PEMBI - BI Maturity Model - Pemwork

PEMBI: Pemwork Business Intelligence Maturity Model

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Contents

1. General Overview ................................. 3

2. Introduction ........................................ 5

3. PEMBI – Pemwork BI Maturity Model ............ 9

4. Vision .............................................. 12

5. Throughput ....................................... 14

6. Execution ......................................... 16

7. Capabilities ....................................... 21

8. Conclusion ........................................ 25

9. Preliminary Assessment ........................ 31

10. Bibliography ...................................... 32

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1. Rationale

Over the last decade there has been a global major effort to establish criteria to help us determine whether a business can significantly improve their performance. To this end, businesses have sought to improve their executive management by analyzing information generated by their own businesses, competitors, suppliers, channel, customers, government and any organizations that might be related to their model business. The later combined with the technological maelstrom in which organizations are embedded, has led to the development of tools that facilitate the analysis of variables that could provide pointers to continuous improvement and innovation of processes and services, mainly as semi-automated systems which assist decision-making in enterprises. In this sense, a great deal of companies and organizations have developed models to assess the maturity level of a business in relation to its "business intelligence" (BI). Independent software vendors (ISVs) which procure BI tools have supported BI maturity models to promote their sales. As a consequence, sometimes the "business intelligence" is related to a software tool causing the false assumption that if a company acquires such a tool, their "business intelligence" improves. It is simple to prove such an argument wrong. The BI tool per-se does not evolve the level of business intelligence. Pemwork has built a business intelligence maturity model for organizations, named PEMBI not directly supported by BI tool vendors to facilitate the assessment of an organization and therefore, facilitate defining the subsequent steps to improve. This document presents an introduction to PEMBI.



PEMBI

Business Intelligence (BI) Maturity Model



2. Introduction

A great deal of companies and organizations have designed models to assess the maturity of a business in relation to its "business intelligence" (BI). Some of them even as a tool for pre-sales in ISVs. The BI term itself was first introduced in 1989 by Howard Dresner as "concepts and methodologies to improve business decisions using facts and information that come from support systems" (Power, 2007). Perhaps a more appropriate definition is the one provided by Azvine (2006) and by Wells (2008) and Irena Hribar noted in 2009 (Rajteric , 2009):

• “BI is all about how to capture, access, understand, analyse and turn one of the most valuable assets of an enterprise – raw data – into actionable information in order to improve business performance" (Azvine B. , 2006).

• “Business intelligence the ability of an organization or business to reason, plan, predict, solve problems, think abstractly, comprehend, innovate and learn in ways that increase organizational knowledge, inform decision processes, enable effective actions, and help to establish and achieve business goals" (Wells , 2008).

• “BI is neither a product nor a system. It is an architecture and a collection of integrated operational as well as decision-support applications and databases that provide the business community easy access to business data” (Atre, 2003).

An appropriate definition should include the meaning of the word "intelligence" which, according to Oxford Dictionary, means:

• the ability to acquire and apply knowledge and skills. • the collection of information of military or political value.

Thus, the definition of “intelligence” in the business arena could be as follows:

"The ability of a business or organization to acquire and apply knowledge and skills"

Intelligence is intuitively related to objectives so that, it is posible to apply intelligence to a well-defined target. The highest form of objectives are ebedded into a business’ vision. Intelligence is a key element to achieve a vision. Even more, intelligence is required to design a well structured business’ vision. So, intelligence is present in the design process of a vision and its execution.



PEMBI defines business intelligence as:

“The ability of a business or organization to understand and solve problems through the management and improvement of knowledge, business skills and experience, all together aimed at achieving its vision”

The fundamental matter of the -business intelligence- (BI) is the vision of the organization. In the business arena, it should focus on the value proposition of their products and services and their delivery to the market. In a broader sense, should also include their value chain and furthermore, the environment related to their services or products.



