Journal of Knowledge Management Practice, August 2005

Preliminary Study: Knowledge Management (KM) Practices In The Small Medium Software Companies

Mohammad Nazir Ahmad Sharif, Nor Hidayati Zakaria, Nazmona Mat Ali, Mohd Zaidi Abd Rozan, Universiti Teknologi Malaysia

ABSTRACT:

Generally, knowledge management solutions provided by software developers and vendors do not target smaller-sized companies for their tools. This is because of purely market driven; small medium companies are apparently not a ready market. The large companies market is far from saturated; therefore there is no need to penetrate more difficult market such as small medium companies. However, we believe that Small Medium Companies (SMCs) also need KM. For example, in the context of Small Medium Software Companies (SMSCs), KM concept is not new. In fact, there have been KM related concepts such as knowledge assets, knowledge processes that involve in their business process. Whereas, the SMSCs itself is knowledge intensive organization wherein the knowledge is very crucial resources and has numerous of knowledge intensive tasks. Despite that, what we want to highlight here is about how far KM practices in SMSCs are systematically emphasized, managed, or being concerned among members. This paper concludes a review study of understanding KM practices in Small Medium Software Companies. Thus, as an initial stage, we propose a model as a framework of study for understanding KM practices in SMSCs. Although this is a review study, it has significantly sparked a new idea by giving a simple guideline as a basis for understanding KM practices in SMSCs.


Introduction

The broad range of knowledge management related articles, papers, books, authors, disciplines and conferences are evidences that KM is a discipline, which needs to be considered in any modern organizations. The KM literatures range from early awareness of the construct (Drucker 1967) and comprehensive overviews (Despres and Chauvel, 2000) and the development of specific applications of knowledge to work have been explored by industry practitioners such as Collison and Parcell (2001) in British Petroleum, Mann et al (1991) in power utilities and O’Dell and Grayson (1998) in management commentators and researchers (e.g. Carneiro 2000; Newell et al 2003). Despite of differences regarding to theory and practice in KM, there is a growing recognition amongst researchers, KM practitioners, industry alike for the need to better understand what knowledge is, the value of knowledge, and how it should be managed (Handzic 2001). In some cases this is formalized as KM and in other cases as the learning organization (DiBella et al 1996) or organizational memory (Weick 1979). However, all these are recent responses to the need to better understand and manage knowledge for success and survival in modern competitive environment. Factually, the central task of those concerned with KM is to determine best ways to develop, nurture and exploit knowledge at individual and convert it to organizational knowledge. In other words, it needs to ensure to get the right knowledge to right people just in time (Snowden 2002) and help people share and put knowledge into action in ways that strive to improve organizational performance (Dixon 2000; O’Dell and Grayson 1998).

In the emerging of KM, most of the larger companies or organizations consider KM as a vital tool for managing organizational knowledge. Mostly, KM solutions, tools are developed and proposed by KM vendors for implementing KM in various of large organizations, specifically for knowledge-based organizations. However, one area of omission in knowledge studies is within smaller-sized and medium-sized companies. In fact, they also need KM. In the context of small medium software companies, KM is a relatively not new. Contrary to the popular modern stance smaller medium companies were forerunners of KM. They have been practicing KM since ancient time. During ancient times, as small business moved towards growth, and the eventual development of ancient international business activity, knowledge of foreign markets, customs, customers, and trade winds were distinguished winners from losers. This was KM in action. This was KM initiated, implemented and practiced by smaller-medium sized business. While is true to say that smaller-sized and medium-sized companies have traditionally had a great understanding of the importance of knowledge for their business improvement. However, they keep slow in their feet when come to managing or leveraging the knowledge assets they have. They have failed to fully exploit highly valued knowledge assets, in order to help their business achieve competitive advantage. This is the reason that they must get back on knowledge management intention, as large companies seek to strengthen their control of the knowledge market.

In this paper, we propose a conceptual model as our framework of study to understanding KM practices in small medium software companies. The model was derived from literature survey of KM as mainly explained by Nonaka’s KM model (Nonaka and Takeuchi 1995) and KM framework by Handzic (2001). In order to understand typical key processes in software companies, we apply an improved Capable Maturity Model (CMM) for software or CMMSM (Johnson and Brodman 1997; Otaya and Cerpa 1999) as a basis guideline for understanding KM practices in smaller-sized companies with particular focus on project management process as stated in level 2, CMMSM. In section 2.0, we describe the concepts of KM, KM models and frameworks. Section 3.0 explains about small medium software companies, CMMSM, the nature and the need for KM in SMSCs. Section 4.0 discusses on our literature findings that towards on our work for understanding KM practices in SMSCs. Finally, in section 5.0 we conclude some remarks on our works mainly on how the proposed model should be realized and then possible model should be proposed by refining our conceptual model through a fieldwork study in SMSCs.

