In the previous chapter, the measurement of the building blocks of innovation – person, product, process, and press – was discussed. To understand innovation as a systems phenomenon – an emergent property of a set of interacting components – it will be clear that the building blocks cannot simply be assessed separately and individually in order to gain insights into the resultant organizational outcomes. Innovation managers also need to move beyond understanding outcome in the narrow, proximate sense of the ideas generated and instead examine outcomes in their broader, business context, consistent with a focus on organizational innovation. To do this it is logical to ask, What are the visible, external, and measurable signs of successful innovation? How does a manager know when creative individuals are working effectively together, in a favorable setting, to develop novel and useful products that form the basis of a business enterprise? What is the effect, in the broadest sense, that results from the interaction of the person, product, process, and press?

Part of this shift in scale and focus is a shift away from the relatively simple realm of smaller numbers of observable variables, and relationships among those variables, to the more complex interaction of larger numbers of latent variables, with multiple predictive relationships and associations, and competing models. To assist in understanding the relationships between the independent and dependent variables that define the innovation process, this chapter uses path diagrams and concepts from structural equation modeling (SEM). For a more detailed discussion of this methodology, see Grace, Schoolmaster, Guntenspergen, Little, Mitchell, Miller, and Schweiger 2012).

Studying the effect of innovation in an organizational context means studying organizational performance. In the literature of organizations and innovation, the popular term that describes this is firm performance. It is axiomatic, in studying organizational innovation, that “all the innovative activities must result in better firm performance compared to companies that do not innovate” (Kemp, Folkeringa, De Jong, & Wubben, 2003, p. 18). However, the task is not simply to survey the different ways that firm performance is measured in practice; rather, it is to take a step back to a more theoretical foundation and question what managers should be measuring.