However, the measurement of intelligence , for example in humans, has been the subject of great debate, trying to quantify precisely this ability in different axes of knowledge and human endeavors: a) professional, b ) social , c ) intrapersonal , d) knowledge and even e) spiritual. Sometimes measurement of intelligence in “knowledge” is still more specific, such as mathematics, English, engineering, programming and problem solving. In this sense, a common way of measuring human intelligence is known as IQ ("Intelligence Quotient"). The IQ of a person is "is a number that results from the realization of a standardized assessments to measure the cognitive abilities of a person in relation to their age group" (Definicion.DE , 2015). Interestingly, this metric is performed by comparing certain skills against other human beings.

Furthermore, once the measurement of a concept is given, it is common to analyze their development or behavior over time as a general practice. Moreover, it is possible to consider the "maturity" thesis which, specifically in the technology and software arena, was developed as the "Capability Maturity Model" or CMM in the late 80s and early 90s by Carnegie Mellon University at the Institute of Software Engineering. It uses and principles have been spread to other models that purport to represent the degree of development of different variables.

IQ



The maturity model for intelligence applied to humans could be based on the manner in which a person thrives his/her intelligence scaling its measurement into different levels. Related to such levels of intelligence, people use nouns in a colloquia way such as -silly-, smart, clever or wise to recognize the maturity level of human intelligence. A natural path of thoughts in this regard may lead us to define levels of business intelligence in organizations. At present, existing maturity models provide numerical levels or descriptors that do not necessarily categorize the "intelligence" qualitative or quantitatively using similar terms to smart, wise or genius. Would not it be logical to use similar adjectives to describe the maturity of the intelligence of an organization? Of course, modifying those adjectives that could be offensive.

At present there are various models of maturity of the intelligence of a business or organization , among those:

a) DecisionPath – BI Maturity Model. b) Gartner Maturity Model for Business Intelligence and Performance

Management. c) TDWI - Analytics Maturity Model and Assessment Tool. d) American SAP User Group BI maturity model.



3. PEMBI – Pemwork BI Maturity Model The Pemwork Business Intelligence (BI) Maturity Model is designed in 2015 as an evolving effort to establish parameters for the measurement of the "intelligence" of a business regardless of the software tools organizations use. PEMBI recognizes the importance of technology and tools, however, it makes a comprehensive analysis including the vision and business objectives of the organization. Organizations define a vision and pervasively shares it through diverse channels to the governing body and all employees. Vision is precisely the starting point in PEMBI to analyze the maturity of BI in an organization. Business Intelligence should be applied on achieving a vision in an effective and efficient way. In fact, the “rate of achievement in a time period” is a metric that is interesting when the success or failure of an organization is being analyzed. Indeed, PEMBI links the degree of achievement of the vision to the maturity level of the business intelligence.

PEMBI



PEMBI includes five levels (unconscious , astute, smart, clever, wise, holistic) in four

categories of study:

1. Vision. Every organization must define a vision (Ambler, 2013) and, in its broadest sense, strategic goals so that its vision might be reachable in time. Precisely the intelligence of the organization should be contrasted against their historical results in terms of their vision fulfillment. To accomplish this, it is necessary to analyze the robustness of the vision itself. Poor objectives will surely oblige their intelligence not to thrive properly. Vision should always go ahead execution.

2. Throughput. Business intelligence has to be analyzed in terms of explicit results achieved over time according to their vision.

3. Execution. The way organizations achieve their vision is a natural area to analyze decision-making mechanisms and processes that enable the achievement of results.

4. Capabilities. Precisely the collection of human skills, intangible and tangible assets in the organization is key to pursue its vision.

Vision

Throughput Execution

Capabilities



The PEMBI model distinguishes six levels of maturity (unconscious, astute, smart, clever, wise and holistic) in 4 categories and 18 areas of analysis shown in the following table:

