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СКАЧАТЬ second challenge is to define the right HR policies. Rasmussen and Ulrich (2015) thus give an example where an offshore drilling company uses quantification to define a policy linking management quality, operational performance and customer satisfaction (Box I.2). This example therefore illustrates how quantification can help identify problems and links between different factors in order to define more appropriate and effective HR policies.

Box I.2. Quantification as a source of improvement in the definition of HR policies (source: Rasmussen and Ulrich 2015)

      An offshore drilling company commissioned a quantitative study that demonstrated several links and influential relationships between different factors. First, the study shows that the quality of management (measured through an annual internal survey) influences turnover, on the one hand, and customer satisfaction, on the other hand (measured through a company’s customer relationship management tool). Staff turnover influences the competence of teams (measured according to industry standards) and their safety and maintenance performance (measured using internal company software, such as falling objects), which also has an impact on customer satisfaction, and is also strongly linked to the team’s operational performance. This study therefore provided the company with evidence of the links between these various factors, which made it possible to define a precise plan of action: improving the quality of management through training and a better selection of managers, improving team competence through training and increased control, among other things.

      Finally, the third challenge is to prove the contribution of the HR function to the company’s performance. As Lawler et al. (2010) point out, the HR function suffers from the lack of an analytical model to measure the link between HR practices and policies, and the organizational performance, unlike the finance and marketing functions for example. To fill this gap, they suggest collecting data on the implementation of HR practices and policies aimed at improving employee performance, well-being or commitment, but also on organizational performance trends (such as increasing production speed or the more frequent development of innovations).

      This trend therefore values quantification as a tool to improve the HR function via several factors: more objective decision-making, the definition of more appropriate and effective HR policies and proof of the link between HR practices and organizational performance, which can encourage the company to allocate more financial resources to HR departments.

The other, more critical trend is part of a sociological approach and takes a more analytical look at the challenges of quantification. Desrosières’ work (1993, 2008a, 2008b) founded the sociology of quantification, which focuses on quantification practices and shows how they are socially constructed (Diaz-Bone 2016). This analytical framework is based, among other things, on the concept of conventions, which are interpretative frameworks produced and used by actors to assess situations and decide how to act (Diaz-Bone and Thévenot 2010). The economics of conventions focuses on coordination that allows institutions and values to emerge, and shows how this coordination is based on conventions, which make it possible to share a framework for interpreting and valuing objects, acts and persons, and thus acting in situations of uncertainty (Eymard-Duvernay 1989). The originality of Desrosières’ work lies in mobilizing this concept of convention to analyze quantification operations, which amounts to studying “quantification conventions” (Desrosières 2008a), namely a set of representations of quantification that will make it possible to coordinate behaviors and representations (Chiapello and Gilbert 2013).

Desrosières thus seeks to deconstruct the assumptions that accompany the myths surrounding quantification (the myth of statistics that are ostensibly a transparent and neutral reflection of the world, for example, and that constitute a guarantee of objectivity, rigor and impartiality), in particular by emphasizing the extent to which quantification is based on social constructions, and not on physical or natural quantities. He suggests that statistical indicators should be considered as social conventions rather than measures in the sense of the natural sciences (e.g. air temperature) (Desrosières 2008a). Gould (1997), without claiming to be part of the sociology of quantification, also provides very illuminating illustrations of how quantification can be influenced by social prejudices, making objectivity impossible. In one of his books, Desrosières (2008a) also highlights the extent to which statistics, far from being merely a transparent reflection of the world, create a new way of thinking about it, representing it, measuring it and, ultimately, acting on it. However, his work also focuses on the history of statistics and the dissemination of new methods in the field. Thus, Desrosières (1993) highlights the link between the State and statistics. The latter, historically confined to population counting, has gradually been enriched by new methods and theories (probabilities with the law of large numbers, then econometrics with regression methods, to cite only two examples), which have partially loosened its ties with the State, and have brought it closer to other sciences, such as biology, physics and sociology. In another book, Desrosières (2008b) highlights the developments in modern statistics after the Second World War (reorganization and unification of official statistics, willingness to act on indicators such as the unemployment rate, etc.). These founding works have since been widely adopted by many authors.

Chiapello and Walter (2016), for example, are interested in the dissemination of calculation conventions used in finance. They show that, contrary to a rational ideology that would have the algorithms mobilized in finance be so because they are the most effective and rigorous, this dissemination is sometimes entangled in the power games between different functions or professions in the world of finance. Similarly, Juven (2016) shows that the activity-based pricing policy introduced in French hospitals does not always respond solely to the rational logic of improving hospital performance, but comes from choices and trials and errors that can only be understood by looking at the sociological foundations of the decisions taken (Box I.3). Finally, Espeland and Stevens (1998) focus on the social and sociological processes underlying “commensuration” operations, which make it possible to compare different entities (individuals and positions, for example) according to a common metric.

Box I.3. Example of the introduction of activity-based pricing in French hospitals (source: Juven 2016)

      The introduction of activity-based pricing in French hospitals is a long-term process that takes several years. It required, among other things, a quantification of medical procedures and patients: how much a particular medical procedure costs and should be remunerated, or the management of a particular type of patient. However, this statisticalization has been the subject of many controversies between doctors, health authorities and patient associations. These different actors obviously have divergent interests, between reducing hospital costs and improving the management of a specific pathology. This case therefore illustrates the way in which the quantification of reality, far from being merely a neutral reflection of reality, proceeds from choices, negotiations and controversies that illustrate its sociologically constructed dimension.

      Finally, this second trend takes a more critical approach to quantification. While the first trend is based in particular on the idea of quantification that can supposedly provide objectivity, transparency, neutrality and rationalization, the second trend questions this vision and these assumptions, thus questioning more generally the contributions of quantification to management.

       I.4. The positioning of this work

Our book seeks to provide a nuanced and didactic perspective on the use of HR quantification. Therefore, it draws on these two currents to try to reflect as much as possible both the advantages and limitations of quantification. More precisely, we ask ourselves the question of the use that companies can make of HR quantification, but also the evolutions СКАЧАТЬ