Identifying the knowledge management structures in enterprise systems projects

Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

Knowledge management for ERP success

The business value of Enterprise Resource Planning (ERP) systems and in general large software implementations has been extensively debated in both popular press and academic literature for over three decades. Despite the positive motives for adoption, various organizations have reported negative impacts from these large investments. This ‘disconnect’ between large IS investments and firms’ organizational performance may be attributable to the economic transition from an era of competitive advantage based on information to one that is based on Knowledge. This paper discusses the initial findings of a two-phased study that focuses on empirically assessing the impact of knowledge management on the success of Enterprise Resource Planning systems. The research study uses information gathered from twenty-seven public sector organizations in Queensland, Australia. Validation of the a priori model constructs through factor analysis identified two dimensions of knowledge management. Further analysis assessed the comparative differences in perceptions of knowledge management in ERP, across four employment cohorts.

Succession management as a knowledge management strategy

One of the most critical issues for building innovation capacity in organisations is the acquisition and maintenance of knowledge. As knowledge is the basis of human capital, then the ability to attract, retain and engage talent is argued to be an important element of innovation. By attracting and retaining good staff, the organisation is retaining organisational knowledge which is necessary particularly for exploitation of current capabilities, but will also contribute to capacity for exploration for future innovation. This paper addresses the importance of retaining and developing staff as a critical issue for knowledge management and addresses the issue of retaining talent through effective succession management practices. The findings from an exploratory study into current practices in the Australian rail sector, provides further insight into the potentially critical issues for the effective use of succession management as a knowledge management and employee retention tool for building innovation capacity.

Systematising knowledge management in projects

Purpose – The purpose of this paper is to provide a practicable systems-based approach to knowledge management (KM) in a project environment, to encourage organisations to unlock the value in their review processes. It relies on knowledge capture and storage at decision review points, to enrich individual, team and organisational learning during the project life cycle. The project's phases are typically represented horizontally with deliverables (objectives) or project "promises" as the desirable outcomes. The purpose of this paper is to give expression through introducing a vertical dimension to facilitate the KM process. A model is proposed that conceptualises project-specific knowledge drawing on and feeding into the organisation's knowledge management system (KMS) at tactical and strategic levels. Design/methodology/approach – This conceptual paper links concepts from systems theory with KM, to produce a model to identify, collate, and optimise project-based knowledge and integrate it into the management process. Findings – The application of the system theory approach enriches the knowledge generated by a project, and feeds it into the next phase of that project. At the same time, it contributes to the individual's and project team's KM, specifies possible courses of action, together with risks, costs and benefits and thus it expands the organisation's higher level KMS. Research limitations/implications – The concept suggests that the knowledge capture, storage and sharing process may best be undertaken holistically, in view of the systems relationships between the tasks. Systems theory structures this process. Research opportunities include studying the interfaces between levels of KM, in relation to the project's progress. Practical implications – Reconceptualisation of the project as a knowledge creation process may improve the project's progress as well as add to the individual's, project team's, and wider organisation's knowledge base. An example is given. Originality/value – This paper illuminates the broader potential of under-utilised opportunities in well-known management approaches to add dimension to the business project, of knowledge creation, storage and sharing.

Extending knowledge management across the supply chains in the construction industry : knowledge sharing in construction supply chains

Supply chain management and knowledge management have emerged as two distinct business philosophies in the last decade. Both are making rapid inroads into the construction industry. The premise of this paper is that knowledge management would make it possible for all the trading partners in a supply chain to reap benefits. Current research in knowledge management in the construction industry is generally targeting those big organisations that are main contractors. This has restricted the scope of knowledge management, and limits the benefits to a few, rather than the whole industry. If the construction industry as a whole is to prosper and improve its productivity, strategies for knowledge management strategy at the industry level must be established. This paper argues the case for extending the scope of knowledge management across the full extent of the supply chain, and attempts to identify the benefits that may arise out of sharing knowledge across the supply chain.

Five case studies applying soft systems methodology to knowledge management

Construction projects are faced with a challenge that must not be underestimated. These projects are increasingly becoming highly competitive, more complex, and difficult to manage. They become problems that are difficult to solve using traditional approaches. Soft Systems Methodology (SSM) is a systems approach that is used for analysis and problem solving in such complex and messy situations. SSM uses “systems thinking” in a cycle of action research, learning and reflection to help understand the various perceptions that exist in the minds of the different people involved in the situation. This paper examines the benefits of applying SSM to problems of knowledge management in construction project management, especially those situations that are challenging to understand and difficult to act upon. It includes five case studies of its use in dealing with the confusing situations that incorporate human, organizational and technical aspects.