Category Items/Levels Unconscious Astute Smart Clever Wise Holistic

Range Limited Low Medium HighConsider all

stakeholders

Considers full

ecosystem

Fulfillment Unaware Limited Measured FocusedRequires

constant updateHolistic

Strategic objectives CashflowReach critical

massStructured Flexible, Bold

Considers all

value chain

Drives full

ecosystem

Business focus Survival To stabilize Growth Growth LeadBeyond

competition

Goals Impact on cash

flowGrowth Performance Innovation

Innovation for

entire value chain

Designs

ecosystem

Effectiveness Unaware Lucky Structured Pursues

Drives value

chain

effectiveness

Drives society

Throughput / vision Unaware Dynamic Measured FocusedForces a new

vision

Creates others'

visions

Throughput / ecosystem Unaware Erratic Aware Ramping upLead the global

value chain

Creates rules of

distribution

Impact on chain value Unaware Unaware Aware Partial LeaderCreates new

value chains

Decision Making Poor Intuitive Structured Structured to all WiseWise for entire

ecosystem

Continuous improvement Non-existent Chaotic Key areas As a cultureExpands to value

chain

Address key

elements in

ecosystem

Knowledge Caotic Triggered Managed Used Used for value

chain

Shared with

ecosystem

Data Erratic Silos Share critical Share importantShare with value

chain

Shared with

ecosystem

Processes Primitive Changing Stable Flexible Drive value chain Drive ecosystem

Infrastructure Basic to deliverSilos to enable

operation

Improves on key

areas

Drived by

innovation

Integrated with

value chain

Optimally

managed

throughout the

ecosystem

Personnel Capabilities

Previous

immediate

experience

Develops as

required

Development

focused on key

(throughput)

Pervasive to all

(Talent factory)

Extends to value

chain

Shares and

leverages with

ecosystem

Governance Unstructured

Minimal, as

required to

deliver key value

Aligned with

innver visionFlexible

Aligned with

chain value vision

Drives the

ecosystem

Organization Follow the leader Dynamic Structured Adaptative

Flexible and

inclusive to value

chain

Considers full

ecosystem

Vision

Throughput

Execution

Capability



4. Vision

The vision of an organization is a key element to analyze the business intelligence since it determines the foundational desired future. It is precisely the vision that sets the direction for the organization. If it is not clear or its scope is not defined, it will be really challenging for the company to pursuit it. Ambiguity in its definition causes a weak link to its strategic objectives, and therefore imprecise alignment to short- and medium term goals. The vision determines the first element and certainly the most important when assessing the intelligence of a business or organization. Four areas of analysis to determine the level of maturity for the organization are considered:

Assertiveness. A vision should be the result of assertively addressing a market

need or solve a problem, in both current and future cases. There should be a

vision establishing a future model of society (and market) which serves

consistently with its approach. This analysis will also assess the relevance,

uniqueness and the degree of impact of such a vision on society as it

determines the final boundary of success.

Scope. A vision must provide a purpose to move defining a domain of

activities. It should be possible to define steps to assess if its accomplishment

is feasible. In this sense, it is good to set a challenging vision, not fully satisfied

today by other entities, including elements unresolved at present

nevertheless, according to the course and history of humanity, they can be



achieved. A vision should not go against the society it serves. It must be

inclusive and global. It must be divided into stages when deepen it. The scope

should establish reasonable time frames for the type of business that arises.

Today the trend is to be more aggressive in vision and in their achievement

over time. A few decades ago it was easy to think in visions to 10 or 20 years,

now marked trends in some sectors even less than five years term.

Focus. A vision should be future focused providing a direction to decision

making that drives all efforts and capabilities of an organization. Dispersion

reduces the degree and speed of achieving results. A vision’s focus has to be

concrete but challenging. A business case is how Amazon started with a vision

where they would become an on-line platform for selling "everything", while

their strategic objectives were initially focus on selling books on-line.

Strategic objectives. A vision must be grounded and naturally aligned to

strategic objectives. Objectives should be raised as a bridge to achieve the

current stage towards the vision. Goals should be attainable with existing and

reachable resources, they should be ambitious but cautious not to set

unrealistic expectations that could generate a negative effect on the

environment in the future. Strategic objectives used in-house might be

different than those used for public or marketing purposes, which provide

usually much more conservative metrics.

