An Overview of Knowledge Management in DeGPT System via Knowledge Audit

Transcription

1 3 rd International Conference on Managing Rivers in the 21 st Century: An Overview of Knowledge Management in DeGP System via Knowledge Audit CHANDRIKA MOHD JAYOHISA, Lecturer, Centre for Diploma Programme, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia LARIYAH MOHD SIDEK, ASSOC. PROF Head of Centre, Centre for Stormwater & Geohazard Management, University enaga Nasional, Jalan IKRAM-UNIEN, Kajang, Selangor. LIM LIYEN, Assistant Lecturer, Centre for Diploma Programme, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia SHARMILA RANI MOGANADAS, Lecturer, Centre for Diploma Programme, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia NUN SHWU HUEY, Lecturer, Centre for Diploma Programme, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia AMINAH AHMAD, Lecturer, Centre for Diploma Programme, Multimedia University, Jalan Ayer Keroh Lama, Melaka, Malaysia HIDAYAH BASRI, Research Officer, Centre for Stormwater & Geohazard Management, University enaga Nasional, Jalan IKRAM-UNIEN, Kajang, Selangor. ABSRAC Knowledge audit bases the crux of any knowledge management programs. he fundamental aspect of this paper is to conduct a four-phase knowledge audit on the Decision Support System of Gross Pollutant raps (DeGP) within the Department of Irrigation and Drainage (DID) of Malaysia. Knowledge needs analysis; knowledge inventory analysis; knowledge flow analysis and knowledge mapping encompass this knowledge audit process. Questionnaires and interviews were carried out to collate the relevant information. he findings indicated the strengths of the system as a knowledge hub and several gaps were identified as well. Finally, some additional recommendations were made pertinent to potential steps that might be taken to further support knowledge management system (DeGP) and the DID organization. Keywords: knowledge audit; knowledge management; gross pollutant trap; decision support system 1. Introduction he influx of knowledge management has long been prevalent in various organizations and industries throughout the globe. Additonally, the pressure of the emergence of the global knowledge-based economy and recognition of knowledge as key and intangible asset are making the effective management of knowledge a priority (Chong & Choi, 2005). Besides that, knowledge management is also perceived to help shape technological and organizational innovations of an organization for a more effective operation and thus enable an organization to better compete in the marketplace and for survival (Chong and Choi, 2005). Nevertheless, some studies have highlighted that many companies encountered failures in the implementation of knowledge management (Cheung, Ko, Chu, & Lee, 2005; Akhavan, Mostafa & Mohammad, 2005). Some of the reasons posited by Weber (2007) pertinent to knowledge management failures include: attempt to create a monolithic organizational memory; lack of integration between humans, processes and technology; contributors do not know the ideal specificity of knowledge; ignore impediments to knowledge transfer; do not properly oversee the quality of stored knowledge; do not promote collaboration, and etc. On the other hand, Cheung et.al (2005) pointed out that a company should be aware of what knowledge it has and what knowledge is important in order to implement KM strategies. he authors further stated that otherwise, this will lead to a waste of resources and capital as there is no return received. his entails the need for organizations to gain prior understanding of their knowledge state before embarking on any knowledge management programs. herefore, conducting a knowledge audit prior to knowledge management programs is deemed to be vital for any organizations (Hylton, 2002; Cheung et.al, 2005; Robertson, 2005). In essence, the knowledge audit is a fact finding, analysis, interpretation, and reporting activity, which 1

