Knowledge cubed: Performance management with the NIMCube PMS

Successful product development is an assumed function of an organisation’s ability to make efficient use of existing knowledge together with its effectiveness in creating new knowledge. The management and measurement of these capabilities requires new methods and systems. Norman Roth Juan Prieto David Pilarek and Stephen Evans describe a performance management system that tries to satisfy this need.

The systematic use of measurement frameworks for performance control can be traced back to the beginning of the 20th century. The DuPont System of Financial Control developed in 1919 by US-based DuPont de Nemours and Co. for instance arranged a set of financial measures culminating in return on investment (Christ 1999). In 1951 General Electric planned a system of partly non-financial measures (Eccles and Noriah 1992) while French companies began working with the renowned Tableaux de Bord in 1959 (Weber and Schäffer 1998). Throughout the 1980s and 1990s interest in performance management rocketed. (Keegan et al 1989) built a balanced performance matrix (Lynch and Cross 1991) composed the Performance Pyramid and (Fitzgerald et al 1991) reflected on means-end relations in measurement frameworks. In 1992 (Kaplan and Norton 1992) introduced the Balanced Scorecard concept more often equated with performance measurement today (Klingebiel 1999). Others enforced an explicit focus on knowledge measurement (Edvinsson and Malone 1997) (Sveiby 1997) (North et al 1998) whereas (Kerssens-van Drongelen 1999) put emphasis on determination of R&D performance. Recently (Neely and Kennerley 2000) presented the innovative stakeholder-centred Performance Prism.

However these academic and industrial efforts cannot satisfy several of the major problems inherent with knowledge-sensitive performance management and measurement today.

Only few performance management systems (PMS) deliberately focus on the early knowledge-intensive phases of product development (Kerssens-van Drongelen 1999) (Kaplan and Norton 1996).
Even though some current PMS cascade measures down from strategic to operational levels (Pritchard 1990) alignment of daily process control and strategic control is deemed insufficient (Säubert 1998) (Kaplan and Norton 1996).
Notwithstanding the awareness of financial and non-financial indicators an extension of measurement to efficiency and effectiveness of knowledge application let alone the critical balance between knowledge reuse and invention seems not to be forthcoming (Sveiby 2000) (Amidon 2000) (Evans 2000).

In the following section we present a reuse- and invention-sensitive performance management framework the NIMCube PMS which draws on the strengths of the current systems and resolves identified shortcomings.

The NIMCube PMS

The approach integrates three modules: a performance management methodology and model a reuse and invention measurement catalogue and a performance management infrastructure (PMI). These modules are embedded within an innovative software solution.

The PMS builds on an infrastructure composed of reuse and invention assets (Röhrborn et al 2000) (Prenninger et al 1999). These are associated with the distinct phases of a product development process. Thus as opposed to systems such as the Balanced Scorecard the Performance Pyramid etc. it is explicitly focused on product development. It thereby supports strategic and operational performance measurement. With knowledge being the focal point the NIMCube PMS allows for an assessment of the organisational knowledge reuse and invention flows. This not only complements but also enhances traditional product-centred measurement approaches. The desire is that companies applying the NIMCube PMS are more likely to use their existing knowledge assets more efficiently to create new knowledge purposively and eventually increase competitiveness.

The performance management methodology and model

The integration of operational process-oriented control in early product development phases and prospective strategic management requires a multi-dimensional approach. We address this requirement by utilising the three-dimensional set-up of a cube. The facets of such a cube incorporate the measurement perspectives of the NIMCube PMS. The rationale behind this approach is a commonly used definition of innovation (Dvir et al 2000):

innovation = (reuse of knowledge + invention of knowledge) x exploitation.

This equation then suggests labelling the six measurement perspectives of the cube as follows: exploitation enabling context stakeholder contributions NPD performance reuse and invention. In adjusting the measurement cube to the characteristics of a user organisation it is recommended that these six facets are customised to fit the organisation as closely as possible. The application of a cube obviously allows for an extension of the classical measurement of input-output relations (i.e. stakeholder contributions and NPD performance) to dimensions such as reuse invention enabling context and exploitation. Understanding product development as a knowledge-intensive system aids the diligent management of reuse and invention processes and goes beyond traditional measurement and control of process productivity. The idea of a measurement cube renders a three-dimensional navigation functionality: it covers the product development process along the horizontal dimension disseminates measures through the organisation down the vertical dimension and finally spreads measures across functional interfaces on the spatial dimension.

