The impact of uncertainty on innovation-related decision makingmaking

There exists a wide consensus in innovation management research that uncertainty has a strong inuence on innovation-related decision making and outcomes (Tatikonda and Rosenthal 2000; Herstatt et al. 2004; Loch et al. 2008). Section 2.2.1 highlighted that uncertainty is a necessary precursor to innovation in that it creates (at least perceived)

opportunities to better meet market needs. The previous section discussed how internal and external drivers of innovation-related uncertainty often lead to a lack of information regarding the innovation object. We now aim to foster a better understanding of the impact of uncertainty on innovation-related decision making, with a particular focus on the fuzzy front-end of innovation. Only with this understanding can innovating organi-zations evaluate whether and how to address innovation-related uncertainty.

First, uncertainty can cause signicant delays in decision making at the fuzzy front-end of innovation. Stockstrom and Herstatt (2008) cite a large scale German interview study by Bullinger (1990), which reports that one-third of all product-development ef-forts are unnecessary changes that prolong project completion times. Retrospectively, the interviewed corporate managers claimed that information to avoid these wasted ef-forts was often available at the time the innovation project was initiated. Uncertainty can increase delays in highly dynamic market environments in which market and tech-nological conditions quickly change. Strong and frequent changes in the environment decrease the chances of eectively matching a given set of resources and capabilities to market needs and determining organizational requirements (Khurana and Rosenthal 1998). Organizations that are less exible in allocating resources and unwilling to exper-iment and fail will be more likely to delay innovation development in situations of high environmental uncertainty (Eisenhardt and Tabrizi 1995).

Second and more importantly, uncertainty has been closely related to the quality of evaluation during the course of innovation, i.e. the higher the uncertainty, the lower the quality of innovation-related evaluation will be (Kim and Wilemon 2002; Brun et al. 2009).

High degrees of uncertainty have been positively related to avoiding the dealing with of that uncertainty. Organizations are more likely to be able to counter uncertainty if they are suciently informed about how much time and money they must invest to reduce particular dimensions of uncertainty. In cases where uncertainty is very high, organiza-tions will often rely on existing information, which may foster ill-informed decisions. For example, uncertainty about the distribution of demand functions commonly leads com-panies to charge too little for a new product because they underestimate the innovation's additional value. Instead, they tend to focus on variable production costs to determine prices, and furthermore, neglect investments in the exclusive resources and capabilities that allowed the innovation's development (Marn et al. 2003). Similarly, uncertainty

about customers needs in changing market environments drive incumbent rms to rely on the feedback of existing customers. While this may decrease uncertainty about the demands of this particular group, it will often lead to faulty assessments if new customer groups (and needs) emerge and grow in importance (Christensen and Bower 1996).

When information gaps are still present after the evaluation process, they may prevent investment in new products even with low uncertainty regarding the potential customer benets and internal ability to meet customer needs. A recent Japanese study of the medical industry found that uncertainty with regard to long-term commitments to reg-ulatory processes during the innovation development process is a central obstacle that hinders innovations from moving from the concept- to the development-phase (Numata et al. 2010).

As a consequence,uncertainty has been negatively associated with innovation success potential (Stockstrom and Herstatt 2008).

For example, Souder (1988) found that uncertainty from lack of communication may negatively impact decision quality when selecting and pursuing innovation. In particu-lar, disharmony between marketing and R&D departments appears to have a negative inuence on innovation success potential. He concurs that disharmony prevents eec-tive communication, i.e. the ow of information that can reduce uncertainty with regard to the need-solution t. Decisions are not only delayed but are also based on insu-cient levels of information, which ultimately leads to erroneous decisions. Tatikonda and Rosenthal (2000) studied the impact of task uncertainty in new product development projects within high-tech rms. They found that higher degrees of uncertainty due to technical novelty has a signicantly negative inuence on the project success variables of time-to-market and unit-cost objective. However, they also found that technical per-formance objectives are positively associated with uncertainty due to technical novelty in new products. Companies that engage in innovation with a high degree of techno-logical uncertainty compromise new product performance by signicantly overstretching development schedules and costs. The authors argue that high-tech rms underesti-mate development performance, and more importantly, overemphasize the achievement of technological goals compared to factors that are relevant to business success.

To conclude, uncertainty can have considerably negative impact on the speed, evaluation quality, and subsequent success of innovation projects. These ndings strongly suggest that innovating organizations should actively engage in activities that help to reduce

uncertainty. Such activities may increase the quality of innovation evaluation, which appears to have positive eects on the success of an innovation undertaking.