2 Rivers th 9 th December 2011, Penang, Malaysia includes a study of the company's information and knowledge policies, its knowledge structure and knowledge flow (Paramasivan, 2003). Further, Robertson (2005) asserted that knowledge audit can reveal the organisation s knowledge management needs, strengths, weaknesses, opportunities, threats and risks. Along with this, Hylton (2002) further emphasized that knowledge audit is also essential to implement a new KMsystem or to improve on the existing one. As is evident, several studies have used the knowledge audit approach to assess the knowledge health of the organizations as well as systems (Cheung et.al, 2005; Dow, Pallaschke, Merri, Montagnon, Schabe, Belingheri and Bucher, 2008). Likewise, this study has endeavoured to conduct a knowledge audit on the Decision Support System for Gross Pollutant rap (DeGP), which was developed by the Centre for Stormwater and Geohazard Management (CSGM) in University enaga Nasional (UNIEN). his system is perceived to be a catalyst for the Department of Irrigation and Drainage (DID) in acquiring, storing and retrieving relevant and resourceful knowledge of GPs in rehabiliating river system in Malaysia. With regard to this, a knowledge audit approach, which bases knowledge needs analysis, knowledge inventory analysis, knowledge flow analysis and knowledge mapping is presented and its trial implementation amongst the engineers of Department of Irrigation and Drainage (DID) throughout Malaysia is discussed. he analysis of the audit results deemed to provide an overview of the current knowledge coverage of the system and the DID as a whole. In addition, this paper also intend to shed light on the areas which may be improved to create, store, distribute and share the relevant knowledge between the DID employees and other potential users of the system, such as external consultants, researchers and the government. In short, the purpose of this paper is to present some preliminary results, in the aspect of current knowledge management of the DeGP in the context of DID as well as to make suggestions for future improvements. 2. Methodology In this study, knowledge audit on DeGP was conducted by adapting a knowledge audit tool from Sharma & Chowdhury (2007) which consists of the following four components: (a) Knowledge needs analysis (K-Needs Analysis) identifies knowledge possessed by engineers of DID in the area of GP and what knowledge they require in the future in order to perform their tasks. K-needs analysis also assesses knowledge sharing culture amongst engineers of DID in their organization (Chandrika, Sharmila, Nun, Lim & Aminah, 2010). (b) Knowledge inventory analysis (K-Inventory Analysis) identifies the knowledge assets and knowledge sources used by engineers of DID throughout the entire organization. K-inventory analysis involves surveys in order to classify explicit and tacit knowledge used by engineers of DID as sources of GP and where the knowledge are located within the organization (Chandrika et al., 2010). (c) Knowledge flow analysis (K-Flow Analysis) determines how engineers of DID find the knowledge that they want with manual procedure of GP and procedure with DeGP and how do they share the knowledge they have. his analysis will also determine how those tacit and explicit knowledge flows within the organization (Chandrika et al., 2010). (d) Knowledge mapping (K-Mapping) maps the knowledge assets and resources and the knowledge flow in the organization into a knowledge map. A knowledge map includes knowledge flow and show how the knowledge moves around the organization from organization from where it is to where it is needed (Chandrika et al., 2010). With the creation of knowledge map, knowledge gap can be identified. An in-depth interview with UNIEN researchers was held to obtain vital information such as knowledge needs identification. In addition, a short course was conducted in UNIEN for the purpose of trial session on DeGP. At the end of the short course, a questionnaire was distributed to respondents for the purpose of conducting this survey. he questionnaire had been divided into several sections which are: (1) Knowledge Management Readiness; (2) Knowledge on Gross Pollutant rap (GP); (3) User Satisfaction with DeGP; (4) Enhancement Strategies and (5) Demographic. For Part (1) to (4), Likert Five-point measurement was used. he profile of the respondents is shown in able 1 below. able 1: Profile of Respondents No. of ype of Work Respondent s Strategy / Policy 1 Design / echnical / Operations 12 Research / Science 5 Management 1 Others 9 3. Results and Discussion 3.1. K-Needs Analysis

3 3 rd International Conference on Managing Rivers in the 21 st Century: Knowledge audit was conducted on behalf of UNIEN in auditing the efficiency of the DeGP to its potential stakeholder and DID in Malaysia. he system was built to serve as a catalyst in sharing both explicit and tacit knowledge, supporting a continuous research and knowledge generation and become one of the smart tools in decision making for the DID and also to the researchers. An informal interview session was conducted with the stakeholders of the system who finds difficulties in getting and sharing information of Gross Pollutant rap especially when in needs of furthering research in Malaysia Waste Water Management. Furthermore, a longer time is needed to find and get both the tacit and explicit information. his portrays a lack of centralized mechanism and inadequate database hub, which keeps vital information and knowledge, facilitates knowledge sharing, reports record keeping and etc. Such circumstance, therefore, imposes difficulties in disseminating and sharing information effortlessly to other researchers and engineers. Furthermore, knowledge loss is also encountered within the organization as knowledgeable workers, such as experts, senior workers and management staffs leave the company with their innate knowledge, technical skills and experiences. For instance, essential knowledge, skills and experiences possessed by knowledge workers in selecting the GP trap, installing the traps in an area, identifying the types of gross pollutant and etc. will be drained out of the organization when the workers leave as the organization lacks the ability to capture and store them. o lend impetus to this, a mechanism that encourages proper knowledge storage and sharing is perceived to be crucial for the organization as well as the existing and future employees. raining was conducted in the second session, to expose the participants to the DeGP and questionnaires were given to them. Part A of the questionnaires is to determine the participant s organization culture and management support. he results from the questionnaires gave positive outcomes from the DID which reflected a positive organization culture and support from their higher level management in upgrading their skills and knowledge activities. Cheung, C. F., Ko, K. C., Chu, K. F. & Lee, W. B. (2005) stated the importance of people in contributing to one of the important components of KM since creating, sharing and using knowledge is something that is done by people. Likewise, even though, DeGP system helps to enable and facilitate in decision making and sharing information, yet it needs people to have a continuous support in using it. Culture, belief and understanding contribute to the success and failure between KM systems with people (Cheung et al, 2005). able 2 summarizes the ypes of Knowledge requires in dealing with GP knowledge which is then related to the objective and the functionalities of the DeGP. he results show that, currently there are limited resources in acquiring the different types of knowledge for the GP. As an example, currently it is difficult for the participants to understand and get access to sufficient data and working examples in choosing and estimating and to get the correct estimated detailed design of selected GP. ypically the participants depend on MSMA manual book for the formula and data, yet no example or method on how it is done is made available. his manifests the existence of limited information, researches and data in identifying the type of gross pollutant of a particular area. Such scenario necessitates the need for having more information in the future. ypes of Knowledge able 2: Summary of the ypes of Knowledge requires for the GP Exists Current R e q u i r e d Futu re DeG P Requ ired GP Maintenance 3