The six measurement facets as well as the navigation scheme are sufficiently generic to support user-specific customisation. We will therefore provide a brief description of each measurement facet and its purpose in the following section. A discussion of the three-dimensional navigation scheme complements the introduction of a methodology and model and arranges for presentation of the second module; the reuse and invention measurement catalogue.

Exploitation – the difficulty of highly innovative and creative development on the one hand and its conversion into marketable products on the other is likely to be settled by an early identification and communication of concrete market requirements. The quantifiable contribution of product development to commercial success is reflected on the exploitation facet.
Enabling context – this facet describes and measures the setting and context within which product development is executed. This includes the determination of available capabilities and potentials as well as their realisation and deployment. The enabling context comprises innovation-friendly people management supportive information technology adaptive organisational structures and last but not least the social political and competitive environment.
Stakeholder contributions – since the work of (Freeman 1984) growing attention has been paid to a stakeholder-oriented approach to management. Stakeholders not only pose particular demands on product development but also contribute deliberately to successful innovation (e.g. co-development with key suppliers). This facet captures and quantifies the distinct involvement of stakeholders in product development processes. Typical stakeholders are for instance corporate management internal disciplines and processes suppliers regulators and above all the employees and the customers.
NPD performance – this measurement perspective reflects the (output) accomplishment of a product development process. The facet provides traditional monetary indicators as well as other measures such as throughput time and quality.
Reuse – this facet quantifies the reuse of knowledge. The measurement and evaluation typically follows a generic reuse and invention process (Roth et al 2000). Major emphasis is put on fulfilment of the knowledge reuse and invention processes in order to balance the three items of the innovation equation: reuse invention and exploitation.
Invention – the modification of existing knowledge (ideas) or the creation of new knowledge from scratch and an essential component of any innovation process. The invention facet describes organisational and individual creativity. Invention and reuse leverage each other as they regularly interact.

The six measurement facets make allowances for the complexity of product development processes they support the required knowledge orientation of performance management and address the delicate balance between efficient reuse and creative invention of knowledge.

It is assumed that multi-dimensional navigation functionalities along process phases through organisational structures and across functional interfaces are a success factor for a comprehensive performance management system. In particular for interdisciplinary product development it is essential to add a navigation dimension capturing these functional overlaps and interactions. The architecture of the measurement cube realises this as follows:

Horizontal navigation – a generic product development process (for example Ulrich and Eppinger 1995) lies behind the NIMCube PMS which can be customised to the very specific needs of a company. Moving the measurement cube along this process and selecting indicators and metrics qualified for the distinct process step gives way to a purposive view of the process step. The use of a general development process allows the possibility of adjusting the model to company-specific characteristics and finer details.
Vertical navigation – the navigation through organisational structures is brought about by means of designate views on the measurement facets. The measurement cube may for example reflect indicators and metrics for corporate management for product development project teams as well as for an individual engineer.
Spatial navigation – the third dimension supports the presentation of measures reflecting the typical cross-functional aspects of product development.
The reuse and invention measurement catalogue.

A comprehensive repository of indicators and metrics is at the root of the measurement facets. As these measures are coherently connected with each other they realise the principle of cause-and-effect relations as for example required by (Kaplan and Norton 1996). The measurement catalogue is assumed to be unique as it combines conventional measures (for instance return on investment) with explicit measures of knowledge reuse and invention (for example proportion of reused assets within a product). Furthermore it adds the description of external influential factors (for instance competitive concentration) and the involvement of stakeholders (for example co-operation with key customers in concept development). The broad range of measures is provided in a high-level reference catalogue to enable the user-specific selection of indicators and metrics. The calculation documentation visualisation and interpretation of the selected measures are facilitated by means of an indicator record integrated in the software solution.