Goals. Business goals should be linked to strategic objectives, should you be

drafted according to known SMART principles (acronym for "specific,

measurable, achievable, realistic and timely"). The difference, in the context

of PEMBI, between objective and goal is that the objective is a statement that

provides the "core" of the desired direction of the organization while the goal

sets "specifics and metrics in time".


5. Throughput PEMBI considers the "Throughput" category as the most rigorous area to determine the BI maturity level of an organization where results metrics are evaluated with respect to its vision. It is an acid test to measure the intelligence of an organization and it is based on the most tangible asset: its performance towards its vision. Throughput is evaluated considering its current context and its history of achievement. There are four areas of analysis:

Effectiveness, valued as the current level of achievement

of the vision compared to its plan of accomplishment. It

focuses on the evaluation of metrics of accomplishment

and its analysis. It avoids subjective considerations and

tries to materialize its current position in an objectively

manner. Besides, metrics related to internal and external

(value chain and environment in general) impact are

considered in this area of analysis.

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Throughput / vision, looking at the historical evaluation

of results to achieve the vision. It has possibly been

necessary to rethink the vision due to the success or

failure of their results or even define other "visions" of

other institutions throughout execution.

Throughput / ecosystem in this area of study results of

the company are analyzed for their ecosystem, first

determining the influence of his execution in their

environment in general, to even assess their impact on

society in general. This area analyzes the degree of

influence on the environment to achieve results aligned

to their strategic objectives and vision.

Impact on value chain in this area of study the impact of

the results in the value chain is analyzed, movements

that generated over time in the different business

models of businesses that belong to the chain are

evaluated value. Also, their behavior will be analyzed

over the competition and its market share over time.

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6. Execution

Within the "execution" category PEMBI establishes different levels of BI maturity analyzing how the organization achieves results. Precisely, in this category an assessment has to be performed to study processes which involve: the generation and management of information for decision -making, innovation, continuous improvement and critical processes to deliver products and services to the market. Another important factor is related to the way people use data and knowledge to innovate processes and products / aimed at achieving the strategic objectives services.

Decision making. Decision-making in an organization is one of

the most important elements when it comes to non-

automated or repetitive areas. It is constantly necessary as we

approach the environment and our customers. Decision-

making plays a major role against competition and alliance

generated with the value chain to better compete against the

environment. The decision focuses more on the areas where it

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brings greater value and therefore becomes a critical area. At

present, however, it does not represent a formal area of skills

development. Usually it develops informally, without a

specific methodology or specific training within the

organization. Further information entries are critical as

ingredients to increase the likelihood of success in the

decisions made. Decision making has itself:

Inputs, the quality of data or variables that feed the

relevant indicators or gauges for decision-making is an

essential part of decision-making, otherwise you will

surely have the famous behavior called "garbage in,

garbage out" in English referred to "trash at the

entrance, garbage out."

Metrics, models and methodologies for making

decisions require variables, indicators or gauges that

allow them to qualify and quantify the state of the

same.

Methodology, where criteria for decision-making and

formal methodologies for evaluating alternatives in

staff having this function are established.

Outputs, on how to communicate decisions made and

their incorporation into cases of experience ensure

the ongoing evaluation to correct or adapt according

to the situation of the environment. You must prepare

a permanent monitoring model.

Performance. The implementation is a key element of

the decision making. Unexecuted decisions are

worthless. Decisions must permeate operating cadres

to establish the "hows" and thus achieve efficiently

its implementation.

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Continuous Improvement and Innovation. When the guidelines are

implemented through processes to provide a product or service to

market, it is necessary to continuously improve operations processes

and policies implemented by the organization. The degree of

maturity in the business intelligence is linked to how these processes

of continuous improvement and innovation are established and of

course, its impact on tangible results. Innovation processes and

continuous improvement, although studied in the category of

performance and potential impact in it, may impact other categories

such as the so-called vision or capabilities.

Knowledge. The management of knowledge generated by the

company is another element that assists the measurement of

intelligence of a business. The wealth of knowledge and experience

accumulated by the talent and the history of the business should be

managed properly to serve as input information analysis process to

detect weaknesses and opportunities of the hand with the decisions

of the company staff as well as the actors who play in the business

environment and of course, the same customers. Proper knowledge

management helps preserve the current stage of development and

the improvement and innovation power.

