Building credible human capital analytics for organizational competitive advantage

• DOI: http://doi.org/10.1002/hrm.21848
• Date: 01 May 2018
• Author: Dana B. Minbaeva
• Published date: 01 May 2018

SPECIAL ISSUE ARTICLE

Building credible human capital analytics for organizational

competitive advantage

Dana B. Minbaeva

Department of Strategic Management and

Globalization, Copenhagen Business School,

Copenhagen, Denmark

Correspondence

Dana B. Minbaeva, Copenhagen Business

School, Department of Strategic Management

and Globalizaion, Kilevej 14, Copenhagen,

Frederiksberg 2000, Denmark.

Email: dm.smg@cbs.dk

Despite the enormous interest in human capital analytics (HCA), organizations have struggled

to move from operational reporting to HCA. This is mainly the result of the inability of analytics

teams to establish credible internal HCA and demonstrate its value. In this article, we stress the

importance of conceptualizing HCA as an organizational capability and suggest a method for its

operationalization. We argue that the development of HCA within an organization requires

working with three dimensions of HCA: data quality, analytics capabilities, and strategic ability

to act. Moreover, such work must be undertaken on three levels: individual, process, and

structure.

KEYWORD

human capital

1|INTRODUCTION

A recent study undertaken by Deloitte found that although 75% of

surveyed companies believed that using human capital analytics

(HCA) is important for business performance, only 8% viewed their

organizational capabilities in this area as “strong”(Deloitte, 2015).

Several consultancy reports and numerous LinkedIn blogs concur:

Despite the vastness of available corporate data, organizations have

been slow to develop their HCA capabilities. Those that have

focused on such development have struggled to move from opera-

tional reporting for benchmarking and decision making to analytics in

the form of statistical analysis, development of “people models,”anal-

ysis of dimensions to understand cause and deliver of actionable

solutions (Bersin, Houston, & Kester, 2014). A study of 255 European

business and analytics professionals confirms that despite progress

with operational reporting and strategic workforce planning, most

organizations have yet to fully develop their analytical competencies

(Kassim &Nagy, 2015).

Why do companies struggle to move to analytics? According to

the Deloitte study, the main reason is the difference between aver-

age “readiness”and “importance”ratings for HR and people analytics,

which Deloitte refers to as a “capability gap”:“Organizations are new

to this discipline, and many suffer from poor data quality, lack of

skills, and a weak business case for change”(Deloitte, 2015, p. 71).

Firms may attempt to fill this capability gap by buying expensive solu-

tions offered by external vendors. However, HCA professionals gen-

erally agree that such capabilities are best built and developed

internally. Despite this widespread view, knowledge about how such

in-house development should take place is lacking.

In this article, we approach this issue by arguing that achieving a

competitive advantage through a sound understanding of one’s own

human capital requires building and developing HCA as an organiza-

tional capability. Based on insights from the organizational capabilities

perspective (Teece, Pisano, & Shuen, 2000; Winter, 2000) and the

micro-foundational view of strategy (Felin, Foss, & Ployhart, 2015;

Foss & Pedersen, 2014), we conceptualize HCA as an organizational

capability that is rooted in three micro-level categories (individuals, pro-

cesses, and structure) and comprises three dimensions (data quality, ana-

lytical competencies, and strategic ability to act).

To illustrate our arguments, we use insights from the various col-

laborative projects that Human Capital Analytics Group has under-

taken with numerous companies in northern Europe. More

specifically, over the past three years, we have followed analytics

projects in six European multinationals (Shell, Novo Nordisk, Vestas,

Mærsk Drilling, LEGO, and Nykredit; see Table 1 for background

information). We have also participated in related focus groups, colla-

borated on analytics projects, and interviewed leading professionals

in this field with the purpose of developing a broad understanding of

DOI: 10.1002/hrm.21848

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