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Best practices boost productivity & profits at textile firms - Stanford
15
Dec '10
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 the Stanford Graduate School of Business. 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 the Stanford Graduate School of Business, 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.

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