Search Focus and Sources of Innovation

Chapter 4 delineated distant knowledge along six dimensions. The purpose of the theoretical review was to arrive at a finer definition of what constitutes knowledge bridging organizational and other boundaries.

In addition to being characterized by a high degree of uncertainty and tacitness, knowledge distance is manifest in terms of geography as well as various contextual factors. In general, knowledge which displays high values in these dimensions entails higher innovation potential. However, high values also make it difficult to reconcile such knowledge with the present context. Conversely, local, close knowledge is easier to understand and utilize yet contains less innovation potential. This may seem like an obvious insight, however, it seems that the degree of distance, the intended innovation outcome, and the present technology/product/market context is rarely considered in combination, neither by academia nor practitioners. Matching the nature of knowledge to be integrated and the mechanism to achieve it seems to be equally neglected. The cases seem to confirm this proposition.

PATYO’s search locus is aligned with its mission of finding and transferring key non-automotive trends.

Silicon Valley represents an ideal location in the sense that it represents the most progressive area in the fields of IT and electronics. Particularly those fields have already begun to be integrated into cars and represent an area of considerable car-related progress. Due to the fact that some extent of convergence between mechanical engineering, mechatronics and IT applications already exists, technological distance is relatively moderate. Thereby, while still retaining considerable potential for innovation, the search focus allows for integration of the transferred knowledge. PATYO therefore strikes a good balance between knowledge distance and innovative performance, as illustrated in figure 46.

VIA, on the other hand, opens a channel to virtually anyone with the means of submitting ideas electronically or through ordinary mail. Although an initial search focus was limited to small- and medium sized companies from outside the industry, the choice of search mechanisms, a universally accessible website, there is little scope for enforcing this search focus³⁹. There is thus, a lack of alignment with

39 The intention of attracting primarily small and medium sized companies was stated on the start page of the portal.

Formal proof of such status, however, was not required.

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corporate and innovation strategy with the ideas entering through VIA. In addition, the content of ideas is highly heterogeneous in terms of content, creating challenges for the limited resources of the impulses team to translate, transform, and match ideas with internal centers of competence. With regard to the position on the inverted-U of optimum knowledge distance and innovation performance, VIA would therefore be located on the descending slope of the inverted U characterizing the relationship between knowledge distance and innovative performance.

Whereas VIA may have reached out considerably beyond its ability for matching and integration of distant knowledge, the opposite seems to be the case for Webasto. It reaches out to the least distant and novel sources in the case sample. The greatest deviation from the current knowledge base consists of cognitive distance, since the individuals tapped for ideas have a high product usage/customer-centric perspective.

This also means that these lead users may find it difficult to articulate their ideas, a problem prominently discussed in the lead user literature (e.g. von Hippel, 2005). In order to articulate those tacit ideas, intensive workshops become necessary. However, due to the otherwise low knowledge distance, the yield in terms of innovative potential seems to be rather small. Therefore, the knowledge distance fails to correspond to the strategic goals and expectations vested in the lead-user process. This finding would lend support to Ron Boschma’s (2005) assertion that too little distance may inhibit innovation due to lock-in, conversely, too much distance may prohibit incorporation of novel knowledge. Both extremes can be seen in the VIA and Webasto case, respectively, whereas PATYO seems to have managed to strike a balance between distance and matching ability. Figure 46 illustrates the aspects discussed⁴⁰:

40 Figure 46 shows means and standard deviation of the different subjectively assigned values in the different knowledge dimensions. This is not intended to ascribe the values any statistical significance. Rather, it is intended to illustrate the overall degree of distance as an average of all dimensions included in the radar chart as well as the variance between the different values assigned to the dimensions.

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Figure - 46 Cross-Case Comparison of Knowledge Distance

PATYO

•Provides balanced Knowledge Distance

•High innovative potential yet still compatible with central R&D

•Geographic Distance very high but addressed through frequent rich communication

VIA

•Knowledge sources highly heterogenous

•Mean Distance moderate to high , complicating integration

Webasto

•Knowledge Distance very low

indicating limited innovation potential

•Proximity indicates low difficulty for integration

Innovation Performance

Distance

Innovation Performance

Distance

Innovation Performance

Distance

Mean=3 SD=1.1

Mean=3.3 SD=0.5

Mean=1.3 SD=0.6 Mean=3.3 SD=1

SD= Standard Deviation

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Based on this snapshot of the three cases, one might deduce that the knowledge to be tapped in distant knowledge search and transfer processes needs to be aligned with the strategic intent behind it, as well as with the mechanisms and processes enabling this transfer. Only in the case of PATYO strategic goals which are translated into concrete search criteria are aligned with the search focus and the mechanisms for accessing it. Moreover, the nature of knowledge tapped needs to strike the right balance in terms of providing novelty and enabling matching with existing capabilities. Interestingly, in the case of VIA, there is an “overload” of distant knowledge, whereas at Webasto, search is too close-by the existing context, therefore allowing for little scope for innovation.