Quantifying Human Resources

Uses and Analyses

Clotilde Coron

• Publisher: Wiley-ISTE
• Year: 2020
• Print ISBN: 9781786304469
• eBook ISBN: 9781119721741
• Edition: 1
• Topic: Business
• Subtopic: Management
• Index: Business

Since the late 20th Century, Human Resources (HR) has had a legal obligation to produce reports for management in most firms. However, these have long been considered restrictive and are seldom used to improve decision-making. More recently, the emergence of analytics, Big Data and algorithms has enabled a reconfiguration of the uses of quantification in HR. Accompanied by empirical examples, this book presents and defines the different tools and uses of quantification in HR. It studies the effect of these tools on decision-making and ? without subscribing to the myth of objective and rational quantification ? presents the contributions and limits of the use of data in HR, and analyzes the potential risks of excessive quantification. It also discusses the appropriation of these tools by the various players in a company and examines their effects on the position of HR.

1
From the Statisticalization of Labor to Human Resources Algorithms: The Different Uses of Quantification

Quantification can be used in many HR processes, such as recruitment, evaluation and remuneration (with job classification, for example). In fact, human resources management gives rise to a very wide variety of uses of figures. The first use refers to decision-making concerning individuals (section 1.1), i.e. using quantified information to inform or justify decisions concerning specific individuals, for example, candidates for recruitment, employees for career management or remuneration. The second use corresponds to a general increase in the adoption of figures and their adoption at the collective level, no longer at the individual level (section 1.2). Historically, this use involved legal reporting and dashboards. It is therefore a question of defining relatively basic indicators and metrics, but aimed at monitoring or steering a situation (e.g. number of employees) or phenomenon (e.g. absenteeism). However, these basic indicators are not always sufficient, particularly because of the complexity of certain HR phenomena. The phenomenon of absenteeism can certainly be measured and monitored by basic bivariate indicators, but these will not be sufficient to identify the determinants of absenteeism, and therefore to define appropriate policies to reduce it. As a result, more sophisticated statistical methods have gradually been introduced in the HR field, both on the HR research side and on the business side: this approach is regularly referred to as “HR analytics”. More recently, the emergence of Big Data and the mobilization of algorithms in different sectors of society have gradually spread to the HR sphere, even if the notion of “Big Data HR” remains vague (section 1.3). This new horizon raises new questions and challenges for the HR function.

It should be stressed that the boundaries between these different uses are tenuous and shifting, and therefore this distinction remains partly arbitrary and personal. Thus, a dashboard can mobilize figures initially constructed with a view to decision-making about individuals. In addition, traditional reporting, which is particularly rich in cross-referencing, can be the beginning of a more sophisticated quantitative analysis, and produce similar results. Similarly, prediction and customization algorithms such as job or training recommendations, which we will classify under the category of Big Data and algorithms, are essentially based on statistical analysis tools (correlation, linear or logistic regression, etc.).

However, this chapter will focus on defining the outlines of these three types of uses, using definitions and examples.

1.1. Quantifying reality: quantifying individuals or positions

The HR function is regularly confronted with the need to make decisions about individuals: recruitment, promotion, remuneration, etc. However, under the joint pressure of ethical and legal issues, particularly around non-discrimination, it is also motivated to back these decisions up as much as possible in order to justify their legitimacy. One response to this search for justification is to mobilize quantified assessments of individuals or work (Bruno 2015). These statisticalization operations of the concrete world (Juven 2016) or commensuration (Espeland and Stevens 1998) aim to both inform decisions and justify them.

1.1.1. The statisticalization of individuals and work

To report on these operations, the focus here is on two types of activities. The first concerns the quantification of individuals and refers to, among other things, tools proposed by the psychotechnical approach briefly described in the introduction. The second refers to the quantification of work, necessary, for example, to classify jobs and thus make decisions related to remuneration, but which raises just as many questions because of the particular nature of the “work commodity” (Vatin 2013).

1.1.1.1. Different tools for the quantified assessment of individuals

Faced with the need to make decisions at an individual level (which candidate to recruit, which employee to promote, etc.), the HR function has had to take advantage of different types of quantified evaluation tools (Boussard 2009). Some tools are, in fact, partly the result of psychotechnical work, but HR agents do not necessarily master the epistemology of this approach. The tools are often used without real awareness of the underlying methodological assumptions. The use of quantified HR assessment tools has been relatively progressive, and two main factors have promoted it (Dujarier 2010). First of all, the transition to a market economy was accompanied by a division of labor and a generalization of employment, which required reflection on the formation and justification of pay levels and differences in pay levels within the same company. Secondly, the practices of selecting and assigning individuals within this division of labor have stimulated the quantified assessment of individuals.