Data. The maturity of the intelligence of an organization can also be

observed when analyzing how to create, manage and use data /

information throughout the business process and even the value

chain. It is necessary to analyze the timing of the data, its validity,

quality, supply, storage, display and use for variables or composite

indicators. The data themselves do not represent relevant

information. The importance is due to its assertive and timely use,

always considering the quality and accuracy thereof for the detection

of strengths, weaknesses, opportunities and in general for making

decisions. The data must be analyzed by a shaft to establish the

impact on strategic objectives. It is an analysis of top-down to detect

critical data. This is done to avoid getting lost in a sea of operational

information that may not be relevant to the desired results.

Paragraphs critical analysis of these data are:

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Source, relates to the detection of the original source

of data. It should also establish its acquisition type:

automatic, manual, calculated.

Effective, window or point in time for which this data

is valid.

Context, definition or framework in which the data is

meaningless. For example, the process to which it

belongs.

Quality, reliability, repeatability and uncertainty of

the value of the data value over time.

Storage, storage mechanism of historical data, tools,

availability.

Variable, name of the variable that directly affects the data.

value, property value , type ( numeric, date , currency) and its

accuracy and its unity.

Presentation, what is used, what business intelligence

processes appear or part, what part or composite variables

are correlated.

Use, where that data is used. List of use-cases.

Unit (correlation), its dependence against other data in the

process.

Effort for obtaining quantitatively establish the effort required

to obtain it in relation to the list of applications.

Importance, which saves importance with respect to the

strategic objectives.

o Processes. Another element to assess the degree of maturity of the

intelligence of an organization to analyze business processes . The

business processes or organization symptoms of maturity of business

intelligence . When you have a low level of business intelligence ,

processes are erratic and do not meet customer expectations , nor in

time , background and form. A more mature stage show more

structured processes that provide certainty in delivering functionality

expected, customer service or providing an expected business

profitability.

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Also, a stage even more mature, it would provide processes that adapt

easily to market changes and customer expectations are flexible

processes according to the interests of the client (the term "time to

market" of the organization by example to describe the ease with

which a new design reaches the market and evaluation of their

success), which provide an expected and growing profitability over

time for business. The organization has mechanisms to incorporate

innovation into their processes is a natural ingredient that also

determines a greater maturity in the process. The processes can be

integrated into the value chain and the environment in general, giving

a sign of even greater intelligence organization. The involvement in the

design of processes external to the company (who reside in other

organizations, government or the customers themselves) to achieve

comprehensive customer satisfaction is a step that indicates a higher

degree of business intelligence.

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7. Capabilities

The capabilities in this context represents all the physical, financial and human assets that an organization has to implement and achieve its strategic objectives. Within this category the following areas are discussed:

Infrastructure. It refers to the assets necessary for the

implementation of processes to achieve strategic objectives.

Without a doubt, technology and its integration into the

organization represents an element to be analyzed carefully. In a

special section within this area, they are computer systems that

facilitate the availability of information and the detection of

threats or opportunities. This information is in the latter case for

analysis and decision making of the executive team. However, their

integration into the whole human organization that operates the

company's fundamental. Access to information for decision-

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making is critical. The unique and invaluable human activity

(thinking skills, creativity, self-criticism, imagination and

innovation) should be enhanced with tools. The data should play a

key role in integrating and operational dashboards that facilitate

the operation and direction of the current and future organization.

Paragraph infrastructure gives clear signs of maturity of business

intelligence in an organization. There should be no preconception

about a universal tool, but a set of tools to facilitate efficient and

effective decision-making general staff. It also facilitates

integration with value chain and customer. Furthermore, the

technology allows easy and have a clearer feedback from the end

user or customer. On the other hand, there is another asset

infrastructure also meets its operational role, for example,

machinery, plants, manufacturing equipment for the design of

products / processes and prototypes, control systems, facilities,

equipment and delivery logistics. Also within this infrastructure

financial resources available to the company are included. In this

latter respect its relevance is not evaluated (because this takes

place in the category called "Results"), but its existence is

evaluated here to establish the degree of freedom that the

organization to adapt to present and future.

