Using a balanced scorecard approach to enhance the management of knowledge transfer partnerships

This source preferred by Martyn Polkinghorne

Authors: Manville, G., Petford, N. and Polkinghorne, M.

Start date: 4 September 2008

This data was imported from Scopus:

Authors: Polkinghorne, M., Manville, G. and Petford, N.

Journal: Proceedings of the European Conference on Knowledge Management, ECKM

Pages: 667-674

eISSN: 2048-8971

ISBN: 9781905305537

ISSN: 2048-8963

This paper considers the delivery of government funded Knowledge Transfer Partnerships (KTP), and the need to ensure that the knowledge being transferred is based upon Deep Smarts. To this aim it is proposed that an Intellectual Capital Audit (ICA) is undertaken at the start of each KTP, and again at regular points during the active life of each project, so that the successful engagement of Deep Smarts (the deepest knowledge and understanding held by experts) can be measured and monitored. As Deep Smarts are considered to be observable phenomena, a methodology is proposed that takes a Value Measurement approach using a balance scorecard. The balanced scorecard was developed as a simple form of strategic management. Its strength and utility lie in its ability to relate vision and strategy to four key business functions: financial, customers, internal business processes, learning & growth, and to reveal any causal links between them. The balanced scorecard is well suited to an ICA of Deep Smarts as it provides a quantitative solution for KTP measurement during its active phase. More importantly, it also offers a mechanism for forecasting the progress of the KTP, resulting (in principle) in higher levels of future performance. Because Deep Smarts themselves are very difficult to define, and therefore almost impossible to identify and monitor, a process is required to determine the consequential beneficial attributes that would result from the successful use and transfer of Deep Smarts. It was considered that monitoring changes within these the consequential beneficial attributes would provide a direct indication of successful knowledge transfer being achieved, and would also provide an indication of the level of Deep Smarts exploitation on an on-going basis. Although the optimal solution would be to consider such consequential beneficial attributes for both university and company partners, it was the purpose of this research to concentrate on those relating to only the university in the first instance. A generic balanced scorecard ICA of Deep Smarts applicable for KTPs was therefore developed as a tool that could be employed to determine the consequential beneficial attributes relating to the successful transfer and deployment of Deep Smarts within the delivery of a Knowledge Transfer Partnership.

This data was imported from Web of Science (Lite):

Authors: Polkinghorne, M., Manville, G. and Petford, N.

Journal: PROCEEDINGS OF THE 9TH EUROPEAN CONFERENCE ON KNOWLEDGE MANAGEMENT

Pages: 667-+

ISBN: 978-1-906638-10-8

The data on this page was last updated at 05:09 on February 20, 2020.