4 Rivers th 9 th December 2011, Penang, Malaysia General ype of Proportion of GP Choosing and estimating trapping devices Detailed design of GP Calculating of LCC 3.2. K-Inventory Analysis Knowledge inventory analysis comprises of 2 entities: Physical (Explicit) Knowledge inventory and Corporate Experts (sources of tacit knowledge) inventory (Cheung, Li, Shek, Lee & sang, 2007). In this phase, a knowledge inventory was constructed to record the knowledge needed for GP design based on the results obtained from the questionnaires. Knowledge sources used in the design, maintenance and calculation of GP were recorded into knowledge inventory as shown in able 3. he table reveals all the knowledge acquired by the engineers and consultants for completing the tasks. he knowledge inventory reveals what knowledge the engineers and consultants needed to make decision in each task and where they could find the knowledge and how they could find the knowledge. Based on able 3, the tacit knowledge is accessed from s, phone and face-to-face sessions with consultants, experts and suppliers. However, the explicit knowledge is extracted from documented records such as journals, reports and MSMA. Besides, most of the respondents revealed that explicit knowledge on GP can be obtained mainly from the internet, followed by MSMA Manual and journals (Figure 1). P r o c e ss / a s k Knowledge Items Knowledge of GP able 3: Knowledge Inventory Knowledge Source Internet / Journals/ MSMA Communicati on media E x p l i c i t / a c i t - E Experts/

5 Percentage, % 3 rd International Conference on Managing Rivers in the 21 st Century: GP s Maintenance General Construction General ype & Proportion of GP Choosing & estimating trapping devices Details design of GP Calculate the LCC / MSMA - E / Experts/ Internet / Journals/ Reports - E /MSMA (calculation & verification of the calculation and results) / Internet - E Project Managers / / Experts - - E Experts / / MSMA SBR - E Experts / / phone, Face - - E Experts / phone, Face Source of Knowledge Not Disclosed Books 22.7 MSMA Manual Source Internet Journals Others Figure 1: Source of Knowledge 5

6 Rivers th 9 th December 2011, Penang, Malaysia 3.3. K-Flow Analysis A K-Flow diagram was portrayed to show how knowledge moves between engineers of DID and the knowledge resources with a manual procedure (Figure 2). From K-Flow diagram, it is understood that engineers of DID acquire tacit knowledge from consultants, experts, and suppliers; whereas explicit knowledge can be acquired from internet, MSMA and journals in order to perform GP related tasks. In line with this, engineers of DID need to refer to all sorts of resources in order to obtain knowledge of GP. Knowledge such as GP s maintenance, general construction, choosing and estimating and detailed design of GP are most often referred to consultants, experts and suppliers. However, engineers of DID will also refer to explicit sources such as internet, MSMA and journals in attaining similar knowledge as provided by consultants and other sources. All in all, all the above mentioned sources play important roles in providing essential knowledge to engineers of DID in resolving issues related to GP. Choosing & estimating Detailed design of GP Calculating the LCC of GP Internet Experts Choosing & estimating Detailed design of GP Calculating the LCC of GP DID Detailed design of GP MSMA Choosing & estimating Detailed design of GP Journals Figure 2: K-Flow Diagram

