Economists and industrial policy makers have long puzzled over astounding differences in the productivity of companies in the same industries or countries.
“A natural explanation for these productivity differences lies in variations in management practices,” says Stanford economist Nicholas Bloom who teaches in the global management curriculum at Stanford GSB. The problem, however, has been proving it.
Now Bloom and John Roberts, the John H. Scully Professor of Economics, Strategic Management, and International Business at Stanford GSB, and three colleagues have provided evidence that a core set of management best practices does increase productivity and profits. In a 2-year field experiment that ended in 2010, they compared Indian textile factories in the same labor market and showed that those that adopted so-called best practices improved their productivity about 10% within a matter of months, while a control group did not. The scholars also detailed the impediments that kept firms from adopting better practices.
While India provided the setting for the experiment, poor management practices can be found around the world. For example, U.S. plants making cement and oak flooring display 100% productivity spreads.
Besides Roberts and Bloom, the researchers are economist Aprajit Mahajan of Stanford; Benn Eifert, a recent doctoral graduate of the University of California-Berkeley; and David McKenzie of the World Bank. The $1.3 million experiment was made possible by a variety of grants, with the largest support provided by Stanford’s Graduate School of Business and Freeman Spogli Institute for International Studies.
Here is how the experiment was run:
The researchers worked with Accenture consultants to expose 20 mid-size Indian textile plants owned by 17 firms to management practices commonly employed in U.S., European, and Japanese manufacturing plants
Although India has some textile firms competing globally, the factories studied were smaller family-owned firms producing for domestic or regional markets. The plants, a small fraction of those in the towns of Tarapur and Umbergaon, about 4 hours from Mumbai, were assigned randomly to a control group of 6 or to a “treatment” group of 14 plants. The consultants spent a month at each plant evaluating them on 38 management practices such as routines for recording and analyzing quality defects, production, inventories, and order fulfillment. They also encouraged preventive maintenance, clear job assignments, and incentive pay based on performance.
“The control plants were given diagnostics because we needed to construct historical performance data for them and help set up systems to generate ongoing data,” Roberts explains.
Next the consultants spent 4 months with the 14 plants randomly chosen for “treatment.” They persuaded plant managers to implement the practices and also helped implement, fine-tune, and stabilize the procedures so that they could be carried out readily by employees. For example, one of the practices implemented was daily meetings for management to review production and quality data. The consultant attended these meetings for the first few weeks to help the managers run them and provide feedback.
“The treatment intervention led to significant improvements in quality, inventory, and production efficiency,” the researchers wrote in a summary. “The result was an increase in productivity of about 10%, a 60% reduction in defects, and a substantial increase in profitability of about $200,000 on estimated average-plant sales of $7.5 million.” In contrast, the control group factories registered less than a 1% gain in productivity.
For the most part, the changes were made with the same management, which demonstrated that “achieving better practices is a learning process,” said William Barnett, who is Thomas M. Siebel Professor of Business Leadership, Strategy, and Organizations; he also codirects the business school’s Center for Global Business & the Economy with Roberts and former U.S. Secretary of State Condoleezza Rice, a Stanford professor. The processes that were successfully introduced included recording machine downtimes and the reasons for them, clearly marking the floor where each machine should be, daily updated visual aids on procedures and efficiencies per machine, and spare parts systematically purchased, recorded, and stored.
In quality control, the practices included monitoring, recording, and meeting to discuss defects on a daily basis, developing a clear grading system for the product and an action plan based on defect data. Previously at some plants, defects were logged in handwriting but only referred to if a customer complained. Now defects are analyzed so they can be corrected the next day and not repeated.
In the “treated” factories, Bloom says, display boards now make productivity statistics visible on the shop floor, and incentive pay is based on the data.
Factories often lost track of yarn supplies. Now they have them organized and counted so designers can fashion uses for them.
The Accenture consultants asked standardized questions to learn why a given practice had not been adopted previously. Cultural practices and legal institutions played a role, but, Roberts says, the primary impediment to change is limited knowledge.
“We saw a significant uptake in preventive maintenance in our treatment firms but not in the control firms, who heard about it in the initial consulting. Even in the treated firms, consultants had to persuade the owners to try preventive maintenance on a sample of machines first. They needed to see proof it paid off over time.”
When asked why they had not done preventive maintenance before, factory workers indicated “either it was because they never heard of it, or they didn’t believe it worked, or they thought they were pretty good at what they did already.”
“It’s really the same story as with the U.S. auto industry in the ’70s to ’90s,” Roberts adds. “At first they didn’t adopt Toyota’s lean product techniques because they didn’t know about them. Then they knew about them but didn’t believe they would work in their plants. Finally they needed help implementing them.”
The management of the Indian textile factories was highly centralized, which also makes change difficult. While the average company had four levels of management, all the important decisions were made at the top level.
“A typical company is one guy and his two brothers who own the entire firm,” Bloom says. “They are the only people who would make any substantial decisions involving money, hiring, or product change. Everyone executes what they have been told to do. In America in a similar situation, plant managers have capital budgets; they can hire and fire and have some choice of product mix.”
The reason for centralization is the degree of theft risk the Indian family owners face, Roberts says. The Indian court system has huge backlogs, so it is hard to rely on laws as a disincentive to theft.
Bloom adds: “If the owner lets the plant manager buy yarn, he may buy this from a friend paying 110% of market rates and then get a juicy kickback. So to get around that problem the owners typically make all the major decisions.”
Better management practices helped decentralize decision-making, the researchers found. “Once I’m getting daily updates from the factory on outputs and inputs and efficiency, I don’t need to be on the scene as many hours to check up on stuff,” Roberts says. “For example, if I am monitoring daily yarn inventory and purchases I would notice suspicious jumps in prices or missing inventory.
“In our best managed firm, the family had only one adult male, so he had to be at the plant every day because they do not use nonfamily members as senior managers. Having better data from the plant freed him up to open two more plants because he didn’t need to be there every day.”
Another conclusion of the field study was that modern management leads to computerization and probably a changing workforce.
“When you need to produce daily charts, you need computer-literate managers and analysts, so you start to change the educational composition of the factory,” Bloom said. “This wasn’t obvious to us in advance, but it could be one reason that in the United States, for example, it’s harder and harder to earn a good living if you are not very well educated. You can see in India that these management practices are bad news for the illiterate factory worker and good news for the guy with more skills.”
Some theoretical work by researchers suggests computer literacy may drive a widening income gap, and this research would support that idea, Roberts said.
The study showed “substantial productivity gains from adopting lean manufacturing practices,” said Kathryn Shaw who is Ernest C. Arbuckle Professor of Economics, and is well known for her careful studies of firms’ human resource management strategies and the productivity impact of management practices in U.S. steel mills. The Indian textile plant study, she adds, “is uniquely able to answer the question: Why don’t more firms in developing countries like India adopt modern manufacturing practices?”
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