written under the letter

I. Name of the Payments Processing Team Leader is substracted to TL for privacy reasons.

I: Hello, TL! Thank you for having the time to talk. I have some additional questions regarding

the process description that you provided earlier.

TL: No worries, Mikhail! I would be happy to help!

I: Great, thank you! The first question is how the client initiates the payment?

TL: The payment can be initiated through various input channels connected with our PE. It can

be initiated through one of our applications, such as mobile banking or XYZ Touch, or even

inserted directly in the branch.

I: Thank you for your answer. I see that the payment can be initiated through various channels,

yet can we say that the PE starts to work while some information object has been entered to it

independent from the channel?

TL: Hm… Yes, I think so.

I: Ok. Can we name this document a payment order, for example, and say that it reaches the system

through one of the available channels?

TL: Oh, now I see what you meant! Yes, definitely, we can say so.

I: Is there maybe a better name for this payment order?

TL: I don’t think so. You formulated it very precisely, Mikhail.

I: Thank you, TL! I have one more question for you if you don’t mind.

TL: Yes, sure!

I: As I noticed after the observation under Payments Processing Officer, if the payment order

contains restrictive conditions such as an embargo warning, he created the case in Pega and sent

this payment order to Claims & Investigations Team. Is this the only point of contact between your

team and Claims & Investigations during the “Process Payments” process?

TL: Oh, yes! I think I forgot to mention it in the process description, yet you noticed it correctly.

From time to time, Claims & Investigations Officers contact us to clarify some details, but I think

it is out of the scope of our process.

I: Got it. It was the last question from me. Thank you, TL!

TL: Not at all, Mikhail! Have a nice day!

I: You too!

Appendix L

“Process Payments” Process As-Is Model

Appendix M

Current Reality Tree

Appendix N

Validation of the Relationships Between Identified Factors

Although the influence of factors presented in the Ishikawa Diagram can be proved logically, the

following three of them can be measured and therefore verified using quantitative tools shown in

Figure 18:

- Error rate;

- Average duration of the activity execution;

- Work experience.

It is assumed that the work experience is correlated with the error rate and the average duration

of the activity execution. Since all of these factors are numerical, their correlation can be validated

by the regression method.

Correlation between work experience and average duration of the activity execution

The personal productivity (i.e., the average duration of the activity) was calculated as a weighted

average according to the following formula:

T =∑ 𝑡𝑖∗𝑛

𝑖=1 𝑞𝑖

∑ 𝑞𝑖 , where:

n is the number of human resources involved in the activity;

𝒕𝒊 is the average time spent by a particular human resource for the execution of one process

activity;

𝒒𝒊 is the average amount of activities conducted by a particular human resource.

It was decided to prove the correlation between work experience and average duration of the

activity execution based on the “Correct error” activity, which has the highest impact on the

process cycle time and is executed by a higher amount of human resources than authorization

activities. The calculation of the average duration of the “Correct error” activity is presented in

Table 44.

Table 44: Calculation of the average duration of the “Correct error” activity execution

PPO Work experience, months

(X variable) 𝒒𝒊 𝒕𝒊, sec (Y variable)

1 5 292 59

2 7 310 60

3 14 319 50

4 20 356 43

5 23 352 41

T 50


Figure 58 represents the correlation between work experience and personal productivity. R-

squared of 0.9318 and p-value of 0.00014 less than 0.05 indicate the statistical significance of the

test. Therefore it can be claimed that the correlation between those two variables is strong, linear,

and negative. In other words, the higher the work experience, the lower the average duration of

the activity execution.

Figure 58: Correlation between work experience and personal productivity


Correlation between work experience and error rate

The average error rate (p) was calculated as a weighted average according to the following

formula:

p =∑

𝑑𝑒𝑓𝑖𝑞𝑖

∗𝑛𝑖=1 𝑞𝑖

∑ 𝑞𝑖 , where:

n is the number of human resources involved in the activity;

𝒅𝒆𝒇𝒊 is the number of defective activity outputs;

𝒒𝒊 is the average amount of operations conducted by a particular human resource during

the working day.

It was decided to prove the correlation between work experience and error rate based on the

“Correct error” activity due to the same reasons provide regarding the previous correlation. The

calculation of the “Correct error” activity's average error rate is presented in Table 45.

Table 45: Calculation of the average error rate of the “Correct error” activity

PPO Work experience,

months (X variable) 𝒒𝒊 𝒅𝒆𝒇𝒊 𝒑𝒊 (Y variable)

1 5 265 48 0.1811

2 7 282 40 0.1418

3 14 290 23 0.0793

4 20 324 18 0.0556

5 23 320 19 0.0594

p 0.0999


Figure 59 represents the correlation between work experience and personal productivity. R-

squared of 0.8969 and p-value of 0.00236 less than 0.05 indicate the statistical significance of the

test. Therefore it can be claimed that the correlation between those two variables is strong, linear,

and negative. In other words, the higher the work experience, the lower the error rate.

y = -1.0867x + 65.797R² = 0.9318

0

10

20

30

40

50

60

70

0 5 10 15 20 25

Pe

rso

na

l pro

du

ctiv

ity, se

c

Work experience, months

Figure 59: Correlation between work experience and error rate


y = -0.0067x + 0.1958R² = 0.8969

0.000

0.050

0.100

0.150

0.200

0 5 10 15 20 25

Err

or

rate

Work experience, months

Appendix O

Current Reality Tree (Extended)

Appendix P

“Process Payments” Process To-Be Model

Appendix Q

Future Reality Tree

The Analysis of Company Business Processes - IS MUNI

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