Development and evaluation ofa knowledge risk management

model for project-basedorganizationsA multi-stage study

Mostafa JafariDepartment of Industrial Engineering,

Iran University of Science and Technology (IUST), Tehran, Iran

Jalal RezaeenourDepartment of Industrial Engineering,

Industrial University of Science and Technology, Tehran, Iran

Mohammad Mahdavi MazdehDepartment of Industrial Engineering,

Iran University of Science and Technology (IUST), Tehran, Iran, and

Atefe HooshmandiDepartment of Management, University of Tehran, Tehran, Iran

Abstract

Purpose – This paper seeks to develop a model for risk management of knowledge loss in aproject-based organization in Iran.

Design/methodology/approach – This study uses a multi-stage research approach. In the firststage, existing practices are examined to develop a model for risk management of knowledge loss. Inthe second stage, the model is evaluated by testing it in a case study. The methods integrated as thefoundations of the Integrated KM and RM model are: the PMBOK risk management (RM) approach,the Fraunhofer IPK knowledge management (KM) model, and the TVA knowledge risk assessmentframework.

Findings – The analytical approach includes a six-step integrated model that manages the risk ofcritical knowledge in the case study. The results show that, after a year of implementing the model, thejob positions facing knowledge loss were reduced by 88 percent.

Research limitations/implications – The integrated KM and RM model can be used to assist theplanning, establishment and evaluation of knowledge loss in projects. This helps to ensure that keyissues regarding knowledge loss are covered during the planning and implementation phases ofproject management.

Originality/value – This study provides an integrated perspective of KM in project-basedorganizations. It offers valuable guidelines that can help decision makers consider key issues during arisk assessment of knowledge factors in project management. Outputs of this model can prepare anextensive assessment report about the risk of knowledge loss in a project-based organization withsuggestions for preservation plans to mitigate its effects.

Keywords Knowledge management, Risk management, Iran, Project management,Organizational change, Modelling

Paper type Case study

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0025-1747.htm

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Management DecisionVol. 49 No. 3, 2011

pp. 309-329q Emerald Group Publishing Limited

0025-1747DOI 10.1108/00251741111120725

1. IntroductionOrganizations today must respond rapidly to customer needs and rigorous globalcompetition. In response, there has been a strong increase in the move towardsproject-based organization. Projects are defined as unique and impermanent activitieswith altering manpower that are usually short term. Project members must respondrapidly to new situations in their tasks. The uniqueness and impermanent nature ofprojects are the main barriers to organizational learning (Hanisch et al., 2009). Thistype of organizational form is learning-intensive (Ajmal et al., 2010) and it has somelimitations such as high rate of employee turnover that are obstacles to the acquisitionof experience and knowledge gained in projects (Disterer, 2002). In addition, it is easilypossible for projects to become separated from one another, and this can lead to thefragmentation of an organization’s knowledge and expertise (Koskinen, 2010; Kang,2007).

In view of these limitations, the implementation of a process for protecting projectknowledge is a necessity for organizations. Jugdev (2007) proposes that organizationsshould frequently evaluate their investment in both tangible and intangible assets inthe project management environment because it can help project management to be afoundation of competitive advantage. Several researchers have mentioned theimportance of managing knowledge in the project management environment, but mostof these academics provide only restricted, anecdotal guidance for professionals whodesire to enhance their knowledge management (KM) capability in the projectenvironment ( Jugdev, 2007; Leseur and Brookes, 2004; Christensen and Bang, 2003).The final conclusion is that KM and project management should complement eachother (Leseur and Brookes, 2004).

In terms of the balance-sheet, evaluation of risk is of limited use because intraditional definitions knowledge and intangible assets are unaccounted (Caspary,2008; Martin et al., 2002). Losing these kinds of assets does not affect income directlybut it has important effects on the organization as a dynamic concept ( Jafari et al.,2007). Nowadays, knowledge is the key resource of economy and maybe it is the onlydominant resource of competitive advantage (Drucker, 1995; Jafari et al., 2009).Knowledge as an asset compared to other kinds of assets has a unique nature in whichthe more it is used the more its value increases ( Jafari et al., 2010).

Organizations cannot engage in risk management (RM) without accounting for theimportance of in-house knowledge. Identification and response to risk factors in eachorganization depend on its intellectual capital, that is, knowledge and judgments ofpersonnel. Personnel’s past experiences of situations can help predict potential events,therefore the main decision makers of organizations need to collect and manageemployees’ knowledge in order to recognize risk factors quickly and react to them(Neef, 2005).