The performance management infrastructure

The performance management methodology and model as well as the reuse and invention measurement catalogue are firmly entrenched within a performance management infrastructure (PMI) composed of reuse and invention asset models. These models are constructed by documenting those specific knowledge assets relevant to the process step (for example a design drawing a patent etc.) and by linking the assets in a logical context (Röhrborn et al 2000) (Prenninger et al 1999). These configurations can then be assigned to designate phases of the development process. The single assets are described referenced and stored by a set of characteristics:

Metadata – provides a qualitative description of the asset (for instance name of the engineer date of conceptualisation etc.) (Röhrborn et al 2000).
Relations – describe the context and implications of the reuse and invention assets (Röhrborn et al 2000). These relations allow for connecting the assets for running efficient asset searches and for purposive application of selected components.
Indicators – supply specific and real-time information on the reuse and invention assets. These attributes are assumed to be vital against the background of ensuring dynamism and adaptability of the model (for example replacement of obsolete assets through new assets). We distinguish two basic categories of indicators: standard operational (task) indicators which are assigned to every reuse and invention asset of the PMI and standard management indicators which refer to distinct asset types.

The software solution

All three NIMCube PMS components are integrated within a software solution (NIMSoft). The three different navigation axes are implemented on an explorer-like basis. The main screen shows the six facets of the unfolded Measurement Cube and the metrics for each of the facets. The overriding principle is the clear and visible implementation of the six measurement facets and of the three navigation axes.

The major functionalities of the NIMCube software are described in the following listings.

Functionalities concerning the PMI:

Visualisation retrieval storage classification dissemination creation of reuse and invention assets
Community of practice support
Metadata administration
Context representation
Push/pull mechanisms
Provision of assets-oriented metrics.

Functionalities concerning the measurement model:

Cascaded representation of the measurement model with the six facets
Classified metric catalogue
Three axes navigation structure
Automatic report generation
Cockpit functionality (dashboards)
Aggregation of metrics with weights
Assign and maintain metric to measurement level
Design and run a NIMMeasure usage report.

Outlook

We have introduced a performance management system focused on knowledge reuse and invention in the context of product development. NIMCube PMS consists of a methodology and reference model a reuse and invention measurement catalogue and a performance management infrastructure. The three modules integrate with an innovative software solution. This arrangement allows building on current frameworks meeting the need for reuse- and invention-sensitive performance management.

The NIMCube PMS originates from the European NIMCube project sponsored by the EC’s IST programme. The NIMCube project works with diverse complementary activities in order to raise awareness of knowledge management in product development. Interested organisations have become members of our Business Support Group allowing for active involvement in the project and immediate benefit from its outcomes.

Acknowledgements

This work is co-sponsored by the European Commission through the IST Project No. 11926 NIMCube: New-use and Innovation Management and measurement methodology for R&D. The authors wish to thank the Commission for its support. We also wish to acknowledge our gratitude and appreciation to all the NIMCube project partners for their contribution during the development of various ideas and concepts presented in this paper.

