The Impact of Information Networks on Productivity

Organization Network Analysis session

Jacomo Corbo (The Wharton School of Business) — Gary Pisano (The Wharton School of Business)
The Impact of Information Networks on Productivity

As the information content of work increases, the role of information becomes increasingly central to our understanding of the performance of individuals, groups and organizations. Ironically, while a growing number of workers transact in information, researchers have less and less information about how these workers create value, and managers have greater difficulty measuring, managing and optimizing work. The challenges associated with managing information diffusion and of estimating information worker output are particularly acute for companies involved in complex product innovation, where performance hinges critically on an organization’s capacity to constantly and consistently innovate and many facets of the product architecture and their component interdependencies are ever changing. Unfortunately, methods and tools available to address these challenges are scarce.

At the same time, information technology affords us an unprecedented opportunity to monitor information flows, observe worker interactions and organizational structures, and estimate individual and organizational performance. This research is part of a nascent stream exploring the relationship between information, technology and information worker productivity, using empirical evidence to examine how communication behaviours and information-seeking habits affect individual level and group level output. Our work also examines how design interfaces in the product architecture map onto communication patterns within the development organization.

In particular, we ask: Do different types of information exhibit different diffusion patterns, and do different characteristics of social and organizational structure, as well as product architecture, in turn affect access to different kinds of information? Does better access to information predict an individual’s productivity and performance and what exactly is the relationship between communication flows and individual and organizational performance?

Finally, we look at how resource and task allocation strategies impact communication patterns and, by extension, individual and organizational performance.

We leverage a rich and unique data set related to the aerodynamic development operations of several companies in Formula One (F1). The data includes the majority of established F1 competitors as of 2009 and features email communication, organizational network, and CAD design data for all participant companies as far back as 1999 (and no later than 2002) until today.

Productivity metrics are often notoriously difficult to apply to organizational divisions below whole business divisions, e.g. at the individual or group levels. In our case, the aero performance data relates to a CAD aero part design for which the trail of individual workers’ marginal contributions to that design are recorded, allowing for the assessment of productivity at the level of individual workers, whole teams, and the entire department. Notably, the performance measures used to assess productivity are common to all companies in F1, which facilitates a rare industry-wide comparison of the impact of managerial variables on performance.

Combining network and econometric analysis, we uncover strong relationships between organizational networks, communication behaviors, and productivity, and show that the pattern of communication within organizations, both within and between collaborating teams, is pivotal to organizational performance and productivity. We find that communication patterns strongly predict project completion times and even individual and group performance. Our findings shed light on the underlying mechanisms that drive performance, show how information flow dynamics relate to long-run productivity, suggest how organizations can be designed to maximize output, and allow us to forecast individual level and group level productivity. Our findings also provide some of the first evidence of the economic significance of information diffusion in communication networks.