A review of the literature (see Section 2) revealed that there is no appropriate modeldeveloped for project RM based on KM. In addition, among the previous relatedstudies, quantitative assessment of knowledge risk factors (KRFs) has not beenperformed, implying that the quantitative influences of KRFs on duration, cost andquality of a project have not yet been examined. In other words, among existingapproaches and developed models, there are not universal models that focus on bothKM and RM.

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So, the main objective of this study is to develop and evaluate a model for riskmanagement of knowledge loss in project-based organizations in combination with theFraunhofer IPK KM model, the Project Management Body of Knowledge (PMBOK)(2004) RM approach, and the TVA (2008) knowledge risk assessment framework. Theprincipal research question can be stated as “How well does the model presented in thispaper serve to identify and manage the risk of knowledge loss in a project-basedorganization?”.

2. Literature review2.1 Knowledge managementKnowledge is information in practice; it is a kind of personal information. Holm (2001)defines it as obtaining the right information, for the right people at the right time inorder to help them in problem-solving. The threat of losing the organizational memoryis one of the main reasons why KM has been accepted as part of management practice.So far, several different frameworks and models of KM have been developed. Nonakaand Takeuchi (1995) created a dynamic model to illustrate the interaction between twokinds of knowledge: tacit and explicit knowledge. Probst (1998) developed a descriptivemodel entitled “The building Blocks of KM”. In this model, KM can be visualized as adynamic cycle that spins permanently and includes eight blocks in the form of externaland internal cycles. The focus of the Fraunhofer IPK KM model is on value-addingorganizational processes, in which improvement of their key knowledge leads toimproved organizational operation. This model consists of four key activities:knowledge generation, storage, distribution, and application (Merits et al., 2003). Notethat in most of the references, KM has four main steps:

(1) Creation.

(2) Storage.

(3) Distribution.

(4) Usage (Berryman, 2005).

So, we consider Fraunhofer IPK KM model as a KM reference model in this research.

2.2 Risk managementRisk is an event or unclear situation that will influence the timing, cost and quality of aproject (PMBOK, 2004). RM is the effort to optimize decisions in order to reduceuncertainty about future events when the information is incomplete, unclear or underdiscussion (IRM, 2002). There are four well-known approaches to RM: PMBOK (2004),project risk analysis and management (PRAM) (Simon et al., 1997; Association forProject Management, 2004), management of risk (MOR) (Office of GovernmentCommerce, 2002) and the standard AS/NZS4360 (Standards Australia/Standards NewZealand, 2004). As can be seen in Figure 1, there is no significant difference betweenthem. The key steps of planning, identification, qualitative and quantitative analysis,reaction to risk, and controlling are present in all these approaches. The PMBOKapproach will be used in this article for RM; its six steps are as follows (PMBOK, 2004):

(1) Planning. The process of making decisions and outlining the RM and itsprocedure.

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(2) Risk identification. The process of identifying probable effective risk factors inrelation to project goals, determining their features, and finally documentationof findings.

(3) Qualitative analysis. Output of this stage prioritizes the project risk factorsusing the following categories: not very important, not important, averageimportant, important, and very important. The output does not consist of aprecise calculation of time and cost, rather it allows the less important riskfactors to be ignored.

(4) Quantitative analysis. The process of quantitative assessment of the probabilityof important risk factors and examination of their effects on project goals.

(5) Response to risk. The process of selecting and determining reactions in order toincrease likely opportunities and decrease threats to a project.

(6) Monitoring and control. The process of continuous monitoring of identified riskfactors, controlling the existing risk factors and defining the new ones.

2.3 Knowledge management and risk managementTah and Carr (2001) have developed a common language for describing risk factorsbased on a hierarchical-risk breakdown structure. According to their framework,defined risk factors and remedial actions can be implemented in a databasemanagement system to act as a knowledge repository. They followed a knowledgeengineering (and not KM) approach to acquire risk-related knowledge. A group ofresearchers from the ICAS business school (Martin et al., 2002) illustrated in their casestudy that applying knowledge in RM is one of the best ways to increase its value.Although their research presented a suitable use of KM systems by a propercombination of KM and RM discussions, it cannot suggest a suitable solution forgeneralizing the acquired result of this research to other organizations.