7 Detailed design of GP Choosing and estimating Detailed design of GP Choosing and estimating 3 rd International Conference on Managing Rivers in the 21 st Century: 3.5. Knowledge Mapping Figure 3 shows how engineers of DID gather information to analyze and conclude result in GP. As mentioned in the K-Flow analysis, engineers of DID need to refer to explicit and tacit resources to gather all required information. However, with the existence of DeGP system, engineers of DID can analyze the results and thus decision can be made in a more efficient and better way. DOE (Department of Environment) DeGP General type & proportion of GP Choosing & estimating Detailed design of GP Inventory / Reference / MSMA Experts (Department of Environment) Calculating the LCC of GP Detailed design of GP DID Choosing & estimating trapping devices Internet Majlis Perbandaran Choosing & estimating trapping devices (Department of Environment) Detailed design of GP Project Manager (DID) Figure 3: K-Map 7

8 Rivers th 9 th December 2011, Penang, Malaysia Without DeGP system, we can see that engineers of DID need to request assistance from other parties such as DOE, consultants, Majlis Perbandaran and experts to complete their tasks. As a result, more time will be needed and it will incur more costs. However, with the use of DeGP system, engineers of DID can calculate the Life Cycle Cost of GP, assist others in selecting the right GP installation, reducing errors and mistakes in selecting the wrong GP and reducing the need to hire consultant. Moreover, the data collected, findings and results can be shared within the DID departments as well as other parties and can be used for future development. herefore, engineers of DID can accomplish tasks more quickly and job performance can be improved by speeding up decision making process. However, DeGP system also requires more information related to detailed design of GP, choosing and estimating and knowledge in GP in order to complete the tasks. From the study and the development of knowledge map, a few gaps had been identified. Currently, not all knowledge is being capture, store and share between the relevant parties such as consultants, government, suppliers and researchers in Malaysia. More research ought to be conducted in order to gather information that suits Malaysia s climate condition. Even though there s a positive results in knowledge sharing among the DID, yet the management of DID should continuously increase the awareness of storing more GP activities, projects and ongoing research done for their future decision making. Recommendations and Conclusion Knowledge audit is regarded as a crucial step of a knowledge management initiative. As is mentioned in the previous studies, knowledge audit tends to provide an evidence-based assessment of the knowledge management areas that require more focus and efforts from the organization. he focus of this paper is to establish a knowledge audit approach, composed of knowledge needs analysis, knowledge inventory analysis, knowledge flow analysis and knowledge mapping on the DeGP. he knowledge audit approach on the system is demonstrated through a case study, which was carried out amongst the engineers of DID in Malaysia. he aim of this knowledge audit reporting is also to elicit recommendations for review of the existing knowledge management strategy within the system as well as the organization as a whole. Recommendations include, to encourage knowledge sharing by awareness campaigns, seminars and workshops for all levels of society; the relevant findings of previous GP related studies should be made available to all potential users; the government should look into organizing more job-related trainings and workshops for DID employees and increase budget allocation for gross pollutant trap projects; encourage knowledge sharing by developing a website that gathers and incorporates GP related knowledge and references; and improvise the features, interface, automation and functions of DeGP to become more attractive for the users. In a nutshell, the findings of this research are deemed to upsurge the awareness and importance of knowledge sharing amongst employees of DID and other related parties; as well as to embark on improvisation on DeGP in order to contribute to the commercialization of the system to potential users. Acknowledgements he authors would like to express their sincere thanks to the Centre for Stormwater and Geohazard Management (CSGM), University enaga Nasional (UNIEN), Malaysia for their thoughtful insights in this research. Many thanks are also extended to the Department of Irrigation and Drainage (DID), Malaysia for their willingness to participate in this research. We would also like to thank the wonderful people at Multimedia University (MMU), Malaysia for their great work in providing research fund and handling administrative tasks. References 1. Akhavan, P., Mostafa Jafari & Mohammad Fathian. Exploring Failure-Factors of Implementing Knowledge Management Systems in Organizations. Journal of Knowledge Management Practice. Retrieved from: 2. Chandrika, M. J., Sharmila, R. M., Nun, S.H., Lim, L., Aminah, A. (2010), A Knowledge Audit Initiative on DeGP System: A Case Study on GP Consulting Firm, Conference Proceedings of Global Conference on SME and Entrepreneurship Cheung, C. F., Ko, K. C., Chu, K. F. & Lee, W. B. (2005). Systematic Knowledge Auditing with Applications. Journal of Knowledge Management Practice. Retrieved from: 4. Cheung, C. F., Li, M. L., Shek, W. Y., Lee, W. B., & sang,. S. (2007). A systematic approach for knowledge auditing: a case study in transportation sector, Journal of Knowledge Management, 11(4), Retrieved from: countid=28110

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