Management Quality Matters: Measuring and Benchmarking the Quality of Firms' Management in Turkey


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This is an edited excerpt from a chapter, “Quality of Firm Management in Turkey,” from the upcoming report, “Creating Good Jobs in Turkey.”

How well firms are managed, and whether their management quality (or lack thereof) affects firm performance, are questions that policymakers and researchers everywhere – especially in emerging economies – are very interested in answering.
This area of inquiry is important because much of the evidence shows that the quality of management techniques that are used to run a firm – how it manages its capital and human resources, and how it monitors inventory, among other important areas in the production process – affect firm productivity, adaptability to change, and potential for growth. These factors are especially important in competitive and challenging environments. 
Despite the potential effect of management practices on firm performance, it is a relatively understudied area in the economics literature. Survey-data limitations have made it difficult for economists to analyze the relationship between firm management practices and firm performance.
But that pattern is changing: The World Management Survey (WMS) team designed a new interview-based evaluation tool to quantify the quality of management practices in firms across countries and sectors, and across 18 basic practices in four categories: operations, target-setting, performance monitoring, and talent or human-resource management. (The WMS was started by researchers at the London School of Economics and Stanford University, and it has been conducting management surveys worldwide for more than 10 years.)
In the last decade, many countries interested in benchmarking their firms’ performance have participated in the surveys. Turkey joined this effort in 2014. The new data allows us to measure how Turkish firms perform across the four benchmark dimensions of management. and it allows us to measure how they compare with competing firms across the globe. The results help the private sector and the public sector offer suitable support to improve firm performance and productivity as a whole.
In this analysis, we’ll share some of the early results from Tukey’s first quality-of-management survey, including how Turkey compares to other countries; we'll highlight the importance of measurement; and we'll try to motivate Turkish researchers and policymakers to use the results to help firms in Turkey.  
Average scores for firms in Turkey are low relative to the country’s development level (Figure 1). Firms in comparator countries like Mexico and Poland have higher absolute scores, and relatively higher scores for their development level. (The average scores combine sub-scores for each of the four categories: operations, targeting, monitoring and human resources.)

Figure 1: Per Capita Income and Average Management Score

Note: On this chart, Turkey's position is just above the position of Malaysia.
Source: World Management Survey and authors’ calculations.

Relatively poor performance in Turkey, and key comparator countries, is mostly driven by a large “left tail” of poorly managed firms – a factor that is not uncommon across developing countries (Figure 2). In particular, the fraction of firms performing below the lowest quartile of U.S. firms ranges between 55 percent and 70 percent in such countries as Turkey, Brazil, Poland, Chile, but also China and India. Although there is a large variation in management scores across firms, the distribution of scores in these countries, compared to the distribution in the United States, is either narrow or flat, bimodal and/or nonsymmetrical.

Figure 2: Smooth distribution of total management scores

Note: The vertical red dashed line represents the lowest quartile of the US distribution.
Source: World Management Survey and authors’ calculations.

Comparing the four dimensions of management practices (operations, monitoring, targeting and human resources) across key countries and the United States (which has among the highest average scores in the world sample) shows that weaknesses in each country stem from different sources (Figures 3a-b).

In Mexico and Chile, the lowest score is obtained in the sub-component of targeting practices, which measures whether a firm has clear targets, with a broad set of metrics to measure them, and whether targets are based on solid rationale and cascaded down through the firm. Brazil, Chile and Turkey have relatively low scores for human resource practices, which measures talent management within the firm and whether there is a systematic approach to identifying good and bad performers and rewarding/dealing with them proportionately. It also assesses whether systems are in place to develop, promote and retain good performers. Poland and Brazil have very low scores in the sub-component that measures operational practices; this category measures how well modern management techniques have been introduced, the motivations behind changes, and whether processes and attitudes towards continuous improvement exist. Turkey has the lowest score in monitoring practices among all countries shown in Figure 3a. Monitoring measures the use and collection of data and information, and indicators, to monitor performance and revise production performance.

Figure 3(a): Scores by sub-category; Figure 3(b): Total average management scores

Sources: World Management Survey and authors’ calculations.