Akindele et al. (2004) tried to identify, qualitatively analyze and reactively plantoward risk factors of important investment projects at Melon financial company. Thisapproach did not refer to previous studies nor did it developing a conceptual model; itmerely dealt with software development. Jones (2005) examined information audit as aKM tool. The audit identified gaps and duplications as well as examples of bestpractice in information and KM across the organization. However it did not seek acomprehensive RM approach in the organization.

Figure 1.The comparison of RMapproaches

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Tennessee Valley Authority (TVA) started a project for controlling the knowledgeattrition of its processes in 1999, and developed a framework named TVA. The revisedthree-step framework of the TVA approach can be accessed through the internet (TVA,2008; IAEA, 2006). Its general view can be seen in Figure 2. It seems that, in the relatedreferences to KM and RM, this framework is the most complete approach so far.However it has some problems: first, it has been developed for organizational processesand is not suitable for the project-based organizations; second, there are no obviousrecords or results of its accomplishment; third, this framework does not deal withquantitative risk analysis of knowledge loss.

Zyngier (2008) conducted a case study research to strengthen KM strategies byusing RM as function of governance. This can ensure through developing RMreporting templates and procedures to guarantee appropriate feedback into KMsystem. In other words, RM can be used as an organized feedback to deal with culturaland structural risk factors to KM strategy.

Massingham (2010) has developed knowledge risk management of overallorganizational activities by presenting a conceptual framework that addresses themajor difficulties connected to traditional decision-tree tools of RM. This model haselaborative instructions for dealing with organizational risk factors. However, it seemsthat it is applicable for process-based organizations and not for project-based ones.Also, this model does not deal with quantitative risk analysis of knowledge loss.

Figure 2.TVA approach for risk

management ofknowledge loss

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3. Research methodIn this study, we adopted a multi-stage, multi-method research approach. In the firststage, we will examine existing practices to develop a model. In the second stage, weare going to evaluate our model by using a case-study approach. In Brewer andHunter’s (1989) point of view, the multi-method or mixed-method research approach “isa strategy for overcoming each method’s weaknesses and limitations by deliberatelycombining different types of methods within the same research problem”. Also thisapproach is identified as “triangulation”, when more than one method is employed inthe same study (Foss and Ellefsen, 2002).

Based on the literature review and considering the strengths and weaknessesobserved in past studies, the authors decided to firstly consider the TVA framework asa basis for developing a new KM and RM model. The Fraunhofer KM model waschosen among the KM models because of its simplicity and worldwide application. Inaddition, the PMBOK approach was considered to be the RM approach to proceed withbecause of the comprehensive nature of its approach. Therefore, as shown in Figure 3,a new integrated model was developed based on these three models and approaches. Inother words, management of organizational knowledge can be followed throughidentification, prioritization and dealing with the KRFs.

According to TVA (2008), we define a total risk factor for each of the employeesbased on two factors. The first factor is adapted from the date of attrition of humanresources as a result of retirement, resignation, or replacement (attrition risk), and thesecond factor shows the importance degree, the knowledge that the individual has inan organization (position risk factor). Total risk factor can be obtained by multiplyingthese two factors. Afterwards, by developing knowledge preservation plans and theiraccomplishment, it can pave the way for organizational KM. So, this article seeks adeveloped model in order to analyze the risk of losing organizational knowledge inproject-based organizations and to identify a management solution for this potentialthreat. In the remainder of this section, we will attempt to develop an integrated modelof KM and RM and then explain its elements. In Section 4 the mentioned model will be

Figure 3.Integrated approach ofKM and RM

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established in a Research and Development Institute (R&DI) of Iran, preparing the wayfor discussion and conclusion that will be provided in Section 5.

3.1 Research framework explanationStep 1: planning of knowledge risk management. This step is mainly to influenceorganizational culture and to acquire top managers’ commitment. Organizationalpolicies about how to face KRFs, responsibilities, and authorities should be determinedin order to cover RM duties. Also the acceptable risk level in an organization should bedefined in this step. In addition, project risk assessment techniques should bedetermined as well as a timetable for doing RM activities during the project life cycle andthe estimation of required budget for establishing the RM process should be defined.

