While many theories put entrepreneurial or managerial ability at the heart of the issue of productivity dispersion, until recently little large-scale quantitative data existed to empirically investigate these claims across firms, industries, and countries. For an informative discussion on the importance of management in driving productivity, we needed to collect systematic data on representative samples of firms across different sectors and countries. To measure management practices, we developed a new survey methodology, first described in Bloom and Van Reenen (2007), and now known as the World Management Survey (WMS).
The WMS is an interview-based evaluation tool that defines 18 key management practices, and scores them from 1 (“worst practice”) to 5 (“best practice”). The evaluation focuses on three key areas: First, monitoring: How well do organizations monitor what goes on inside the firm, and then use this information for continuous improvement? Second, targets: Do organizations set the right targets, track the right outcomes, and take appropriate action if the two are inconsistent? Third, incentives/people management: Are organizations promoting and rewarding employees based on performance, prioritizing careful hiring, and trying to keep their best employees?
It is important to note that these practices do not cover every aspect of management; for example, we explicitly leave out more “strategic” aspects of management relating to innovation, marketing and finance. These aspects are definitely important, but we do not feel confident of judging anything to be on average better or worse in this regard. The WMS focuses on practices that are likely to be associated with delivering existing goods or services more efficiently. We think there is some consensus over better or worse practices in this regard.
To collect the data, we hired MBA-type students who had some business experience, and trained them to conduct the telephone interviews. These students were from the countries we surveyed (and, thus, could interview managers in their native languages), and were studying at top North American or European universities. The students surveyed manufacturing plant managers, retail store managers, clinical service leads in hospitals, and principals or headmasters in schools. We deliberately targeted middle managers at these levels; they were senior enough to have an overview of management practices but not so senior as to be detached from day-to-day operations.
We interviewed these managers using a double-blind survey technique. The first part of this double-blind technique ensured that managers were not told they were being scored or shown the scoring grid. They were told only that they were being “interviewed about their day-to-day management practices.” To do this, we asked open-ended questions. For example, on the first monitoring dimension in the manufacturing survey, we start by asking the open question “Could you please tell me about how you monitor your production process?” rather than closed questions such as “Do you monitor your production daily [yes/no]?”.
The other side of our double-blind approach ensured that our interviewers were not told in advance anything about the organization’s performance; they were provided only with the organization’s name, telephone number, and industry.
The WMS was administered to over 12,000 firms in 35 countries. We randomly sampled medium-sized firms (employing between 50 and 5,000 workers) in manufacturing and retail, hospitals that deliver acute care, and schools that offer education to 15-year olds (which corresponds to high schools in most of the countries we surveyed).ii The surveys focus on particular practices that are not likely to be relevant for very small organizations with few employees, but see McKenzie and Woodruff (2016) for a related exercise focusing on micro- and small-scale enterprises.
Our findings suggest that the WMS provides a methodologically robust way of measuring core management practices. In the manufacturing sector, the median firm in our sample is privately owned, employs around 300 workers, and operates two production plants. Figure 3 presents the average management practice scoreiii across countries. The United States has the highest average management score followed by Japan, Germany, and Sweden. Halfway down the table are Southern European countries such as Portugal and Greece, followed by emerging economies such as India and China. African countries come at the bottom of the table. This cross-country ranking is perhaps not surprising, since it approximates the cross-country productivity and income rankings.
Outside of the manufacturing sector, we also observe wide variation in management practices within countries. To illustrate this, Figure 4 plots the distributions of management scores for hospitals, schools, and manufacturing firms in the United States for the 16 questions that are identical across the surveys. Figure 4 also highlights that average management scores for manufacturing are higher than for hospitals, whose scores are, in turn, higher than for schools.
One possible reason for the difference is that schools are dominated by the public sector compared to manufacturing, with hospitals in-between. In each individual sector (manufacturing, hospitals, and schools), government-owned organizations have lower average management scores than the others. This is true even after controlling for size, country, and other factors. The main reason government-owned organizations have lower scores is that they have weaker people-management practices. In particular, promotion is often based on time served; persistent underperformers are seldom retrained or moved to different positions. Interestingly, public hospitals and schools look as good as, or better than their private counterparts in terms of management. This finding suggests that the lack of managerial autonomy, the power of unions, and/or the unobserved characteristics of public-sector employees may drive the lower average management scores of hospitals and schools, rather than public ownership per se.
