Abductive Reasoning: How Innovators Navigate in the Labyrinth of Complex Product Innovation

Abstract

Complex innovation processes such as drug discovery present challenges to innovators because they must proceed with limited feedback but face a system that involves enormous amounts of information and unknown interdependencies. Organizational scholars suggest that abductive reasoning fits complex situations and may address many of the challenges of complexity. Abductive reasoning is a form of reasoning that generates and evaluates hypotheses in order to make sense of puzzling facts. Existing research on abductive reasoning makes a number of important contributions, but does not explain how innovators can use abductive reasoning to formulate hypotheses for possible new products and then use these hypotheses to navigate in the labyrinth of complex product innovation. We interviewed 85 scientists and managers working in the biopharmaceutical industry and use grounded theory building to develop a new framework. Our framework identifies three social mechanisms that explain how innovators use abductive reasoning to detect useful information despite the noise, avoid competency traps and local optima, and accumulate insights in a holistic way. We contribute to existing research by explaining the systematic process that enables innovators to overcome the challenges of complex innovation and navigate effectively in the labyrinth.

Maneuvering in Poor Visibility: How Firms Play the Ecosystem Game when Uncertainty is High

“…Red managers engaged with some external partners, whom they could project into a range of alternative futures, to understand the technical issues to be addressed across the "very holistic concepts created by [Red] Such engagement with partners narrowed down the range of potentially valuable and connected alternative futures. In essence, similar to the logic of abduction (e.g., Dunne & Dougherty, 2016;Mantere & Ketokivi, 2013;Peirce, 1878), managers understood that they could not predict one future value proposition, but that they could take effort to reduce the uncertainty associated with their proto-visions and iteratively discover whether they remained a possibility. Figure 3 captures this non-deterministic reinforcing process.…”

“…Then, by abductively narrowing down the range of alternative futures (Dunne & Dougherty, 2016;Reetz & MacAulay, 2016), they hoped for clear signals and resource commitments from other actors in the system while ensuring they can strike as soon as they identify a valuable opportunity (Sull, 2005). Thus, our model explains that while actors delay commitment in order to keep the space of possible value creation open, they also act based on their anticipations of value capture to preempt undesirable futures before an ecosystem blueprint crystallizes.…”

“…Such envisioning, however, is not always possible (Anderson, 1999;Dougherty & Dunne, 2011;Dunne & Dougherty, 2016), in particular not when built on generative technologiestechnologies which have the potential to produce unprompted change and to create a breathtaking variety of potential future applications (Gruber, MacMillan, & Thompson, 2008;Zittrain, 2006). For example, attempts to introduce new technologies at lower layers of the digital infrastructure (say, new chip standards to enable near-field communications for 'Internet of Things' applications) typically tend to enable such a large number of potential user-facing applications at upper layers that this can easily overwhelm prospective stakeholders.…”

Managing Innovation Paradox in the Sustainable Innovation Ecosystem: A Case Study of Ambidextrous Capability in a Focal Firm

“…-Head of Strategic Planning Department However, in the evolution of the sustainable innovation ecosystem of complex aerospace products, focal firms should coordinate and integrate different subsystems and modules that are in the charge of other involved organizations [51]. Achieving a balance between different coupling methods in the innovation of complex aerospace products still needs appropriate innovation drive.…”

Taking advantage of emergence for complex innovation eco-systems

“…These four problem cycles are: projects -working on the innovation project (which, like curing cancer, are enormous, global networks); processes -continually integrating diverse emergent sciences to support projects; strategies -experimenting with value creating opportunities that map far into the future; and institutions -generating collaborative commons. Second, to encompass ambiguities, Dunne and Dougherty (2016) develop abductive reasoning to work on all these problems. Third, to address long term emergence and mustering the requisite staying power to persist and learn despite short term pressures, Dougherty et al (2013) develop a way to leverage diverse temporal structures (kairos along with chronos) to leverage emergent knowing and gauge progress over the very long term.…”