Analysing clusters of skills in R&D — core competencies, metaphors, visualization, and the role of IT

Abstract

Introductionhis paper is about the relationship between core competencies and R&D strengths, and the way in which this relationship may be addressed systematically. IT can help by making it possible to analyse quite large volumes of data apparently objectively. But to be effective, it needs to be supplemented by metaphors and visualizations.We start by exploring the relationship between the relatively recent theory of core competencies and the practice of technology management. We show that the theory has strong implications for R&D. Core competencies, technology and R&DWhile there is a substantial literature dealing with technology management, concerted attempts to delineate clearly technology management appear to be R&D Management 28, 1, 1998.Though it is now universally accepted that companies should try to align their R&D activities with their business objectives, achieving this alignment is notoriously difficult in practice. The rise of the core competence framework has been very helpful in creating, and legitimizing, a language in which issues of technical competence and R&D strengths can be followed through to their consequences for competitive advantage. Companies are starting to express their R&D priorities explicitly in terms of core competencies. Without effective IT support, core competence concepts are often applied arbitrarily. This has led to accusations that core competence theory can become yet another battlefield upon which companies play out their internal political battles. Computer-based techniques can help counteract this danger by enabling large volumes of relatively objective data to be collected, then making it possible to analyse and draw out patterns from this data, and finally enabling the data to be represented effectively.It is in this last area of data representation that information technology is now of particular benefit. In order to make the core competence approach sufficiently robust as a basis for decision making, it is necessary to collect and process large volumes of data. However, this data is normally difficult to represent in such a way that managers can assimilate it. In our recent experience, we have come to realize the particular importance of effective representations and metaphors, and have started to shift our own emphasis towards these areas in addition to analysis per se.The paper shows how core competence approaches can support R&D management decision making by exploring the roles of data collection, analysis and representation. Information technology is an integral part of these approaches, and we draw out some generalized lessons for the successful use of IT in decision support.

Diagnosing capabilities in family firms: An overview of visual research methods and suggestions for future applications

“…The competence concept in fact remains at an abstract level, leaving practitioners without clear guidance for the application stage (Javidan, 1998;Klein, Gee, & Jones, 1998;Mills et al, 2002;Tampoe, 1994;Walsh & Linton, 2001). Clark (2000) and Vaitkevičius (2006) further suggest that small businesses have a tendency to approach competence identification from an informal perspective, and lack the instruments to develop their strategic architecture.…”

“…Alternatively, the competence graphic may represent supportive relations, e.g. by depicting competences as a series of interlinked nodes, forming a network structure (Klein et al, 1998). The competence visualization may emphasize the temporal dimension, by relating competences either in a linear, or in a cyclical manner.…”

“…The skill network by Klein et al (1998) enables an organization and its members to understand competences as a network of interrelated skills. It allows them to visualize the dynamics whereby skills flow through an organization to create a product advantage.…”

“…In this regard, the visual scheme emphasizes supportive relations among skills, and serves the purpose to allocate or communicate competence data across the entire organization. According to Klein et al (1998), while numeric data can easily lead to detail views, the corresponding visualization can convey the big picture, and build up greater commitment.…”

“…Competence Architecture (Mills et al 2002) Technology Roadmap (Phaal et al 2003) Skill Network (Klein et al 1998) …”