An Agenda for Future Research on IT and Product Development - Information Technology and Product Development - page 189

10.2.3 Experimentation in Innovation
Experimentation has assumed considerable importance in recent years - both
in business in general (Davenport, 2009) and in product/service development
(Thomke, 2003). Business experimentation enable companies to test out new busi-
ness strategies and processes and make more judicious decisions regarding their
implementation. Simple frameworks have been suggested to organize such business
experiments. For example, Davenport (2009) recommends an iterative hypothesis
testing framework that organizations can employ to test out alternate solutions to
business problems before roll out.
Experimentation has become critically important in product development too as
the scope and the complexity of product development projects continues to increase
(Dahan & Hauser, 2002). However, it is also important to make such experiments
cost-effective. IT can play a key role in achieving this objective. Virtual prototyping
tools help to reduce innovation costs; more importantly, they enable companies to
engage a large set of stakeholders in concept testing activities, thereby reducing the
innovation risks as well as the time-to-market.
Experimentation in service innovation present another set of unique challenges.
As Thomke (2003) indicates it is difficult to test out new services in a traditional
laboratory setting. On the other hand, “live” tests of new services that involve
real-world customer while useful pose several risks including those related to cus-
tomer relationships and brand image. Thus, IT-based testing tools and platforms are
particularly appealing for conducting experiments in service innovation.
Several important research issues arise from this focus on experimentation and
the role IT can play in supporting it. I briefly describe two broad sets of issues here.
First, given the wide range of IT-based tools that are available - from statistical
tools to virtual reality prototyping and simulation tools - developing an understand-
ing of the characteristics of these tools is important in order to select and deploy
the right set of tools in a given context . Studies have identified a whole host of IT-
based tools for experimentation, however, there has been limited attention paid to
evaluating their effectiveness in different contexts. Future studies should focus on
developing contingency models that elaborate on the key elements of various tools
and inform on their relative effectiveness in different product development contexts.
Second, it is evident that to derive value from the different innovation and
experimentation tools available in the market, they have to 'fitted' with the inno-
vation context (Thomke, 2006). This implies changes in innovation systems and
processes as well as the design of appropriate experiments. A critical question for
future research then is how should companies design experiments so as to leverage
the capabilities of these IT-based tools? What aspects of the innovation processes
would need to be modified to enhance the effectiveness of the IT-based tools in
experimentation?
With more and more companies adopting experimentation as the cornerstone of
their innovation strategy, IT will likely come to play a critical role in enhancing
the quality and value of such experiments and thereby contributing to innovation
success. Future research that is targeted at the issues outlined above would thus