Does Management Matter? Evidence from India

A long-standing question is whether differences in management practices across ﬁrms can explain differences in productivity, especially in developing countries where these spreads appear particularly large. We ﬁnd that adopting these management practices raised productivity by 17% in the ﬁrst year through improved quality and efﬁciency and reduced inventory, and within three years led to the opening of more production plants. Why had the ﬁrms not adopted these proﬁtable practices previously? Our results suggest that informational barriers were the primary factor explaining this lack of adoption. Also, because reallocation across ﬁrms appeared to be constrained by limits on managerial time, competition had not forced badly managed ﬁrms to exit.

Policy implications

The research does support some of the common recommendations to improve productivity, like increasing competition (both from domestic firms and multinationals) and improving the rule of law. The results also suggest that firms were not implementing best practices on their own because of lack of information and knowledge, therefore both training programs for basic operations management, like inventory and quality control and demonstration projects would help in increasing efficiency.

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Hypotheses/research question

Does management consulting affect a firm's performance?

Study design

Parallel-group

The sample was randomly chosen from the population of all publically/privately owned textile firms around Mumbai, based on lists provided by Ministry of Corporate Affairs. Firms were between 100-1,000 employees. Geographically the firms were focused in towns of Tarapur and Umbergaon (largest textile towns in area) to reduce consultant travel times. This yielded a sample of 66 potential firms who were then contacted over the telephone by consultants offering free services. Of these 66, 34 expressed interest. These were paid a visit and sent a letter from Stanford and of these 34, 17 agreed to commit senior management time to project (project firms). These 17 firms had 28 plants between them.

Cost benefit ratio

A total increase of profits was estimated to be around $325,000 per plant per year.

Rounds of data collection

Data from firms involved in the project was collected at 2-month intervals starting 10 months before the diagnostic phase and extending to at least 24 months after. Initial data collection using firm records going back to April 08. Round 1 (4 treatment plants) - Baseline data collection in Sep 2008, measuring until Aug 2010. Round 2 (10 treatment plants) - Baseline data collection in April 2009, measuring until Aug 2011. Round 3 (6 control plants) - Baseline data collection in July 2009, measuring until Nov 2011. Additionally, a detailed ground-based survey of 113 textile firms around Mumbai with 100 to 1000 employees took place, collecting data at a yearly frequency using retrospective information.

Baseline data collection and method

Mechanisms for baseline data collection were installed during the diagnostic phase of consulting work in both treatment and control. Firm records dating back to April 2008 were used. Also, the researchers used some incumbent measures collected via retrospective interviews.

Data collection method and data collected

Mechanisms for data collection were installed during the diagnostic phase of consulting work in both treatment and control.

Unit of analysis

Plant

Stratification

Reference

Bloom, N., Eifert, B., Mahajan, A., McKenzie, D., & Roberts, J., 2013. 'Does Management Matter? Evidence from India'. The Quarterly Journal of Economics, Oxford University Press, vol. 128(1), pages 1-51.

Does Management Matter? Evidence from India

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