I teach at a School of Management so you won’t be surprised to learn that I think good management can make a huge difference in the performance of companies, and ultimately the economy.  But you may be surprised that there is very little economic research on the effects of management.  Sure, there’s lots of speculation and countless management books and articles, but a recent review of the economic literature by Chad Syverson concluded: “No potential driving factor of productivity has seen a higher ratio of speculation to empirical study [than management practices].”  The biggest problem has been simply a lack of a comprehensive, reliable data set of management practices.

To address this gap, I recently helped formulate the U.S. Census Bureau’s survey of management and organizational practices at more than 30,000 manufacturing plants across the country–the first large-scale survey of management in America. Along with Nick Bloom, Lucia Foster, Ron Jarmin, Itay Saporta and John Van Reenen, we examined three types of practices– performance monitoring; setting targets, and offering incentives—which we called “Structured Management.”Analysis of the data reveals several striking results about the relationship between performance goals and improved business. Specifically, setting business goals and monitoring results are among the practices that actually yield better business productivity and growth, according to this comprehensive survey of U.S. management conducted in 2011. The survey was funded by the National Science Foundation and had administrative support from the National Bureau of Economic Research and the MIT Center for Digital Business. It was a joint, academic-U.S. census bureau collaboration.
My fellow researchers and I set out to determine whether, and what type of management practices influence bottom-line business results such as productivity, output and growth. Based on the responses, we found a tight link between Structured Management and performance outcomes such as growth, expenditures and innovation as indicated by R&D and patent intensity.
Figure 1: Better Performance is Associated With More Structured Management
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While the survey did not focus exclusively on digital technologies, the conclusions may partly reflect the increasing adoption of information technologies, like Enterprise Resource Planning (ERP) systems, which make data collection and processing much cheaper, easier and more effective. Structured Management scores for data use have improved the most, according to the data.
Figure 2: Average Management Scores Increased between 2005 and 2010, especially for Data Driven Performance Monitoring
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Presumably this reflects the growing use of IT in modern firms.The study also highlights the important rise of data-driven decision-making, which the MIT Center for Digital Business has championed for several years. Most of the rise in structured management practices, for example, has come among businesses that have implemented data-driven performance monitoring.

It was also interesting to note that adoption of structured management practices has increased between 2005 and 2010, particularly for those practices involving data collection and analysis.  This is consistent with my earlier research with Lorin Hitt and Heekyung Kim on Data-Driven Decisionmaking.

Among other key findings:
  • There is a substantial dispersion of management practices across the establishments. Eighteen percent have adopted at least 75% of these more structured management practices, while 27% adopted less than 50% of these.
  • There is a positive correlation between structured management practices and location, firm size, establishment-level measures of worker education, and export status.

Going forward we will continue to analyze the data and explore causality. Additionally, we may do another survey in 2015 to establish longer-term data and perhaps will focus on the retail or health-care sector.

Let me know what other ideas you think we should explore.

This post first appeared on the MIT Center for Digital Business Community site.

 

 

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