Knowledge Management

Knowledge management is widely regarded as the way an organization can leverage the tacit and explicit knowledge of its employees, trading partners, and outside experts for the benefit of the organization (Ackerman et al 2003; Bellaver & Lusa 2001; Choo 1998). KM regards knowledge as vital asset of an organization and systematically develops activities to manage it efficiently. Before we go further, we must be able to distinguish between data, information and knowledge. Ackoff (1989) defines data is raw. It simply exists and has no significance beyond its existence (in and of itself). It can exist in any form, usable or not. It does not have meaning of itself. In computer parlance, a spreadsheet generally starts out by holding data. Information is data that has been given meaning by way of relational connection. This "meaning" can be useful, but does not have to be. In computer parlance, a relational database makes information from the data stored within it (Ackoff 1989). Brooking (1999) describe information as organized data in context and knowledge as information in context with understanding on how to use it.

Basically, KM is about managing knowledge. Since KM is still a relatively new organizational paradigm, there are many definitions on KM (Davenport & Prusak 1998; Nonaka & Takeuchi 1995; Polanyi 1966; Galagan 1997; Drucker 1993; Demerest 1997; De Jarnett 1996; Quintas et al. 1997; Peters 1992; Brooking 1999). Most of the KM definitions are proposed by looking at different perspectives on KM as explained in (Rowley 1999). For example, from project-based perspectives, Davenport and Prusak (1998) defines KM as “Knowledge management is concerned with the exploitation and development of the knowledge assets of an organization with a view to furthering the organization’s objectives. The knowledge to be managed includes both explicit, documented knowledge, and tacit, subjective knowledge. Management entails all of those process associated with the identification, sharing and creation of knowledge. This requires systems for the creation and maintenance of knowledge repositories, and to cultivate and facilitate the sharing of knowledge and organizational learning. Organizations that succeed in knowledge management are likely to view knowledge as an asset and to develop organizational norms and values, which support the creation, and sharing of knowledge”.

Besides KM definitions, similarly, there have been many KM models and frameworks proposed in KM literatures (Nonaka & Takeuchi 1995; Boisot 1987; Chase 1997; Roos & Roos 1997; Demerest 1997; Hedlund 1994; Clark & Staunton 1989; Jordan & Jones 1997; Kruizinga et al 1997; Scarborough 1996). McAdam and McCreedy (1999) have also discussed differences among KM models by categorizing them into namely knowledge category models, intellectual capital models and social constructed models. For instance, KM model in (Nonaka & Takeuchi 1995) was assigned under knowledge category models in (McAdam and McCreedy 1999). Nonaka and Takeuchi’s KM model (see figure 1) assumes tacit knowledge can be transferred through a process of socialization into tacit knowledge in others and that tacit knowledge can become explicit knowledge through a process of externalization. The model also assumes that explicit knowledge can be transferred into tacit knowledge in others through a process of internalization, and that explicit knowledge can be transferred to explicit knowledge in others through a process of combination. Therefore, the transforming processes are assumed to be socialization (everyday comradeship), externalization (formalizing a body of knowledge), internalization (translating theory into practice) and combination (combining existing theories).

 

 

 

 

 

 

 

 

 

 

 


Figure 1: Nonaka and Takeuchi’s KM Model (1995) or SECI Model

From the Nonaka’s model as shown in figure 1, KM is described as knowledge creation process, which represented by spiral conversion mechanism. We believe that each process (socialization, externalization, internalization, combination) managing organizational knowledge assets or artifacts such as lessons learned, best practices, report, technical documents and so on. We can also elaborate the model by showing some examples of KM technologies that may be applied to facilitate the knowledge conversion process such as described in (Marwick 2001)

Small Medium Software Companies

Companies that develop software have a pressure from the customer to deliver better solutions, and to deliver solution faster and cheaper. Many researchers have worked on suggestion on how to improve the development process. As software development is a very knowledge intensive task, both researchers and industry have recently turn their intention to knowledge management as means to improve software development. A common way to develop software is to divide the work into several phases. A much-referenced model of such phases is the waterfall model, which comes in many variants, but most include (Sommerville 1996):

      Requirements analysis and definition – to find what the software system will be used for, that is, find the requirements.

      System and software design – make decision on technical issues, like software architecture, database design and user interface design.

      Implementation and unit testing – write, adapt or generate the actual code in programming language, test and each program unit.

