Discovering the factors impacting the evaluation of knowledge management in the organizational domain

The knowledge, skills and experience possessed by employees, customers, suppliers and other stakeholders are major components of an organization\u27s Intellectual Capital, the effective management of which has been found to be critical for business success. In order to manage knowledge at an organizational level however, it is necessary to be able to define it in the context of the organization, measure its existence and, more importantly, assess how its creation, use, dissemination, evaluation and management impacts business performance and learning. Whilst the term Knowledge Management has evolved since the early nineties into a generally recognisable management discipline in its own right, significant literature over the past eight years has focussed on the management of knowledge as a more generic organizational competence making Knowledge Management Initiatives difficult to identify and define and even more difficult to evaluate. Despite the challenges, the subjects of knowledge management and intellectual capital are gaining strategic management exposure particularly in relation to how investment in, and outputs from, these initiatives can or should be evaluated. Knowledge management and intellectual capital are inextricably related, and whilst some previous research has gone into evaluating knowledge as an extension or derivative of information and into intellectual capital as a discrete item on the balance sheet, little has been done to analyse the development of models that attempt to evaluate the impact of knowledge management as an organizational process or capability. A comprehensive meta-analysis by literature review of international articles dealing with knowledge management and intellectual capital evaluation from a broad range of business and scientific journals was undertaken to identify precisely what has been measured by public and private sector organizations within the Knowledge Management, Intellectual Capital and other closely related domains between the years 1996 to 2002. By the end of 2002, human capital based measures were found to be the most frequently quoted in KM literature. Financial, human capital, internal infrastructure and composite measures such as the Balanced Scorecard have grown in varying degrees in frequency of use, whilst customer, process, intellectual property, innovation and quality related measures have gradually lost ground compared to other metrics between 1996 and 2002. Significant differences occur in the evaluation and reporting of KM initiatives amongst the main geographic regions of North America, Europe, Scandinavia and Japan, but these differences seem to be more related to public policy differences and to management style than to a result of any definitive or deliberate differences in formal evaluation plans and methodologies. Generally, KM evaluation between 1996 and 2002 has focussed on explicit (rather than tacit), internal (rather than external) and outcome (rather than process) oriented measurement processes. Inadequate accounting systems, lack of measurement and reporting standards, lack of long-term vision and poor understanding of the contribution of knowledge to competitive advantage have been and remain major constraints to the future development of KM

HR Metrics and Strategy

[Excerpt] The idea that an organization\u27s people represent a key strategic resource is widely accepted. The business press is filled with examples of top executives proclaiming how important it is to engage people\u27s minds and spirits in the quest for competitive advantage (Boudreau & Ramstad, 1997; Boudreau, 1996). There is also mounting scientific evidence that certain bundles of high-performance work practices (e.g., performance-contingent pay, team-based work structures, selective recruitment and hiring, extensive training, etc.) are associated with higher organizational financial performance (Becker & Huselid, forthcoming; Ichniowski, Arthur, MacDuffie, Welbourne & Andrews)

Picking Investments in Knowledge Management

{Excerpt} What can be measured is not necessarily important and what is important cannot always be measured. When prioritizing investments in knowledge management, common traps lie waiting. They are delaying rewards for quick wins, using too many metrics, implementing metrics that are hard to control, and focusing on metrics that tear people away from business goals. How can investments in knowledge management be picked? This is no easy matter. What can be measured is not necessarily important and what is important cannot always be measured. Not surprisingly, despite the wide implementation of knowledge management initiatives, a systematic and comprehensive assessment tool to prioritize investments in knowledge management in terms of return on investment is not available. This owes to the difficulty of demonstrating direct linkages between investments in knowledge management and organizational performance, most of which can only be inferred, and the fact that the miscellany of possible knowledge management initiatives calls for both quantitative and qualitative approaches. This is indeed the rationale behind the Balanced Scorecard introduced by Robert Kaplan and David Norton in 1992, whose qualities make it quite useful as a knowledge management metric

Benchmarking performance management systems

The Balanced Scorecard and associated performance management approaches, has become a widely practiced and popular management reporting method in recent times. Moreover, enabling technology, which assists in the delivery and personalisation of corporate performance information, is having a deeper and more rapid impact than ever before. This paper presents a brief comparative benchmarking study of leading enterprise performance management systems. Also, the author discusses the merits of bespoke internet technology development and out-of-the-box portal functionalities. An analysis of key business drivers and implementation risks of such approaches is highlighted via a case study example, and concludes the paper

Strategic Human Resource Management Measures: Key Linkages and the PeopleVantage Model

The field of human resource management faces a significant dilemma. While emerging evidence, theory and practical demands are increasing the visibility and credibility of human capital as a key to organizational success, the measures used to articulate the impact of human resource management decisions remain misunderstood, unwanted by key constituents, or even counter-productive. This article proposes that the key to creating meaningful HR metrics is to embed them within a model that shows the links between HR investments and organizational success. The PeopleVantage model is proposed as a framework, the application of the model is illustrated, and the potential of the model for guiding research and practical advances in effective HR measures is discussed

The effect of organizational culture on CRM success

Copyright @ 2013 EMCIS.The aim of this paper is to develop a theoretical framework exemplifying the effect of organizational culture on the success of Customer Relationship Management (CRM) systems' implementation. This is deemed significant as yet little research has investigated the role of organizational culture as a critical success factor to CRM implementation. The proposed theoretical framework is developed based on the notion that nurturing an organizational culture that promotes adaptive learning leads to better management of customer information that in turn improves the quality of customer information, which is considered a key contributor to successful implementation of CRM initiatives. The Competing Values Framework (CVF) is used to measure "Organizational Culture" since it has proven its validity in examining the effect of organizational culture on organizational effectiveness and performance

Learning Lessons with Knowledge Audits

{Excerpt} Knowledge from evaluations will not be used effectively if the specific organizational context, knowledge, and relationships of evaluation agencies, and the external environment they face, are not dealt with in an integrated and coherent manner. Knowledge management can shed light on this and related initiatives can catalyze and facilitate identification, creation, storage, sharing, and use of lessons. Most development agencies have committed to become learning organizations. But the use of evaluation for learning may be less important than that of other inputs, such as self evaluation and training, and evaluation results may only marginally support policy, strategy, and operational changes. In 2006, the Independent Evaluation Department in the Asian Development Bank determined to apply knowledge management to lesson learning. In 2007, it formulated a strategic framework to improve the organizational culture, management system, business processes, information technology solutions, community of practice, and external relations and networking for that. These Knowledge Solutions explain the strategic framework. They also describe the knowledge audit methodology developed to tie in with the department’s audiences. The online, questionnaire-based survey of perceptions conducted as a first exercise that year provided ready and multiple entry points against which the department can take measures to that intent, as well as a comprehensive baseline assessment against which to judge progress. Fundamentally, these Knowledge Solutions contend that evaluation agencies should move from “make-and-sell,” at the simplest level, to “sense-and-respond” in ways that are increasingly satisfying to stakeholders. Knowledge from evaluations will not be used effectively if the specific organizational context, knowledge, and relationships of evaluation agencies, and the external environment they face, are not dealt with in an integrated and coherent manner. Knowledge management can shed light on possible operating frameworks for this and knowledge management initiatives can be applied to catalyze and facilitate identification, creation, storage, sharing, and use of lessons. That would be knowledge utilization indeed

Multiple case-study analysis of quality management practices within UK Six Sigma and non-Six Sigma manufacturing small- and medium-sized enterprises

This paper examines multiple case-study analysis of quality management practices within UK Six Sigma and non-Six Sigma manufacturing small- and medium-sized enterprises