Step 2: identifying KRFs. This step is to identify the characteristics of KRFs that haveinfluence on the project or organizational goals. According to TVA (2008) there are twokinds of KRFs: attrition risk factor (AR) and position risk factor (PR). AR states theexpected date of losing human resources. PR is determined on the basis of uniqueness orcriticality of employees’ knowledge, and by estimating the difficulty degree or level ofeffort required for employees’ to be replaced with a newcomer (IAEA, 2006).

Step 3: qualitative assessment of KRF. In this step, individuals or job positions thatcould potentially be a cause of loss of organizational knowledge should be identified. InRM literature, the risk factor can be calculated by multiplying two factors: risklikelihood and risk severity or impact (Tah and Carr, 2001). So, here we consider thelikelihood as AR the date of losing human resources. The date can be determined basedon personnel’s opinions or their ages and tenure date. Table I shows the criteria used toassign a value to AR. In this research we also consider the risk severity as the PR factorthat can be allocated based on Table II guidelines (IAEA, 2006). To determine PRvalue, direct and indirect supervisors should evaluate responsibilities, individuals’practical experience, informal and formal tasks, indirect duties, recurrent assignments(e.g. trouble shooting or problem solving) and other elements that have an influence onindividual knowledge. Here, the supervisor may decide to consult the project members,customers or other stakeholders to allocate PR (IAEA, 2006).

So, total risk factor (RF) can be obtained by multiplication of AR and PR accordingto equation (1), and regarding assessed, declared cases in Table III:

RF ¼ AR £ PR ð1Þ

Two responsible people who are direct and indirect (higher level) supervisors willassign values to KRFs. Note that their scoring will be RFs and RFm accordingly.

Criteria AR

Losing human resources in current year or next year 5Losing human resources in next three years 4Losing human resources in next four years 3Losing human resources in next five years 2Losing human resources in next six years 1Losing human resources in next seven years (or more) 0

Source: Adapted from IAEA,2006Table I.

AR allocating criteria

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Finally, allocated values will be added together according to equation (2). Allocation ofan upper coefficient value to RFs refers to direct supervisors’ closer contact withsubordinates and more complete awareness of individual’s AR and PR:

RFf ¼ 0:6 £ RFs þ 0:4 £ RFm ð2Þ

The RFf represents a comprehensive assessment of losing knowledge. Note that agroup revision of allocated PRs is a necessity because supervisors and managersusually allocate an upper KRF value to the more active employees. In other words, thefact that some employees perform better than others is not a reason to make theirknowledge critical for the organization.

Step 4: quantitative assessment of KRF. This step requires the statistical analysis ofthe consequences for individuals or job positions with RFf equal to or more than fifteen.In this step, the impact of each important KRF on project objectives (time, cost, andquality) will be determined through interviews with experts and acquiring their

Criteria PR

Critical and unique skills and knowledge. Critical knowledge about main processes oforganization. Special organizational knowledge. Undocumented knowledge. Requiresthree to five years of training and gaining experience. No ready replacements. 5Critical skills and knowledge. Knowledge that other people know about in a limited way.Some documents exist about it. Requires one to two years of training and gainingexperience 4Important fundamental skills and knowledge. Knowledge has been documented.Knowledge that other people have. Recruiting new personnel is possible and requires 6-12months of training 3Skills and knowledge that can be learned through procedures. Obvious and up-to-dateprocedures are available. Available training programs are effective, and they can makenewcomers ready in less than six months 2Ordinary skills and knowledge. The knowledge that outside workforces have, and theycan be simply recruited. Little training is needed 1

Source: adapted from IAEA (2006)Table II.PR allocating criteria

Index RFf

Zone 1 (very high importance): requires quick reactions within definite time limit. Thereactions are: knowledge preservation plan development, knowledge assessment andprofessional training 20.01 to 25Zone 2 (high importanve): requires development of staffing plans in order to addressmethods and timing of replacement, recruitment efforts, training and shadowing ofcurrent incumbent 15.01 to 20Zone 3 (moderate importance): requires development of plans to replace the related jobposition. For instance, recruiting new personnel and developing training programs 10.01 to 15Zone 4 (low importance): requires recognition of the related job position duties anddetermination of the need for a new replacement 5.01 to 10Zone 5 (very low importance): requires determination of the related job duties 1 to 5

