Organizational Selection of Innovation

TL;DR

This paper models how organizations select innovation projects under budget constraints, examining the effectiveness of different decision aggregation methods and highlighting when delegation or collective judgment yields better outcomes.

Contribution

It introduces a model for organizational portfolio selection and compares various decision aggregation strategies, revealing when collective judgment outperforms delegation.

Findings

Ranking agents' preferences often outperforms averaging scores.

Aggregating multiple agents' impressions improves project selection.

Delegation is effective only with relevant experts and proper assignment.

Abstract

Budgetary constraints force organizations to pursue only a subset of possible innovation projects. Identifying which subset is most promising is an error-prone exercise, and involving multiple decision makers may be prudent. This raises the question of how to most effectively aggregate their collective nous. Our model of organizational portfolio selection provides some first answers. We show that portfolio performance can vary widely. Delegating evaluation makes sense when organizations employ the relevant experts and can assign projects to them. In most other settings, aggregating the impressions of multiple agents leads to better performance than delegation. In particular, letting agents rank projects often outperforms alternative aggregation rules -- including averaging agents' project scores as well as counting their approval votes -- especially when organizations have tight budgets and can select only a few project alternatives out of many.