People and workplace analytics: The next generation management information system?

In the year 2013, the movie “Moneyball” prominently depicted data-driven people decisions in baseball. Based on the work of Billy Beane and the so-called “Sabermetrics” the trend towards analytics in sports has seen a peak in the year 2019 with the team Liverpool F.C. winning the Champions League—at least partially attributed to Ian Graham, their people analyst (Schoenfeld, 2019). At the same time, organisations see prospects for data-driven people management beyond mere reporting and controlling. Inspired by the movie “Moneyball”, Ben Waber coined the term “people and workplace analytics” and popularized methods that seek to scrutinize and improve people’s work practices and people decisions in organisational settings (Waber, 2013). A well-known adopter of such methods is the company Uber, which makes heavy use of analytic models and nudges to influence their drivers’ behaviour, e.g. persuading them to service high-demand urban areas (Möhlmann & Zalmanson, 2017).

However, not everything is new about people and workplace analytics (Hüllmann 2020). Scientific management includes the quantification of human labour and uses statistical means to inform managerial decision-making, and the information systems discipline has extensively researched management information and decision support systems (Laudon & Laudon, 2014). Looking back in time, there was “virtually no organizational computer use” (Dickson 1981) until 1955. This saw a sudden change in the following years, reaching a widespread use of management information systems and decision support systems by 1970. Since then, advances in information technology reach us with increasing pace. While originally, only highly structured decisions were assisted and automated, the technological advances increasingly facilitate the support of less structured decision problems. With the use of real-time big data and artificial intelligence, information systems are moving towards more comprehensive knowledge and decision support.

Thesis Goal:

Identify and describe how people and workplace analytics can be informed by existing theories in the management information systems literature.

Lead Questions:

  • Is workplace and people analytics another step in the development of management information systems and decision support systems?
  • How do the roles of the decisions and decision-maker change relating to the classical depiction of management information systems and decision support systems?

Auxiliary Questions:

Advancing from Taylorism and scientific management, organization theory progressed towards seeing organizations as complex socio-technical systems.

  • How does people and workplace analytics relate to this discourse?
    • Is it a step back towards the mechanized human?
  • How does the balance of management control versus empowerment of the individual change?

Thesis Method:

Literature review.

Keywords:

management information systems; people and workplace analytics; decision support; scientific management; literature review

References:

Dickson, Gary W. “Management Information Systems: Evolution and Status.” Advances in Computers 20 (1981).

Hüllmann, J. A. (2020). Three Issues with the State of People and Workplace Analytics. (preprint)

Laudon, Kenneth C, and Jane P Laudon. Management Information Systems. 13th ed. Essex, England: Pearson Education Limited, 2014.

Schoenfeld, Bruce. “How Data (and Some Breathtaking Soccer) Brought Liverpool to the Cusp of Glory.” New York Times Magazine, 2019.

Waber, Ben. People Analytics: How Social Sensing Technology Will Transform Business and What It Tells Us about the Future of Work. Financial Times Prent., 2013.