Source: adapted from IAEA (2006)Table III.RFf assessment criteria

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opinions. After that, critical KRFs with the most harmful impacts should be identifiedthrough sensitivity analysis. The best tool for this step is a simulation that can beutilized with the Monte Carlo technique or Latin Hypercube method. After running thesimulation, the probability of achieving project objectives can be determined, and thenthe priorities of KRFs can be updated. After a comprehensive qualitative andquantitative risk assessment, knowledge preservation plans can be developed andimplemented. For calculating the duration of activities under risk factors, Dawood’s(1998) formula can be used according to equation (3):

Duration of activity A ¼ Min Ta þ ½MaxTa 2 Mina�*ðRFj £ DisRjÞ; J ¼ 1; . . . ; n ð3Þ

MaxTa and MinTa are optimistic and pessimistic durations of activity A, respectively.RFj is the impact of jth risk factor on supposed activity obtained through experts’judgment and past experiences as a percentage of lasting activity duration. Note thatthe overall impact of all risk factors must be 100 percent for each activity. DisRj is arandom number that can be extracted based on probability distribution of risk factor j.And, n is the number of project KRFs.

Step 5: designing and accomplishing the knowledge preservation plans. Aftercompleting the process of qualitative and quantitative risk analysis, the next step is todecrease the risk of losing knowledge from personnel who have the RFf with a veryhigh importance. Basically, any response to risk factors can be categorized into fourmain reaction groups: avoidance, transferring, mitigation or acceptance of risk factors.Regarding the risk importance, usually it is necessary to perform a reaction for eachrisk factor by selecting one, or more than one, group of them. Also, there are differentoptions for reaction to the risk of critical knowledge loss as addressed in Table IV.

However, because a project manager needs to pave the way for making decisionsabout the solutions facing KRF, it is necessary to get enough information through

Other reactionsStaffing orcontracting

Coaching andtraining Re-engineering Codification

Visiting or rotationalstaffCollateral duties ormulti-skillingReward supportingbehavior for learningclimateUsing retentionbonuses to encourageemployees to remain

Recruitment ortransferNegotiate withcurrent employee toadopt responsibilitiesEmploying part-timers, contractors,retirees

SimulatortrainingVideo andcomputer-based trainingOn the jobtrainingMentoring,shadowing andcoachingApprenticeshipplansCross-trainingMethodologyworkshops

ProcessimprovementUpdate equipmentSmart tools andtechnologyRemove task oractivityDesign open placesthat inspirecommunicationConduct projectreviews

DocumentationNovel orupdatedproceduresVideotapedinstructionsPerformancesupportsystemsConceptmappingStandardizingShared folders,intranetCapturelessons learned

Source: adapted from IAEA (2006)

Table IV.Methods of response to

KRFs

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technical interviews with the knowledgeable person, by an expert interviewer. For theprocess of defining the critical knowledge exposed to be lost please refer to IAEA(2006).

Therefore, the initial priority is to acquire and preserve knowledge of personnel whoare going to retire soon. It means that this plan should be developed and implementedfor each of those personnel who have an RFf over 15 and the quantitative risk analysisshows their significant impact on project goals. They may get promotion, replaced orleave the organization for any reason and this will lead to loss their valuableknowledge.

Step 6: monitoring and controlling KRFs. After designing and implementing theknowledge preservation plans, the most important thing is monitoring the process ofknowledge preservation that consists of:

(1) Review the progress of knowledge preservation plans.

(2) Identify positions or incumbents for which or whom reassessment ordevelopment of the knowledge preservation plan is required.

(3) Try to recognize related emergent subjects.

(4) Review the measurement criteria of knowledge preservation plans as follows:. prediction of future likely attritions;. numbers of positions given high priority;. numbers of determined positions for developing the knowledge preservation

plan;. completion of knowledge preservation plans;. knowledge metrics such as workforce performance; and. evaluation of impact of other activities on risk analysis.

(5) Evaluate the effectiveness of knowledge preservation plans in fulfillingdetermined goals.

4. Case studyThe authors were looking for a project-based organization that is exposed to the risk ofknowledge loss when they met the R&DI of an Iranian federal agency. As aproject-based company, R&DI was greatly reliant upon its workforce’s experience tofulfill customer needs. As a governmental body, the mission of R&DI is design,development and manufacturing of a specific high-tech product family, and its budgetis assigned based on project definition and implementation, and based on customerneeds according to its mission. So, it is possible for individuals to cooperate with eachother in project teams. Despite its short lifetime, one of the serious problems that theR&DI faces is the greater attractiveness of some other industries such as car,petrochemical and service industries which leads to a decreasing number of expertsand organizational knowledge loss; there was also a high employee turnover in theR&DI.

