Increasingly we are being required to justify the expenditure on innovation. How effective is it? Does it meet the organisation' s objectives? What is the return on the investment? There is very little doubt that justification of expenditure on innovation is necessary, just like any other element of organisational expenditure. But all too often the measures that are used only provide information about past performance. They contribute very little to our understanding of why that level of performance was achieved; to our improvement of innovation practices; or to our prediction of the future value of our current innovation efforts.
Firstly, what do we mean by measures and metrics? Measurement applies to anything that has a quantifiable characteristic; a metric is a quantifiable characteristic, which one can measure against (Dimancescu and Dwenger, 1996). Metrics such as 'new sales ratio' (contribution derived from new products/services), 'R&D intensity' (spend on R&D as a percentage of sales) and 'number of patents granted' provide some insight into an organisation' s innovation performance, but it is historical. Greater benefit can be achieved from having a range of metrics that provides both forward and backward looking information. Static metrics are data gathered only after the event has occurred; dynamic metrics are real-time data feedback usually related to a goal.
Barclay et al. (2001) suggested process metrics for internal efficiency; business metrics and customer metrics for external effectiveness as shown in Fig. 8.3. Arthur D. Little (personal communication) proposed a metric suite based around the timing of the information and on specific areas of focus. They suggested that metrics be designed with a framework of time and the holistic dimension.
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