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Staff capacities. This section discusses staff skills. Existing talent

and its management to achieve strategic objectives. Proper

management of human talent and its development over time

shows a relevant variable to determine the maturity of an

organization in terms of business intelligence. This section assesses

the talent structure and the organization’s developing skills over

time, as well as the retention mechanisms of critical talent in the

company. The remuneration scheme aligned to the objectives of

the company denotes another element to evaluate the maturity of

the organization. Another key component is to understand the

organization’s objectives, the talent organization and any other

available assets needed to reach the expected goals.

Corporate governance. The analysis of the "governance" of the

company is a relevant component that helps to determine the

level of maturity in terms of business intelligence. Undoubtedly,

the analysis of policies, procedures, participation and influence in

their value chain, environment and society in general are issues to

be analyzed in this section. Signs of maturity are shown with the

degree of intervention and influence inside and outside the

organization, for example, how quickly changes are implemented

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in the company, the effectiveness and efficiency of decision -

making, participation in relevant national and international

forums, the influence on world standards in relevant areas of the

organization.

Organization. The way in which the business and organizational

structure is established to meet the strategic objectives is an

element to be analyzed to determine the degree of maturity of the

business intelligence. The organization must be aligned to the

strategic objectives, which should evaluate how to permeate the

execution in the organization. This section is also necessary to

analyze information silos and relevance aligned vision. The

communication structure of objectives and control schemes of the

organization establish evidence of the state of maturity of business

intelligence. On the other hand, there must be a clear result in the

organization's success or failure. When speaking of failure or

random events, it is crucial to observe the mechanisms for

correcting the organization, the management of acquired

knowledge and assimilation of experience to take advantage of it

in a timely manner to observe the same or similar circumstances.

Create an adequate organizational structure is a complex element

that must adapt to the strategic objectives and depends on the

stage where the organization is located. The adaptation of the

organization over time is also a sign of the maturity of business

intelligence organization.

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8. Conclusion The four categories along with their 18 areas of analysis determined one of six levels of maturity of business intelligence organization: unconscious, astute, educated, clever, wise and holistic. Each area of analysis can be in different stages of maturity. In fact, it is not desirable in all cases to reach the maximum level (holistic wise) but the optimum level is determined by the level of maturity required to achieve the vision of the organization. Thus, the PEMBI model sets as initial goal, according to the nature of the business and aligned to its vision, to standardize the level in its different areas in which the organization is currently maturity. An example is shown below:

Category Area Level

Vision Assertiveness Smart

Alcance Clever

Strategic Objectives Smart

Foco Astute

Goals Clever

Throughput Effectiveness Smart

Throughput/Vision Smart

Throughput/Competition Smart

Impact/Value chain Clever

Impact/Ecosystem Astute

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Category Area Level

Execution Decision Making Astute

Improvement & Innovation Unconscious

Knowledge Management Smart

Data Smart

Processes Clever

Capabilities Infrastructure Unconscious

Human Capabilities Smart

Governance Smart

Organization Clever

You may also see the current state of organizational intelligence in a radial graph:

Another example of business intelligence maturity of an organization can be summarized as follows.

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An example is shown below:

In the chart above, it could pose as a first step to try to homogenize the areas that differ from the average further.