Design teams work together in four functional departments and one of them plays arole in main projects as a manager and chief-designer. The Project Planningdepartment monitors the performance of these four Design departments, and it is alsoresponsible for establishing new management systems. The Human Resources and

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Financial department is in charge of supporting the R&DI processes and recruitinghuman resources based on the R&DI’s human resource development plan. Theeducational characteristics of the R&DI are shown in Table V. Currently, the number ofpersonnel is 175 of which 113 are working in technical workforces and the others aresupportive staff.

Know-how plays an important role in the R&DI and it can be considered aknowledge-based organization. When newcomers join the R&DI they should be trainedon the job regardless of their experiential level, and they need to acquire experiencethrough observation and hands on actions. The necessary time for preparing everyworkforce is at least three months and during this period they are not allowed to workon main projects.

In recent years, a suitable orientation has been initiated in the R&DI aboutmanaging knowledge recourses. These initiatives are made up of strategydevelopment and also development programs for acquiring, preserving andtransferring the knowledge and skills of personnel. Also, this orientation containsthe aim of developing cooperation with universities and research institutes,establishing and supporting technical committees, holding public and professionalseminars, promoting researchers, developing the company’s network and portal. Interms of the problem of losing knowledge resources, a KM project was defined in R&DIin early 2007. One of the most important activities for the establishment of a KMprocess is recognizing the points at which individuals’ or groups’ knowledge inventoryis most important. Therefore, at first, design and development departments wereconsidered as the main points of technical knowledge in R&DI. According to thefollowing steps, the integrated KM and RM model was implemented in thedepartments.

4.1 Knowledge risk management planningIn this step, the most important problems were in making preparations and getting thetop manager’s support of this strategic decision. After that, the top manager made aneffort to state the necessity of commitment of all departments and personnel to theprogram. In addition, resources had to be made ready, such as selecting KM teammembers and providing necessary documents, and these were discussed andconfirmed by the top manager after several sessions. The KM team leader was one ofthe top supervisors of the Project Planning department who had been fully trained inKM. The members of the KM team were three experts from the Project Planningdepartment who were also trained in KM. The Project Planning manager had theresponsibility to monitor the performance of the KM team and the results of sessions

Educational degree No. of individuals Percentage of individuals

Diploma 19 10.9Associate degree 24 13.7Bachelor’s degree 81 46.3Master’s degree 49 28PhD 2 1.1Total 175 100

Table V.Educational structure of

R&DI case study

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and assessments were delivered to the top manager after his endorsement. Afterselecting the KM team members, a program was developed for implementing theintegrated KM and RM model. In this program, it was determined that team membersneeded to complete the preparation and planning activities by the end of March 2007,and from April the next steps of the model should be started.

4.2 Identifying KRFsIn this stage, a knowledge risk card was designed as illustrated in Figure 4. Thecharacteristics of all the workforces in technical positions were recorded in Section A ofthe card. The knowledge risk cards were then sent to the Design and Developmentdepartments so that Sections B and C could be completed. This card was used fordetermining workforces’ AR and PR. Both direct and indirect supervisors should statetheir opinions on the card. Collected cards were delivered to the KM team to check theinformation validity. When there was more than one unit of difference between thevalue assigned by a direct or indirect supervisor about any of ARs and PRs, therelevant card was sent back to that supervisor to be reviewed and corrected.

4.3 Qualitative assessment of KRFsThe most important component of qualitative risk analysis is to identify the priority ofKRFs. So, all the ARs and PRs were integrated together based on equation 2, and thenRFfs were calculated and recorded on cards. Note that allocated values reviewed bydirect and indirect supervisors in the cases of having more than one unit of differencesare indeed similar to the revision of KRF values. Finally, by calculating RFfs, a scatterdiagram of them in all risk priorities was extracted as illustrated in Figure 5. In total,17 persons had RFf greater than 15 and were in the dangerous zone, and so quantitativerisk assessment should be done for them.