      Integration and system testing – check the implementation fulfills the requirements.

      Operation and maintenance – enhance the software or correct errors that are found during usage.

The most popular model applied by many software organizations to improving their software development process is Capability Maturity Model (CMM) for software (CMMSM). The CMMSM in figure 2 was developed by the Software Engineering Institute provides a theoretical framework for the software engineering process improvement (Paulk et al 1993). This original CMM applies to new product development as well as software development.

It consists of five levels of maturity, and the key practices that organizations must implement to achieve each level. The maturity levels are: Initial, Repeatable, Defined, Managed and Optimizing. In example, organizations at the repeatable level (level 2) are assumed to have a chaotic software engineering process and they would need to implement some key management practices: Requirement Management, Software Project Planning; Software Project Tracking and Oversight; Software Subcontract Management, Software Quality Assurance and Software Configuration Management. These management practices help to put in place a basic disciplined process with the aim of obtaining a repeatable process.

 

Level

Focus

Key Process Area

5

Optimizing

 

 

Continual Process Improvement

 

 

Defect Prevention

Technology Change Mgt

Process Change Mgt

 

 

4

Managed

 

 

Product and Process Quality

 

Quantitative Process Mgt

Software Quality Management

 

 

3

Defined

 

 

Engineering Processes and Organizational Support

 

 

Organization Process Focus

Organization Process Definition

Training Program

Integrated Software Management

Software Product Engineering

Intergroup Coordination

Peer Reviews

 

 

2

Repeatable

 

 

Project Management Processes

 

 

Requirements Management

Software Project Planning

Software Project Tracking & Oversight

Software Subcontract Management

Software Quality Assurance

Software Configuration Management

 

 

 

1

Initial

 

 

Competent People and Heroics

 

 

 

Figure 2: Capable Maturity Model For Software or CMMSM (Paulk et al 1993)

Mostly, large companies improving the software development process by using CMMSM. However, small organizations have encountered difficulties applying the CMMSM, since some of its key practices are inappropriate to their software projects (Brodman and Johnson 1994; Otaya and Cerpa 1999). For example, small projects teams cannot cope with the overheads produced by the amount of documentation required by the CMMSM and they must use combined documents to reduce time. In small projects, team usually has a flat structure, resulting in developers being assigned several roles due to scarce resources. This contrast with the team structure and positions suggested by the CMMSM practices and makes some practices more difficult to be implemented. Therefore, the CMMSM has been tailored or generalized to apply it to any size business, organization or project (Johnson and Brodman 1997). Thus, the improved CMMSM version has solved these issues among others, making it easier for small medium software companies to implement this improvement framework. Otaya and Cerpa (1999) have applied an improved CMMSM for improving software development process in Winapp Company. By comparing Winapp’s current practices

with the key practices required by the CMMSM at level 2, as result, the company seems to be still at level 1 of CMMSM model (Otaya and Cerpa 1999). Moreover, Otaya and Cerpa (1999) have included training as another key process area in level 2, although the original CMM does not include it (Paulk et al 1993). Based on efforts in (Johnson and Brodman 1997) and experiences by Otaya and Cerpa (1999), we summarize an improved CMMSM for smaller-sized software companies as shown in figure 3. However, to discuss more on CMMSM is not our scope of this study. Actually, we only refer to the improved CMMSM as a guideline for identifying particular key processes area that we want to focus on when understanding KM practices in SMSCs. From that, we can look into related knowledge and how KM practices activities are implemented in each key process.

Level

Focus

Key Process Area

5

Optimizing

 

 

Continual Process Improvement

 

 

Defect Prevention

Technology Change Mgt

Process Change Mgt

 

 

4

Managed

 

 

Product and Process Quality

 

Quantitative Process Mgt

Software Quality Management

 

 

3

Defined

 

 

Engineering Processes and Organizational Support

 

 

Organization Process Focus

Organization Process Definition

Training Program

Integrated Software Management

Software Product Engineering

Intergroup Coordination

Peer Reviews

 

 

2

Repeatable

 

 

Project Management Processes

 

 

Requirements Management

Software Project Planning & Tracking

Software Subcontract / Employee Management

Software Quality Assurance

Software Configuration Management

Training

 

 

1

Initial

 

 

Competent People and Heroics

 

 

 

Figure 3: An Improved CMM For Small Medium Software Companies

(Johnson and Brodman 1997; Otaya and Cerpa 1999)