Several examples of this are given here and highlight the uses made by the HR function, but also the criticisms resulting from this. However, in this chapter we do not insist on possible biases and therefore on questioning the notion of objectivity, because this will be the subject of section 2.1.

Psychological testing is a first example of a quantified assessment tool. Its use is frequent in the case of recruitment, and it can have several objectives. First, it can aim to match a candidate’s values with the company’s values. In this case, the test is based on the values and behaviors of the individual. Then, it may aim to match the personality of a candidate with what is generally sought by the company. In this case, the test includes questions that focus on behavior in the event of stress, uncertainty and conflict, for example. Finally, it may aim to match the personality of a candidate with the psychological composition of the team in which a position is to be filled. This variety of uses underlines the fact that the implementation and use of this type of test require upstream reflection in order to provide answers to the following questions: What are we trying to measure? What is the purpose of this measurement?

Once these questions have been answered, the second step is to answer the question: how do we measure what we are trying to measure? To this end, the academic and managerial literature provides many scales for measuring different characteristics and different attributes of individuals. Finally, after passing the test, a final reflection must be carried out on how to use it: to classify individuals, as a support point for the recruitment interview, and as a decision-making aid. A characteristic of these tests is that they can lead to a ranking of individuals in different profiles that are not necessarily ranked hierarchically. Thus, a test on one’s relationship to authority may lead to a classification of different types of relationship (submission, rebellion, negotiation, etc.) without one of these relationships necessarily being unanimously considered as preferable to the others. The preference for one type of profile over the others may depend, for example, on the sector of activity or type of company: a recruitment in the army will probably place a higher value on an obedient profile, unlike recruitment in a start-up or in a company with a flatter hierarchy, for example. Psychological tests are still widely used in recruitment today, although their format and administration methods may have changed (Box 1.1).

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Box 1.1. Psychological tests and recruitment (source: Piotrowski and Armstrong 2006)

Psychological tests have been used since the second half of the 20th Century for recruitment purposes. However, they evolved at the beginning of the 21st Century, mainly due to the increasing use of the Internet and tests measuring the adequacy between a person and a profession (person job-fit test).

Among the companies in the Fortune-500 American index, in 2006, 20% used personality tests as part of their recruitment. In addition, 9% use online tests as a pre-recruitment tool. However, these tests are criticized for their lack of standardization and the doubts that remain about their predictive validity.

Personality tests are now generating renewed interest due to the development of “affinity recruitment” based on the matching model operated by dating networks such as Meetic or Tinder.

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The aptitude, competence or intelligence test is a second tool that is often used, in the context of recruitment, for example. Although the distinction between aptitude, competence and intelligence remains relevant, it is necessary to place these tests in the same category here, because they are used to measure a characteristic of the individual considered useful and relevant for success in a given position. In addition, unlike psychological tests, aptitude, competence or intelligence tests are most often used to rank individuals on a one-dimensional scale. However, as with psychological tests, aptitude, competence or intelligence tests require upstream reflection, in this case on the competencies or skills required for successful performance in the role (Marchal 2015). Although theories such as the g factor or measures such as IQ outlined in the introduction assume that a single competency measure predicts or evaluates a set of interdisciplinary competencies, most aptitude and competency tests are designed to correspond to a specific position. However, the division of a position into skills or aptitudes is not without its difficulties (Box 1.2).

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Box 1.2. The difficult division of a position into skills (source: Marchal 2015)

As early as the 20th Century, some psychotechnologists recommended making an inventory of the skills and abilities needed to hold a position, and suggested conducting extensive in situ analyses. However, this procedure represents significant costs, especially since a rigorous approach requires reproducing the analysis each time there is a change, even a minor one, in the organization or working or employment conditions. In addition, in situ analyses are initially very focused on the physical actions performed (by typists, for example), which loses its relevance with the tertiarization of employment. Under these two combined effects, the analyses are likely to evolve, focusing on behaviors and no longer on actions, and focusing on the identification of behaviors specific to a group of jobs and not to a specific job. In doing so, however, the tests produced from this type of analysis lose their specificity, accuracy and ultimately their predictive validity.

In addition, there are many criticisms of these analyses and tests. The first type of criticism highlights the many biases that job analyses can face, particularly because of the importance of the person observing the situation. The second type of criticism highlights the fact that the same job does not correspond to the same reality according to the organizational context in which it is practiced: being an engineer or nurse does not require the same skills or competences in every different organization. More ...

Table of contents

• Cover
• Table of Contents
• Acknowledgments
• Introduction
• 1 From the Statisticalization of Labor to Human Resources Algorithms: The Different Uses of Quantification
• 2 Quantification and Decision-making
• 3 How are Quantified HR Management Tools Appropriated by Different Agents?
• 4 What Effects are the Effects of Quantification on the Human Resources Function?
• 5 The Ethical Issues of Quantification
• Conclusion
• References
• Index
• End User License Agreement