Figure 4.Knowledge risk card

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4.4 Quantitative assessment of KRFsIn order to evaluate the quantitative influences of losing individuals’ knowledge onorganizational goals, one of the main projects of R&DI that had allocated more than 70percent of R&DI’s resources to itself, became the assessment basis. Regardless ofKRFs, normal duration for this project accomplishment was estimated at about twoyears, and the project was about to be started. In this stage, it was necessary to analyzethe influences of KRFs on the main objectives of the project (i.e. quality, time, and cost),this was started by holding some sessions with R&DI experts and supervisors toevaluate their opinions. At the first step, project quality should be taken into account asa determining factor in reaching the project goals. Based on experts’ opinions, it wasspecified that all of the eight individuals with RFf greater than 20 had an importantcontribution to make to the quality of the project due to their key roles in the project.Therefore, planning and implementation of knowledge preservation plans for theseeight people were given priority. After completion of these eight KRFs, the quantitativeanalysis for the remaining nine high important KRFs could be conducted. So, theexperts were asked to declare their estimation of duration and cost influences of theseKRFs on each important project activity. The percentage of influences of all KRFs onthe duration and cost of important project activities can be seen in Figure 6. The finalimpact of KRFs on duration of activities could now be obtained using equation 3. Forextracting the distribution function of duration and cost of activities, the Monte Carlosimulation method was utilized using Palisade@Risk 4.5 software. As a result,according to the last column of Figure 6, distribution functions of duration and cost ofactivities were extracted after a thousand simulation runs.

For all the activities, duration and cost distributions were entered in the PertmasterProject Risk V8.1 software for simulation. After the simulation, influences of KRFs onproject duration and cost can be identified, and so distribution of duration and cost of

Figure 5.Scatter diagram of RFf

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Figure 6.Duration and costestimation of project underthe KRFs

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the project can be extracted. Final results of the project simulation under the KRFsusing the Latin Hypercube method after a thousand runs are illustrated in Figure 7.

According to Figure 7, the probability of an on-time project completion withinplanned costs (761 days and 243,715 million Rials) has been estimated at less than 1percent at a confidence level of 95 percent. In other words, if we want to predict theduration and cost of project completion at 85 percent confidence level, they would berespectively about 899 days and 343,524 million Rials. It is obvious that the result canbe a challenge for R&DI in satisfying customer needs. So, it is necessary to conductsome prevention plans for controlling the project KRFs.

After project simulation under the KRFs, in order to prioritize each KRF incomparison to the others, it is necessary to separately simulate the total duration andcost of the project under each of the KRFs. Table VI shows these simulation resultsunder the nine recognized KRFs. In order to calculate quantitative priority of KRFs inthe second and third rows of Table VI, difference percentage of project duration andcost (at confidence level of 85 percent) have been calculated compared to the plannedtime and cost. Regarding the project manager’s opinion, it was defined that anyexpansion in the project duration is twice as important than any increase in the projectcost. So, normalized weights of duration and cost can be considered as follows:

W ¼ ðtime; costÞ ¼ ð0:67; 0:33Þ

Regarding the duration and cost weights, simple additive method (SAW) can be easilyused to prioritize the KRFs. Based on this method, the quantitative priority of projectKRFs are shown in the end row of Table VI.

Based on the risk priorities, it is obvious that after the eight very high importantKRFs of the previous step, KRFs 6, 5, 1, 4, 7, 2, 3 and 8 have the most influence on theproject goals.

4.5 Designing and accomplishing knowledge preservation plansAfter the quantitative analysis, reaction to KRFs 3, 8, and 9 was acceptance of thembased on the coordination with the project manager. However, it was necessary todevelop knowledge preservation plans for the first eight very high important KRFsand then for the KRFs 6, 5, 1, 4, 7, and 2. This was carried out through holding somesessions with high priority knowledge workers (i.e. KRFs). As a result, criticalknowledge was recognized and the way was paved for preservation plan development.A sample of knowledge preservation plans for a job has been shown in Figure 8.

After the development of 14 knowledge preservation plans, these plans wereimplemented at R&DI. Nine of the aforementioned people who were about to retire, andwanted to be moved to another position or to leave the organization, were replaced with

Figure 7.Final results of project

simulation under theKRFs

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89

Table VI.Decision matrix andquantitative priority ofKRFs

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new ones. The remaining five individuals were ready to continue with job promotion.As a result, nine job instructions were documented through implementation of theknowledge preservation plans.

