The State of Performance-driven Management in America

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
 

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. Presumably this reflects the growing use of IT in modern firms.

The study also highlights the important rise of data-driven decisionmaking, which the MIT CDB 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.

Figure 2: Average Management Scores Increased between 2005 and 2010,Especially for 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.

Tags: u.s._census_bureau, performance_monitoring, productivity, u.s., management, manufacturing, data_analysis, data-driven_decisionmaking, erik_structured_management, erik_brynjolfsson, u.s._economy


This post first appeared on the MIT CDB Community site.

Hollowing Out

Tom Edsall does a nice job summarizing the increasing hollowing out of the job market in his New York Times column today.  The employment/population ratio has fallen drastically since 1999 even as Real GDP hit an all time high this month.  Edsall quotes Andy McAfee and me arguing that technological progress is part of the story for both these trends. Fewer people are working in America today than in the late 1990s, even though overall income is higher.

James Hamilton and Amar Bhide are quoted by Edsall as being skeptical that the restructuring of the economy contributed to job losses.  While Andy and I agree that the Great Recession is undoubtedly the biggest driver of the job losses since 2007, we also see a longer-term forces at work.  In fact, employment growth was sluggish well before 2007.

Digital technologies have advanced very rapidly in recent years.  This can and does create enormous wealth. That’s the good news.  But there’s no economic law that everyone will share in this wealth.  In fact, as David Autor has noted, in recent years, the demand for middle skill jobs, involving routine cognitive and/or physical skills has plummeted. This is reflected both in wages and in employment. At the same time, those in the top 1% have seen their incomes soar.  The median family actually has less income today than 15 years ago, even though the nation is producing more goods and services than ever before.

Of course, creative destruction has always been important to the US economy.  90% of Americans worked in agriculture in 1800.  By 2000, it was less than 2%. This switch did not result in mass unemployment.  Instead, new industries, from autos to computers, were created to employ people more productively.  However, this time around, job destruction is happening faster than job creation, at least for certain types of workers. Demand for jobs involving routine work is rapidly falling since those jobs are the easiest to automate.  As entrepreneurs discover and invent new ways to employ the laid off workers, the economy should come to a new equilibrium and re-employ those who lost their old jobs.  However, even though the overall economic pie will likely grow, the new equilibrium may involve lower wages for many types of workers, and many may choose to drop out of the labor force entirely, as they have over the past decade.

The first step to addressing the challenges of this great restructuring is correctly diagnosing it.  It won’t do to assume that, just because things worked out in the past, everything will ultimately work out this time as well.

Study the Digital Economy at MIT

If you'd like to study the Digital Economy with me and my colleagues at the MIT Sloan School, you may want to apply to our PhD Program.

We're accepting PhD applications thru January 15, 2012

Please spread the word to your smart, creative, ambitious friends and family members.

The Real Welfare Gain from the Holidays

One of the most famous quotations in economics points out how the market system enables each person’s self-interest to benefit others:

It is not from the benevolence of the butcher, the brewer, or the baker, that we expect our dinner, but from their regard to their own self-interest.

That’s from The Wealth of Nations.

But self-interest alone can’t and doesn’t sustain a successful economy like ours. We humans are wired to care about the welfare of family, friends and even total strangers. Adam Smith himself recognized this. In The Theory of Moral Sentiments, he noted that

How selfish soever man may be supposed, there are evidently some principles in his nature which interest him in the fortune of others and render their happiness necessary to him though he derives nothing from it except the pleasure of seeing it.

I doubt our society could survive long if we weren't influenced by our altruistic instincts in small and large ways every day. There’s no better time than now to think about and act on these “principles in our nature” that give use pleasure in bringing happiness to others. Perhaps that’s the ultimate enlightened self-interest.

Enjoy the Holidays!

Morning Joe discusses "Race Against the Machine"

This morning, I discussed Race Against the Machine with Joe Scarborough, Mika Brzezinski and the gang on MSNBC’s Morning Joe show at 30 Rock. Here's the video.

Technological Plateau or Promise?

Have we reached a technological plateau or is innovation still going strong? If you've read my book with Andy McAfee, you know where I stand. David Wessel of the WSJ discusses the pros and cons of the argument and ties it to our current economic woes in this five minute video.

Not All the Economic News is Bad

The past decade has been terrible in terms of job growth and median wage growth, and sadly that was true even before it culminated in the worst recession since the 1930s.

But not all the news is bad. Although it’s not much discussed, this has actually been the best decade since the 1960s for productivity growth. Last year, labor productivity grew by over 4% and it has averaged over 2.5% in the preceding 10 years.

Why does this matter? Simply this: productivity, output per unit input, is by far the most important determinant of our living standards. As Bob Solow showed in his Nobel Prize winning work, the main thing that makes an economy richer is not working harder or even using more capital or other resources. Instead, the main driver is innovations in products, services and business processes that let us create more value without using more inputs. Productivity comes from new technologies and new techniques of production. The most important of these is what economists call general-purpose technologies like the steam engine or electricity. They contribute to productivity directly, but more importantly, they also spur countless complementary innovations that can keep driving productivity growth for decades.

Our era is fortunate to work with one of the most important and powerful general-purpose technologies in history, information technology, in all its forms. Some of my research suggests that IT has been driving the lion’s share of productivity growth in recent years. What’s more, there is no sign that the digital revolution is slowing. On the contrary, I think we are only in the early stages of a transformation that will be no less important than the ones engendered by the steam engine and electricity.