An exploration of knowledge management and intellectual capital in a nonprofit organisation context

In recent years, practitioners and researchers alike have turned their attention to knowledge management (KM) in order to increase organisational performance (OP). As a result, many different approaches and strategies have been investigated and suggested for how knowledge should be managed to make organisations more effective and efficient. However, most research has been undertaken in the for-profit sector, with only a few studies focusing on the benefits nonprofit organisations might gain by managing knowledge. This study broadly investigates the impact of knowledge management on the organisational performance of nonprofit organisations. Organisational performance can be evaluated through either financial or non-financial measurements. In order to evaluate knowledge management and organisational performance, non-financial measurements are argued to be more suitable given that knowledge is an intangible asset which often cannot be expressed through financial indicators. Non-financial measurement concepts of performance such as the balanced scorecard or the concept of Intellectual Capital (IC) are well accepted and used within the for-profit and nonprofit sectors to evaluate organisational performance. This study utilised the concept of IC as the method to evaluate KM and OP in the context of nonprofit organisations due to the close link between KM and IC: Indeed, KM is concerned with managing the KM processes of creating, storing, sharing and applying knowledge and the organisational KM infrastructure such as organisational culture or organisational structure to support these processes. On the other hand, IC measures the knowledge stocks in different ontological levels: at the individual level (human capital), at the group level (relational capital) and at the organisational level (structural capital). In other words, IC measures the value of the knowledge which has been managed through KM. As KM encompasses the different KM processes and the KM infrastructure facilitating these processes, previous research has investigated the relationship between KM infrastructure and KM processes. Organisational culture, organisational structure and the level of IT support have been identified as the main factors of the KM infrastructure influencing the KM processes of creating, storing, sharing and applying knowledge. Other research has focused on the link between KM and OP or organisational effectiveness. Based on existing literature, a theoretical model was developed to enable the investigation of the relation between KM (encompassing KM infrastructure and KM processes) and IC. The model assumes an association between KM infrastructure and KM processes, as well as an association between KM processes and the various levels of IC (human capital, structural capital and relational capital). As a result, five research questions (RQ) with respect to the various factors of the KM infrastructure as well as with respect to the relationship between KM infrastructure and IC were raised and included into the research model: RQ 1 Do nonprofit organisations which have a Hierarchy culture have a stronger IT support than nonprofit organisations which have an Adhocracy culture? RQ 2 Do nonprofit organisations which have a centralised organisational structure have a stronger IT support than nonprofit organisations which have decentralised organisational structure? RQ 3 Do nonprofit organisations which have a stronger IT support have a higher value of Human Capital than nonprofit organisations which have a less strong IT support? RQ 4 Do nonprofit organisations which have a stronger IT support have a higher value of Structural Capital than nonprofit organisations which have a less strong IT support? RQ 5 Do nonprofit organisations which have a stronger IT support have a higher value of Relational Capital than nonprofit organisations which have a less strong IT support? In order to investigate the research questions, measurements for IC were developed which were linked to the main KM processes. The final KM/IC model contained four items for evaluating human capital, five items for evaluating structural capital and four items for evaluating relational capital. The research questions were investigated through empirical research using a case study approach with the focus on two nonprofit organisations providing trade promotions services through local offices worldwide. Data for the investigation of the assumptions were collected via qualitative as well as quantitative research methods. The qualitative study included interviews with representatives of the two participating organisations as well as in-depth document research. The purpose of the qualitative study was to investigate the factors of the KM infrastructure (organisational culture, organisational structure, IT support) of the organisations and how these factors were related to each other. On the other hand, the quantitative study was carried out through an online-survey amongst staff of the various local offices. The purpose of the quantitative study was to investigate which impact the level of IT support, as the main instrument of the KM infrastructure, had on IC. Overall several key themes were found as a result of the study: • Knowledge Management and Intellectual Capital were complementary with each other, which should be expressed through measurements of IC based on KM processes. • The various factors of the KM infrastructure (organisational culture, organisational structure and level of IT support) are interdependent. • IT was a primary instrument through which the different KM processes (creating, storing, sharing and applying knowledge) were performed. • A high level of IT support was evident when participants reported higher level of IC (human capital, structural capital and relational capital). The study supported previous research in the field of KM and replicated the findings from other case studies in this area. The study also contributed to theory by placing the KM research within the nonprofit context and analysing the linkage between KM and IC. From the managerial perspective, the findings gave clear indications that would allow interested parties, such as nonprofit managers or consultants to understand more about the implications of KM on OP and to use this knowledge for implementing efficient and effective KM strategies within their organisations.

Key organizational elements for effective information and knowledge management

Effective information and knowledge management (IKM) is critical to corporate success; yet, its actual establishment and management is not yet fully understood. We identify ten organizational elements that need to be addressed to ensure the effective implementation and maintenance of information and knowledge management within organizations. We define these elements and provide key characterizations. We then discuss a case study that describes the implementation of an information system (designed to support IKM) in a medical supplies organization. We apply the framework of organizational elements in our analysis to uncover the enablers and barriers in this systems implementation project. Our analysis suggests that taking the ten organizational elements into consideration when implementing information systems will assist practitioners in managing information and knowledge processes more effectively and efficiently. We discuss implications for future research.

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.