Literature Finding

Most of KM literatures show that people and learning issues are central to KM (Quintas et al 1977). The vast majority of the existing literature on KM covers these two related issues, usually in an organizational context and covering both theory and practice (McAdam and McCreedy 1999). Thus, KM not only combines theory and practice but also is multidisciplinary. Another important point is that, KM definitions are not predicated on information technology. Peters (1992) positively asserts that KM is not situated in the technology domain. However, a recent advances in technology have led to faster data transfer, but it remains a useful enabler rather than a central facet at the heart of KM. For example in Knowledge-based Knowledge Management (KBKM) proposed by Weber and Kaplan (2003), the development of Knowledge-based system (KBS) was tailored to knowledge management problem. However, clearly where the proposed KM solution is relevant if and only if technology is not taken as the fix for the problem. When an approach is taken whereby technology to fix for knowledge management, the knowledge management solution is less than satisfactory (Weber and Kaplan 2003). It is clearly that to success in KM need for integrated KM practices which influenced by such important factors as illustrated in KM framework by Handzic (2001). The framework (see figure 4) comprises of the essential components of KM and their interrelationships. It proposes two types of organizational factors; organizational environment (notably leadership and culture) and technological infrastructure (the information and communication resources), which may act as an enabler or constraint on knowledge processes (e.g. creation, transfer and utilization) and foster the development of organizational knowledge. The model allows the overall organizational environment to influence the choice of the technological infrastructure to facilitate knowledge process. Finally, the model incorporates a feedback loop to suggest the need for continuous knowledge measurement and potential adjustment of strategies over time.

 

 

 

 

 

 

 

 

 

 


Figure 4: An Integrated KM Framework (Handzic 2001)

In this paper, we propose a conceptual model of study for understanding KM practices in SMSCs. We refer to few key processes from level 2 (see figure 3) in CMMSM as a guideline for doing a fieldwork study. To visualize an overall picture of KM in SMSCs, we view those key processes in Nonaka’s SECI (Socialization, Externalization, Combination, Internalization) model and incorporate two types of organizational factors by Handzic (2001) in our model. Figure 5 shows the proposed model.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Figure 5: A Framework of Study For KM Practice in SMSCs

This model is a conceptual research model, which derived from our understanding on SECI model (Nonaka and Takeuchi 1995), CMMSM (Paulk et al 1993) and improved CMMSM for small medium software companies (Johnson and Brodman 1997; Otaya and Cerpa 1999) and also KM framework in (Handzic 2001). We refer to this model as our preliminary model for understanding KM practices in SMSCs. However, to tailor with the objectives and scopes of this research, we only focus on key area processes from repeatable level in CMMSM when come to conduct a fieldwork study. Finally, we adopt two important factors (Handzic 2001) as enabler or constraints to KM process then tailor to different key area process. We expect from the fieldwork, it will show that SMSCs also need for effectively implementing KM. In fact, by directly or indirectly, we believe that SMSCs have been practicing KM in their tasks through their KM processes (eg. sharing, creation, dissemination, etc) particularly, in different area of key processes as shown during CMMSM’s repeatable stage. We also expect some findings from the fieldwork that can assist us to refine this model and subsequently introducing some form of adapted KM model for tenderly understanding KM practices in SMSCs.

Conclusions

The aim of this paper is to give an overview of our preliminary study of KM practices in SMSCs. From a literature review, we propose a conceptual model as our framework of study for investigating KM practices in SMSCs. We derive the model by adapting established KM models (Nonaka and Takeuchi 1995; Handzic(2001). To tailor with the main area processes in SMSCs, we choose an improved CMMSM for smaller-sized software companies as our basis guideline when come to understand key process in SMSCs. However, we only concentrate on project management process as stated in level 2 of CMMSM. We will undertake a fieldwork study based on proposed model and expecting significant findings from it, which lead to produce an adapted KM model for KM practices in SMSCs. We believe that SMSCs also need KM and the reality is that, SMSCs is knowledge intensive organization and certainly KM practices have been practiced in SMSCs for ages. We also expect from a fieldwork, by having such model, we can know how KM practices in that CMMSM level (e.g. level 2) which lead to indirectly illustrate what level of that company according to the CMMSM.

Acknowledgements

This research was fully funded by the University of Technology Malaysia through Fundamental Research Grant.

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Contact the Authors:

Mohammad Nazir Ahmad Sharif(1), Nor Hidayati Zakaria (2), Nazmona Mat Ali(3), Mohd Zaidi Abd Rozan(4)

(1,2,3,4)Department of Information Systems, Faculty of Computer Science & Information Systems 81310, Universiti Teknologi Malaysia, Skudai, Johor.

Email: {nazir(1),hidayati(2) nazmona(3),zaidi(4)}@fsksm.utm.my