Data-driven Management Evidence Mixed for Optimizing Workforce Performance

On 8 Jul, 2015 By Michael.Walker 0 Comments
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The goal of data-driven management is to optimize decision-making at all levels for better organizational performance. Optimizing workforce productivity is one important goal and using data science to improve process efficiency and worker performance has mixed results according to new research published in April 2015 entitled "The Contingent Effect of Management Practices".

The research found that organizations with a collaborative culture may cause decreases in productivity and performance if they try to use data to foster employee competition.

Read paper here.

Organizational behavior is tricky business and using data to motivate and predict human behavior is difficult if not impossible considering a high causal density environment. Yet human incentives and disincentive matter and many organizations are experimenting using data-driven management techniques in attempt to optimize worker productivity.

There is no one-sized data management solution or formula - every organization is different - and managers need to be careful not to let data alone determine management decisions. While using data is important, the human art of management is critical to tailor the motivation of employees to the company culture to achieve optimal performance.

The optimal data science strategy for optimizing workforce performance is to conduct small, well-designed experiments to find what works and does not work. Data science methodologies and measurements should be employed to avoid the myriad of traps and misinterpretations of data.

Abstract      

This paper investigates how the success of a management practice depends on nature of the long-term relationship between the firm and its employees. A large US transportation company is in the process of fitting its trucks with an electronic on-board recorder (EOBR), which provide drivers with information on their driving performance. In this setting, a natural question is whether the optimal managerial practice consists of: (1) Letting each driver know his or her individual performance only; or (2) Also providing drivers with information about their ranking with respect to other drivers. The company is also in the first phase of a multi-year "lean-management journey". This phase focuses exclusively on changing employee values, mainly toward a greater emphasis on teamwork and empowerment. The main result of our randomized experiment is that (2) leads to better performance than (1) in a particular site if and only if the site has not yet received the values intervention, and worse performance if it has. The result is consistent with the presence of a conflict between competition-based managerial practices and a cooperation-based relational contract. More broadly, it highlights the role of intangible relational factors: the optimal set of managerial practices depends on the long-term relationship the company chooses to have with its workers.