References

1. Amidon D. ‘The great gurus on new use and innovation’ in NIMCube Consortium: D1.2/1.3 Domain Knowledge Collection and Best Practice in New-use and Innovation Management: WP 1 Requirements Engineering & Knowledge Acquisition – Task 1.2/1.3 Research State of the Art and Industrial Practice (Stuttgart 2000)
2. Christ O. Wissensorientierte Führung (Universität St. Gallen – Hochschule für Wirtschafts- Rechts- und Sozialwissenschaften St. Gallen 1999)
3. Dvir R. Pasher E. Evans S. Roth N. and Prieto J. ‘How to manage the balance between new-use and innovation in R&D processes’ in 3rd European Project Management Institute (PMI) Conference Proceedings (Jerusalem 2000)
4. Eccles R.G. Noriah N. and Berkley J. D. Beyond the Hype – Rediscovering the Essence of Management (Boston 1992)
5. Edvinsson L. and Malone M. Intellectual Capital: Realizing Your Company‘s True Value by Finding Its Hidden Brainpower (New York 1997)
6. Evans S. ‘The great gurus on new use and innovation’ in NIMCube Consortium: D1.2/1.3 Domain Knowledge Collection and Best Practice in New-use and Innovation Management: WP 1 Requirements Engineering & Knowledge Acquisition – Task 1.2 / 1.3 Research State of the Art and Industrial Practice (Stuttgart 2000)
7. Fitzgerald L. Johnston R. Brignall T.J. Silvestro R. and Voss C. Performance Management in Service Businesses (The Chartered Institute of Management Accountants London 1991)
8. Freeman R. E. Strategic Management: A Stakeholder Approach (Boston 1984)
9. Kaplan R. and Norton D. ‘The balanced scorecard – Measures that drive performance’ in Harvard Business Review (No.1 1992)
10. Kaplan R. and Norton D. The Balanced Scorecard – Translating Strategy into Action (Boston 1996)
11. Keegan D.P. Eiler R.G. and Jones C.R. ‘Are your performance measures obsolete?’ in Management Accounting (No.12 1989)
12. Kerssens-van Drongelen I. C. Systematic Design of R&D Performance Measurement Systems (Thesis University of Enschede 1999)
13. Klingebiel N. Performance Measurement Grundlagen – Ansätze – Fallstudien (Wiesbaden 1999)
14. Lynch R.L. and Cross K.F. Measure Up – The Essential Guide to Measuring Business Performance (London 1991)
15. Neely A. and Kennerley M. ‘Performance measurement frameworks – A review’ in Neely A. (ed.) Performance Measurement – Past Present and Future (Cambridge 2000)
16. NIMCube Consortium: D4.1 Functional Specification: WP4 Development of the 1st SW prototype – Task 4.1 Functional Specification of the 1st prototype (Stuttgart 2000)
17. NIMCube Consortium: D4.2 SW Platform decision document: WP 4 Development of the 1st SW prototype – Task 4.2 SW Platform decision (Stuttgart 2000)
18. North K. Probst G. and Romhardt K. ‘Wissen messen – Ansätze Erfahrungen und kritische Fragen” in Zeitschrift für Organisation (Nr.3 1998)
19. Prenninger J. Polterauer A. Prieto J. and Röhrborn D. ‘MaKe-IT SME – Managing of knowledge using integrated tools’ in 5th International Conference on Concurrent Enterprising Proceedings (Le Hague 1999)
20. Pritchard R.D. Measuring and Improving Organizational Productivity – A Practical Guide (New York 1990)
21. Röhrborn D. Hauß I. and Prieto J. ‘Modellbasiertes Wissensmanagement im Intranet und Internet’ in KnowTech 2000 Knowledge Engineering Management Consulting & Training Tagungsband (Leipzig 2000)
22. Roth N. Prieto J. Dvir R. and Evans S. ‘An integrated framework for new-use and innovation measurement and management’ in Neely A. (ed.) Performance Measurement – Past Present and Future (Cambridge 2000)
23. Roth N. Prieto J. and Pilarek D. ‘Ein Performance-Measurement-System für wissensintensive Produktentwicklungsprozesse’ in IO Management (No. 1/2 2001)
24. Säubert H. ‘Die Generierung von Steuerungsgrössen für die Erfolgsmessung von Wissensmanagement’ in IO Management (No.10 1998)
25. Sveiby K.-E. The New Organizational Wealth: Managing and Measuring Knoweldge-Based Assets (San Francisco 1997)
26. Sveiby K.-E. ‘The great gurus on new use and innovation’ in NIMCube Consortium: D1.2/1.3 Domain Knowledge Collection and Best Practice in New-use and Innovation Management: WP 1 Requirements Engineering & Knowledge Acquisition – Task 1.2 / 1.3 Research State of the Art and Industrial Practice (Stuttgart 2000)
27. Ulrich K.T. and Eppinger S.D. Product Design and Development (New York 1995)
28. Weber J. and Schäffer U. Balanced Scorecard – Gedanken zur Einordnung des Konzepts in das bisherige Controlling Instrumentarium Forschungspapier Nr. 60 (WHU Koblenz Vallendar 1998)

Norman Roth can be contacted at: norman.roth@iao.fhg.de
Juan Prieto can be contacted at: juan.prieto@iao.fhg.de
David Pilarek can be contacted at: david.pilarek@iao.fhg.de
Stephen Evans can be contacted at: steve.evans@cranfield.ac.uk