As proponents of evidence-based policymaking, we believe that objective data of firm performance is critical to assessing the situation, identifying weaknesses, increasing awareness, affecting action and promoting positive change. We do so because we believe that objective measures can help firms design and introduce corrective measures, and that they can help governments introduce appropriate programs (and policies) to support firms make needed reforms.
Objective data can, for example, clarify for managers (sometimes in a rude awakening) the quality of their own performance. Interestingly, the survey asks managers to rate how well-managed the firm is, in a sort of self-assessment.
As the accompanying charts show, managers in Turkey, Mexico, Chile and Brazil misjudge their own management practices (Figure 4). This illustrates a vast difference between the self-provided scores against actual, objectively measured scores.  These figures reveal that most managers in these countries are unaware that their own management practices are poor. The large gap between the self-assessment and the actual score illustrates managerial overconfidence, which can limit openness to change. Objective data help managers recognize the need to seek tools to make meaningful managerial improvements. (Both theoretical and empirical literature shows that managerial overconfidence has significant effects on corporate decisions and performance.)

Figure 4: Difference in the actual score and the self-assessed score

Source: World Management Survey.
The variation in management practices, across regions within Turkey, is clear (Figure 5). While Akdeniz (on the Mediterranean) has the highest management score on average – 2.83 – Guneydogu Anadolu (in Southeast Anatolia) falls behind the rest of the regions, scoring 2.55 on average. The difference between the top and bottom performers is not large. A common feature in all of Turkey’s regions is that a large fraction of firms fall below the lowest quartile of U.S. firms’ management-score distribution.  Similar to the international patterns illustrated in Figure 1, there is positive correlation, across the regions of Turkey, between regions’ development level and firms’ management scores. In particular, higher per-capita income levels are associated with higher average management scores.

Figure 5: Average Scores and Per Capita Income Level by Region and Industry

Note: Per-capita income is measured in PPP-adjusted constant U.S. dollars in 2011.
Sources: Turkish Statistics Institute, World Management Survey, Taskin (2014), and authors’ calculations.

We examine the correlation between management quality and firm performance, using sub-sector level performance measures. We used sub-sector level data for this analysis. Value-added per hour in sub-sectors of manufacturing sector are obtained from data from the Productivity Directorate General in the Ministry of Science, Industry and Technology.
The positive and statistically significant correlation between productivity (at the sub-sector level) and management-quality scores highlights that, to positively affect productivity in the manufacturing sector in Turkey, it is critical to promote performance improvements among firms in the sector.  
As expected, and consistent with empirical evidence and findings in other countries, multinational firms in Turkey are better managed than domestic firms; exporters are better managed than non-exporters; and family- or founder-owned firms have lower management scores than the other types of firms. Better-managed firms have higher levels of autonomy in terms of decision-making in such areas as hiring, sales and production than firms with lower scores. They also employ workers with higher levels of education (both managers and non-managers) than firms with lower management scores.  

Figure 6: Management Quality (Overall) and Productivity (Per Hour)

Sources: World Management Survey, Productivity Directorate General (Ministry of Science, Industry and Technology), and authors’ calculations.
We are grateful to Turkey for participating in this effort – a critical first step in identifying and measuring challenges that limit productivity in the private sector. Moreover, benchmarking firms’ performance in other countries can help promote competitiveness.  It is clear from our analysis that firms in Turkey have room – often ample room – to improve the quality of their management practices.
The next step in our analysis is formulating practical solutions that firms, industry associations and government can put in place. For instance, government can collaborate with industry associations to increase awareness of best management practices in manufacturing among firms (and managers) in the sector. Firms, industry associations and other stakeholders (such as academia) can design management training courses that address weaknesses among managers in the sector. The government can also help firms by reviewing its regulatory framework and the overall environment for doing business to identify disincentives that may impede firms from implementing better management practices.
Ben-David, Itzhak, Graham, John R., and Campbell R. Harvey (2013), “Managerial Miscalibration,” Quarterly Journal of Economics, Vol 128(4): 1547-1584.
Bloom, Nicholas, and John Van Reenen (2007), “Measuring and Explaining Management Practices Across Firms and Countries,” Quarterly Journal of Economics, 122(4): 1341– 1408.
Bloom, Nicholas, Lemos, Renata, Sadun, Raffaella, Scur, Daniela, and John Van Reenen (2014), “New Empirical Economics of Management,” Journal of the European Economics Association, Vol 12(4): 835-876.
Taskin, Temel (2014), “GDP Growth in Turkey: Inclusive or Not?” Central Bank Review, Vol 14(2): 31-64.



Ximena Del Carpio

Ximena Del Carpio, Senior Economist, World Bank

Temel Taskin

Economist, Development Prospects Group

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