As is clear from Table 1, analysis and experimentation account for about 77% of the activity pattern of the designers and developers involved in product design and development. Sofar, we have largely neglected the organisation of these 77% in the context of new product development. If we want to arrive at a more effective and efficient design and development process, we thus will have to better handle and understand the management of ‘analyses and experiments.’ In a very interesting paper, Eisenhardt and Tabrizi (1995) argue that in complex new product development projects (i.e. projects marked by high levels of ambiguity), traditional project management approaches fail and should be replaced by experiential project management, consisting of a rapid sequence of design-build-test-redesign cycles in which the subsequent users of the product can be deeply involved.

This finding is precisely at the heart of the argument made in this contribution: in situations marked by high levels of ambiguity, when defining and designing a product’s form to fit the context of use, we have to bring in modes of managing new product design and development that explicitly recognize the value and the contribution of experimentation and analysis. This implies we arrive at ‘intelligent’ experimentation strategies that move beyond ‘mere’ trial and error experimentation. This is where the integrated design capability, combining design methods, design technologies and organizational approaches, enters as a new focus in product development organization, not in the least because of increased pressures on speed-to-market, shortening product life cycles and rapid erosion of design advantages due to intense competitive rivalry in new product design.

It is therefore an important finding that design technologies (I tend to call them meta-technologies or ‘technologies to develop technology’) add a new dimension to the management of the new product development process as they explicitly allow to better control cycles of experimentation in product definition and design given their ability to cope with both ambiguity and uncertainty. Ambiguity is thereby linked to reducing differences in interpretation on the product form and design (for instance, on the definition of the relevant space of functional parameters), while uncertainty is linked to arriving at acceptable target values for the chosen functional parameters via the reduction of information asymmetries on the context of use of the product.


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Design Management
VIZO Workshop

“Design makes the Difference”
Brussels, Belgium - 29/30 November 2002

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