Category Items/Levels Unconscious Astute Smart Clever Wise Holistic

Range Limited Low Medium HighConsider all

stakeholders

Considers full

ecosystem

Fulfillment Unaware Limited Measured FocusedRequires

constant updateHolistic

Strategic objectives CashflowReach critical

massStructured Flexible, Bold

Considers all

value chain

Drives full

ecosystem

Business focus Survival To stabilize Growth Growth LeadBeyond

competition

Goals Impact on cash

flowGrowth Performance Innovation

Innovation for

entire value chain

Designs

ecosystem

Effectiveness Unaware Lucky Structured Pursues

Drives value

chain

effectiveness

Drives society

Throughput / vision Unaware Dynamic Measured FocusedForces a new

vision

Creates others'

visions

Throughput / ecosystem Unaware Erratic Aware Ramping upLead the global

value chain

Creates rules of

distribution

Impact on chain value Unaware Unaware Aware Partial LeaderCreates new

value chains

Decision Making Poor Intuitive Structured Structured to all WiseWise for entire

ecosystem

Continuous improvement Non-existent Chaotic Key areas As a cultureExpands to value

chain

Address key

elements in

ecosystem

Knowledge Caotic Triggered Managed Used Used for value

chain

Shared with

ecosystem

Data Erratic Silos Share critical Share importantShare with value

chain

Shared with

ecosystem

Processes Primitive Changing Stable Flexible Drive value chain Drive ecosystem

Infrastructure Basic to deliverSilos to enable

operation

Improves on key

areas

Drived by

innovation

Integrated with

value chain

Optimally

managed

throughout the

ecosystem

Personnel Capabilities

Previous

immediate

experience

Develops as

required

Development

focused on key

(throughput)

Pervasive to all

(Talent factory)

Extends to value

chain

Shares and

leverages with

ecosystem

Governance Unstructured

Minimal, as

required to

deliver key value

Aligned with

innver visionFlexible

Aligned with

chain value vision

Drives the

ecosystem

Organization Follow the leader Dynamic Structured Adaptative

Flexible and

inclusive to value

chain

Considers full

ecosystem

Vision

Throughput

Execution

Capability

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The development of business intelligence in time may suffer ups and downs over time depending on initiatives running. What is relevant in this regard is to always maintain a growing trend. As another example, shown below how the maturity of an organization is displayed on the typical time describing the various stages in the process of acquiring maturity.

Acquisition of Information. Most basic level of productive activities. Source data that isolation is the summary of the activity in its primary , unitary and simple way . These data in its most elemental form are stored in databases is isolated and registration information for any analysis or proof of a unit activity. Data structuring. It represents the first level of aggregation giving the first performance of a set of activities . Operating processes. It represents the next level of aggregation of data or information of a process. If it comes to a process or thread it is because information structures are usually grouped or associated with an area of responsibility of the company. Normally threads are defined by the different levels of responsibility or hierarchy established within and outside the company. Monitoring. The next stage is the monitoring of operating variables along different operating recorrridos or more generally, determining at each point certain criteria or business rules that take care of manually or automatically and detect behaviors outside the standards specified.

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Follow up. When you begin to establish business goals and its operation, monitoring compliance with these indicators is done, reporting automatically to monitor results. At this stage the key is to follow-up actions that are outside the process or atypical and correct feedback to maintain control of the operation. Diagnosis. When recurrent failures or bizarre behaviors appear, a diagnose stage that can be part of a structured process is established. This diagnosis determines causes that must be corrected in a timely manner. Analysis. Within the analysis stage, general application use cases or complex simulations using more specialized tools are applied. It usually involves more than one process and the involvement of multivariate models. Simulation and forecasting. This type of mechanism is established when the information is involved in complex processes. Thus the approach is to first reproduce the operating behavior and then make projections or scenarios to simulate its future behavior. Here it is necessary that the information is multivariate trends and history that allow reproduction accuracy of operational models and have an appropriate level of certainty in their behavior and prognosis. Optimization. Adjustments and improvements to operating processes. Innovation. Involve innovation to change focus or current operating models. Create new models from established mechanisms and arrangements that make the organization migrate to a new stage with impact on all company resources (technology, processes and people).

The Pemwork business intelligence model is accompanied by an organizational questionnaire that facilitates the initial diagnosis of organizations. This tool has been designed to facilitate the starting point plan, divided by categories and areas which is annexed as a questionnaire in this document.

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9. Preliminary Assessment Visit the URL: https://docs.google.com/forms/d/1dX6BgHjYQf9ydAuuImvOyeMjZsb0dfnhfzvWqBS9-Ng/viewform?c=0&w=1

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