4.6 Evaluating the knowledge preservation plansThe significant point in evaluating the development of knowledge preservation plansis repeating the risk assessment of KRFs in contingency and periodic span of time. It isnecessary to implement the qualitative risk analysis process every year. In addition, inthe case of employees’ replacement or resignation, each of the supervisors andmanagers of the R&DI had the authority to ask the KM team leader to review therelated knowledge risk card. Therefore a year after implementation of the IntegratedKM and RM model, knowledge risk cards of all individuals were reviewed, and thescatter diagram of RFfs can be seen in Figure 9. After a year of implementation of thepreservation plans, a large number of KRFs in zones 1, 2, and 3 transferred to zones 4and 5. Therefore, critical KRFs have been decreased significantly.

5. ConclusionNowadays most organizations face a challenge resulting from knowledge and skill lossof human resources. Usually this knowledge is undocumented and to acquire theseskills require years of experience. Knowledge can be lost through different ways:retirement, internal replacement, or personnel quitting. This research presented amodel to show what the threats of losing critical knowledge of employees who areabout to retire, move or leave the organization would be by developing a KM modelbased on a risk assessment approach. In addition, some solutions were presented formanaging the knowledge of these employees, and decreasing the risk of losing theirknowledge. With slight changes, this model can be applied to a wide range of profitand non-profit project-based organizations.

Figure 8.A sample of knowledge

preservation plan for a jobposition

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Real information from a R&DI of Iran was used to deploy the developed model in a realsituation. Research results paved the way for preserving knowledge properties of theR&DI by identifying and managing the critical knowledge of key personnel: a yearafter implementation of the mentioned model, the numbers of job positions facingcritical knowledge loss decreased by 88%. It seems that this model will prepare asmooth and easy way to forecast cost and duration of projects under KRFs.

There are some restrictions to the implementation of this model. The task ofallocating influences of KRFs on activity durations will prepare an important inputdata that has a significant influence on model outputs. There is not a suitable set ofdata about distribution functions of KRFs and their effects on project goals in mostproject-based companies, so generating reliable input data based on experts’ opinion isan important issue that should be taken into account.

An important point that should attract future research is that almost all the expertswho have unwritten critical knowledge are key personnel in organizational dailyactivities, and therefore they have limited time. A process that could be suitable is toconduct a knowledge self-assessment process (for more information please refer toIAEA, 2006).

Another limitation of this model occurs due to its implementation in just one mainproject. So, another important consideration for future study is to implement the modelfor a set of projects concurrently. Additionally, it seems that qualitative risk analysis ofKRFs based on strict ordinal numbers has some inbuilt bias. In order to handle theinherent subjectivity a fuzzy logic approach can help to deal with problems connectedto quantification of linguistic terms.

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Figure 9.Scatter diagram of RFfs

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About the authorsMustafa Jafari is an Assistant Professor in the Industrial Engineering Department in IranUniversity of Science and Technology (IUST), Tehran, Iran, with BSc in Mechanical and MSc inproductivity and PhD in Industrial Engineering from I.I.T. Delhi. He works in the area ofStrategic Planning, Business Process Reengineering, Human Resource Management andKnowledge Management, with more than 30 research papers and five books in the area ofindustrial engineering. Mustafa Jafari is the corresponding author and can be contacted at:mostafajafari2006@yahoo.com

Jalal Rezaeenour received his BSc and MSc in Industrial Engineering from Iran University ofScience and Technology, and currently is a PhD candidate in the same university. His researchinterests are in Performance Measurement, Knowledge Management, Decision Making and

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Multivariate Data Analysis. He has published one book and has more than 15 refereed papers indifferent conferences and journals.

Mohammad Mahdavi Mazdeh is an Assistant Professor in the Industrial EngineeringDepartment in Iran University of Science and Technology (IUST), Tehran, Iran. He received hisBSc and MSc in Physics from Tehran University of Iran and his PhD in Industrial Engineeringfrom Brunel University in London, UK. His research interests are Strategic Planning, Schedulingand Sequencing, Supply Chain Management and Knowledge Management.

Atefe Houshmandi received her BSc in English Literature from Azad University of Iran. Sheis currently a Master’s student of Urban Management at University of Tehran. Her researchinterests are in Human Resource Management, Knowledge Management, Urban Managementand English literature. She has more than nine years of experience in the field of teaching Englishliterature and managing related institutes.

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