Optimal Prototyping on Experimentation Platforms
Testing and prototyping comprise an integral part of almost any new product development process. Recent emergence of experimentation platforms who specialize in offering evaluation/assessment of prototypes to outside parties have opened up the possibilities for firms in reconfiguring their product development processes. Firms can, by outsourcing the evaluation stage of their dev-test cycles, obtain cost efficiencies and scale. At the same time, a lack of visibility into the actual evaluation process and the possible ambiguity in the product development firm's requirements may lead to potentially noisy evaluations, raising concerns regarding the fidelity and accuracy of the results. The current article formulates a model of “outsourced evaluations” and examines how the noisy low-fidelity evaluations alter the firm's optimal prototyping. Our results demonstrate that imperfect evaluation fidelity changes the client's optimal experimentation, with starkest difference being that it can make it optimal for the client to select and launch a prototype that did not yield the best evaluation. In addition, our analysis reveals that the client should optimally request most precise measurements when their ex-ante uncertainty is moderate (not too high or low). Finally, examining the optimal measurement technology choices of the platform, we find that when the client's ex-ante uncertainty increases from moderate to high values, the platform should offer lower fidelity evaluations, but at a higher fee. We develop managerial insights for how the optimal choice of fidelity and the optimal length of the evaluation cycle should be planned depending on the platform's evaluation fees and the client's ex-ante uncertainty. The resulting framework can offer guidance to product and software development firms who leverage external experimentation platforms.
testing, fidelity, search, platofrms, outsourcing
Business Administration, Management, and Operations
SMU Cox: IT & Operations Management (Topic)