Unfortunately, not everyone is benefitting from strong productivity growth. In fact, many have been directly hurt as their jobs are automated. This is one of the main themes of my new ebook with Andrew McAfee, Race Against the Machine. Grappling with this paradox, high productivity but stagnating employment, is one of the great challenges for our generation.

How do you think we should address it?

Race Against the Machine

Andy McAfee and I have just released a short e-book, Race Against the Machine. In it, we try to reconcile two important facts. 1) Technology continues to progress rapidly. In fact, the past decade has seen the fastest productivity growth since the 1960s, but 2) median wages and employment have both stagnated, leaving millions of people worse off than before. This presents a paradox: if technology and productivity are improving so much why are millions being left behind?

In the book, we document remarkable advances in digital technologies in particular. Innovations like IBM’s Watson, Google’s self-driving car, Apple’s Siri are turning science fiction into reality. Machines are doing more and more tasks that once only humans could do.

The good news is that this has radically increased the economy’s productive capacity – productivity is at record highs and increasing at an accelerating rate. The 2000s had faster productivity growth than even the booming 1990s. However, technological progress does not automatically benefit everyone in a society. In particular, incomes have become more uneven, as have employment opportunities. Recent technological advances have favored some skill groups over others, particularly “superstars” in many fields, and probably also increased the overall share of GDP accruing to capital relative to labor. While trillions of dollars of value were created between 2002 and 2007, over 60% of the increase went to the top 1%, as technology made it easier for them to leverage their talents globally.

The stagnation in median income and employment is not because of a lack of technological progress. On the contrary, the problem is that our skills and institutions have not kept up with the rapid changes in technology. In the past, as each successive wave of automation eliminated jobs in some sectors and occupations, entrepreneurs identified new opportunities where labor could be redeployed and workers learned the necessary skills to succeed. In the 19th and 20th centuries, millions of people left agriculture, but an even larger number found employment in manufacturing and services.

In the 21st century, technological change is both faster and more pervasive. While the steam engine, electric motor, and internal combustion engine were each impressive technologies, they were not subject to an ongoing level of continuous improvement anywhere near the pace seen in digital technologies. Already, computers are thousands of times more powerful than they were 30 years ago, and all evidence suggests that this pace will continue for at least another decade, and probably more. Furthermore, computers are, in some sense, the “universal machine” that has applications in almost all industries and tasks. In particular, digital technologies now perform mental tasks that had been the exclusive domain of humans in the past. General purpose computers are directly relevant not only to the 60% of the labor force involved in information processing tasks but also to more and more of the remaining 40%.

As the digital revolution marches on, each successive doubling in power will increase the number of applications where it can affect work and employment. As a result, our skills and institutions will have to improve faster to keep up lest more and more of the labor force faces technological unemployment. We need to invent more ways to race, using machines, not against them.

In the end, Andy and I are optimistic that that we can harness the benefits of accelerating innovation. But addressing the problem starts with a correct diagnosis, and that’s what our e-book sets out to provide.

Do agree with our diagnosis? What is your prescription?

Three Events on Technology, Employment and the Economy

If you’re interested in technology, employment and the economy, you might be interested in three events happening in the next few weeks.

The first is the Compass Summit in Palos Verdes, California, on October 23-26. There will be an impressive array of technologists, business leaders, visionaries and policymakers coming together to discussion how innovation can lead us out of some of messes we’ve created lately. I’ll be giving a talk called “Race Against the Machine: How the Digital Revolution Irreversibly Transforms Employment and the Economy” and my colleagues Tom Malone, Andy McAfee and many others will also be participating.

The second event is a whole symposium on technology and employment that the MIT Center for Digital Business is hosting on October 31 (yes, Halloween), followed by a game of Jeopardy! between a team from the MIT Sloan School, a team from Harvard Business School, and IBM’s Watson. Dave Ferrucci, the “father” of Watson will be speaking, along with some amazing technologists and economists. We’ll look at how technologies like Watson, Google’s self-driving car, Apple’s Siri, Heartland Robots and other amazing technologies have gone from fiction to reality, and what it means for jobs, wealth and the economy.

The morning sessions are at the new MIT Media Lab building on October 31, starting at 9:00 am. In the afternoon, we’ll head over to Harvard Business School. Space is limited, so if you’d like to attend please email Joanne Batziotegos (jtegos at mit dot edu) to reserve a spot.

The third event is Techonomy. This was the best non-MIT conference I went to last year and I’m really looking forward to it this year. It will be in Tucson this year, from November 13-15. I’m going to debate Tyler Cowen, the uber-blogger and economist, on the question “Can Technology Be Society’s Economic Engine?” It should be a lot of fun.

Let me know if you plan to attend any or all of the events, but if you miss them, watch this space for a summary of some of the highlights afterwards.

Data-driven Decision-making

Information technology has created a data explosion. We now record virtually every click of every visitor to website, every search on Google or Bing, every transaction at every cash register, every call or text on cellphones, every inventory change in our supply chains and petabytes of other data on what we buy, sell, or even consider. This creates a level of visibility that managers and economists have never had before. And it creates enormous opportunities to use data to change the way decisions are made.

There have been some great case studies of how analytics have affected specific companies, but ironically, there has been relatively little systematic data on this question. Working with Heekyung Kim and Lorin Hitt, we sought to help address this gap in a research paper. We found that publicly-traded companies that were more data-driven were about 5% more productive than their competitors, a statistically significant difference.

I talk a bit about "big data" and how it can change decision-making in this short video that McKinsey recorded when the visited me a couple of months ago.

Is your organization using data more aggressively for decision-making? If not, what's holding you back? If so, what have been the results?