Industrial Research Performance Management: Key Performance Indicators in the ICT Industry: Contributions to Management Science
Autor Tatjana Samsonowaen Limba Engleză Paperback – 28 ian 2014
almost no research has focused explicitly on the performance measurement of research activities, or indeed tried to develop a systematic approach to setting KPIs for specific research goals.
This work, in co-operation with ABB Research, Deutsche Telekom AG Laboratories, EMC2 Advanced Technology Solutions, IBM Research, Intel Research, Microsoft Research,
Philips Research, and SAP Research, develops a systematic approach to performance measurement for industrial research organizations in innovation-driven companies.
The following questions are addressed:
(1) Which research goals do research departments have?
(2) Which KPIs do they use to monitor the achievement of these goals?
(3) Is there a systematic best-practice approach to selecting KPIs for performance goals?
The outcome is a complete set of eleven performance clusters, such as the transfer of research results to the development or other organizational departments, and each cluster has its own set of KPIs. The eleven clusters are: Technology Transfer, Future Business Opportunities, Technical Achievements, Intellectual Property, Operational Excellence, Talent Pool, Image, Publications, Presence in Scientific Community, Collaboration with Academia, Collaboration with Partners and Customers.
This work led to the creation of the Institute for Industrial Research Performance Management that provides ongoing research and insights for managers of industrial research organizations.
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Specificații
ISBN-13: 9783790829297
ISBN-10: 3790829293
Pagini: 476
Ilustrații: XII, 464 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.66 kg
Ediția:2012
Editura: Physica-Verlag HD
Colecția Physica
Seria Contributions to Management Science
Locul publicării:Heidelberg, Germany
ISBN-10: 3790829293
Pagini: 476
Ilustrații: XII, 464 p.
Dimensiuni: 155 x 235 x 25 mm
Greutate: 0.66 kg
Ediția:2012
Editura: Physica-Verlag HD
Colecția Physica
Seria Contributions to Management Science
Locul publicării:Heidelberg, Germany
Public țintă
Professional/practitionerCuprins
Performance Management.- State-of-the-art in Performance Management.- Performance Management - Analysis Approach.- Survey Findings.- Towards a Systematic Performance Management Approach for Industrial Research in the ICT Industry.
Textul de pe ultima copertă
Managers are increasingly concerned with the typical methods available for organizational performance measurement and control. Research into performance measurement, within the field of innovation management, has been variously approached through frameworks for performance measurement in general (for example, the Balanced Scorecard by Norton and Kaplan), R&D performance management, and surveys on in-use Key Performance Indicators (KPIs). It is striking, however, that
almost no research has focused explicitly on the performance measurement of research activities, or indeed tried to develop a systematic approach to setting KPIs for specific research goals.
This work, in co-operation with ABB Research, Deutsche Telekom AG Laboratories, EMC2 Advanced Technology Solutions, IBM Research, Intel Research, Microsoft Research,
Philips Research, and SAP Research, develops a systematic approach to performance measurement for industrial research organizations in innovation-driven companies.
The following questions are addressed:
(1) Which research goals do research departments have?
(2) Which KPIs do they use to monitor the achievement of these goals?
(3) Is there a systematic best-practice approach to selecting KPIs for performance goals?
The outcome is a complete set of eleven performance clusters, such as the transfer of research results to the development or other organizational departments, and each cluster has its own set of KPIs. The eleven clusters are: Technology Transfer, Future Business Opportunities, Technical Achievements, Intellectual Property, Operational Excellence, Talent Pool, Image, Publications, Presence in Scientific Community, Collaboration with Academia, Collaboration with Partners and Customers.
This work led to the creation of the Institute for Industrial Research Performance Management that provides ongoing research and insights for managers of industrial research organizations.
y>
almost no research has focused explicitly on the performance measurement of research activities, or indeed tried to develop a systematic approach to setting KPIs for specific research goals.
This work, in co-operation with ABB Research, Deutsche Telekom AG Laboratories, EMC2 Advanced Technology Solutions, IBM Research, Intel Research, Microsoft Research,
Philips Research, and SAP Research, develops a systematic approach to performance measurement for industrial research organizations in innovation-driven companies.
The following questions are addressed:
(1) Which research goals do research departments have?
(2) Which KPIs do they use to monitor the achievement of these goals?
(3) Is there a systematic best-practice approach to selecting KPIs for performance goals?
The outcome is a complete set of eleven performance clusters, such as the transfer of research results to the development or other organizational departments, and each cluster has its own set of KPIs. The eleven clusters are: Technology Transfer, Future Business Opportunities, Technical Achievements, Intellectual Property, Operational Excellence, Talent Pool, Image, Publications, Presence in Scientific Community, Collaboration with Academia, Collaboration with Partners and Customers.
This work led to the creation of the Institute for Industrial Research Performance Management that provides ongoing research and insights for managers of industrial research organizations.
y>
Caracteristici
Five-level Performance Management Model Recommendations and guidelines for the development of a Performance Management System 8 case studies of ICT companies, where more than 70 personal interviews with senior decision makers were made Database of 30 organizational research goals,11 performance clusters,37 KPI classes and 164 different key performance indicators Includes supplementary material: sn.pub/extras