Hybrid Data Competencies for Municipal Civil Servants: An Empirical Analysis of the Required Competencies for Data-Driven Decision-Making

• Author: J. Dingelstad,R. T. Borst,A. Meijer
• DOI: http://doi.org/10.1177/00910260221111744
• Published date: 01 December 2022
• Date: 01 December 2022
• Subject Matter: Articles

https://doi.org/10.1177/00910260221111744

Public Personnel Management

2022, Vol. 51(4) 458 –490

© The Author(s) 2022

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DOI: 10.1177/00910260221111744

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Article

Hybrid Data Competencies

for Municipal Civil Servants:

An Empirical Analysis of the

Required Competencies for

Data-Driven Decision-Making

J. Dingelstad1, R. T. Borst2, and A. Meijer2

Abstract

This study focuses on an important yet often neglected topic in public personnel

competency studies: competencies required for digital government. It addresses the

question: Which competencies do civil servants need for data-driven decision-making

(DDDM) in local governments? Empirical data are obtained through a combination

of 12 expert interviews and 22 Behavioral Event Interviews. Our analysis shows that

DDDM as observed in this study is a hybrid process that contains elements of both

“traditional” and “data-driven” decision-making. We identified eight competencies

that are required in this process: data literacy, critical thinking, teamwork, domain

expertise, data analytical skills, engaging stakeholders, innovativeness, and political

astuteness. These competencies are also hybrid: a combination of more “traditional”

(e.g., political astuteness) and more “innovative” (e.g., data literacy) competencies.

We conclude that local governments need to invest resources in developing or

selecting these competencies among their employees, to exploit the possibilities data

offers in a responsible way.

Keywords

competencies, behavioral event interviews (BEIs), data-driven decision-making, JD-R

model, local government

1Erasmus University Rotterdam, The Netherlands

2Utrecht University, The Netherlands

Corresponding Author:

R. T. Borst, Utrecht School of Governance, Utrecht University, Bijlhouwerstraat 6-8, Utrecht 3511 ZC,

The Netherlands.

Email: r.t.borst@uu.nl

1111744PPMXXX10.1177/00910260221111744Public Personnel ManagementDingelstad et al.

research-article2022

Dingelstad et al. 459

Introduction

The importance of civil servants’ competencies—broadly defined as work-related

knowledge, skills, traits, and motives—to cope with the challenges of the 21st century

is increasingly emphasized in the public Human Resource Management (HRM) litera-

ture (Bonder et al., 2011; Getha-Taylor et al., 2016; Kruyen & Van Genugten, 2020).

These studies focus, for example, on collaborative competencies, typical for the zeit-

geist of New Public Governance (NPG; Getha-Taylor, 2008, 2018). However, the

development of digitalization and datafication of society and governmental organiza-

tions and the competencies this requires of civil servants are underexposed (Kruyen &

Van Genugten, 2020).

The attention to civil servants’ competencies dates to the 1950s (Hood & Lodge,

2004), and gained momentum around the turn of the century. Since then, Competency-

Based Management (CBM) is increasingly embraced as a new approach to managing

almost all key human resource processes (Bonder et al., 2011; Hondeghem &

Vandermeulen, 2000; Kruyen & Van Genugten, 2020). Indeed, studies have focused

on training and developing competencies (e.g., Naquin & Holton, 2003; Sims et al.,

1989; Van Buuren & Edelenbos, 2013), on recruitment and selection procedures based

on competency profiles (Farnham & Stevens, 2000; Sundell, 2014) but also on com-

plete job analysis processes based on competency profiles that inform strategic man-

agement (Bonder et al., 2011; Hondeghem & Vandermeulen, 2000; Pickett, 1998). All

these studies show that civil servants are usually recruited and trained based on gen-

eral, universal or core (clusters of) competencies required for all public but also pri-

vate employees. However, civil servants need specific, context-dependent competencies

related to their job (Bonder et al., 2011; Getha-Taylor et al., 2016; Kruyen & Van

Genugten, 2020). Within this CBM and competency profiles literature, digital or data

competencies are barely mentioned, and civil servants themselves also seem unaware

of the importance of digital competencies (Kruyen & Van Genugten, 2020). The lack

of attention to digital or data competencies is rather surprising since over the past

decades’ digital technologies have come to play a major role in the public sector (Lips,

2020; West, 2005).

Following the private sector, governments have started to use increasing amounts

of data sources to support decision-making (Choi et al., 2018). This data-driven deci-

sion-making (DDDM) is decision-making “based on the analysis of data rather than

purely on intuition” (Provost & Fawcett, 2013, p. 53). It represents a shift in govern-

mental decision-making that strongly preferences a way of working in which data

facility and analysis are the most significant elements. Organizational theorists have

argued that advanced technological systems almost always come with high hopes for

their potential to change organizations for the better (Contractor & Seibold, 1993;

DeSanctis & Poole, 1994). It is therefore not surprising that DDDM developers, users,

and scholars also hypothesize different, faster, more supported, more precise and

cheaper decisions than “traditional” decisions based solely on experience and intuition

(Berner et al., 2014; McAfee & Jolfsson, 2017; OECD, 2017; Van der Voort et al.,

2019).

460 Public Personnel Management 51(4)

Decades of extant research in organization theory demonstrate that technological

advancements restructure and reshape work practices and show the importance of the

role of human agency in this process (Barley, 1986; Boudreau & Robey, 2005;

Contractor & Seibold, 1993; DeSanctis & Poole, 1994; Pentland & Feldman, 2007).

The introduction of new technologies in organizations thus presumably alters the set

of required competencies somehow (Orlikowski, 2000). Various studies highlight the

importance of developing the “right” competencies in governments to exploit the new

technology of DDDM (e.g., Brown et al., 2011; Desouza & Jacob, 2017; Kim et al.,

2014; Malomo & Sena, 2017). However, none of them explain what the “right” com-

petencies entail. They do not define them more precisely than for example “skills that

allow for the analysis and modeling of complex phenomena” (Malomo & Sena, 2017,

p. 17). This highlights the need to develop a thorough academic understanding of the

role of competencies in public DDDM.

This study fills the gap both in the literature on CBM and in the literature on public

DDDM by addressing the following research questions:

Research Question 1: How is DDDM executed in practice in governmental

organizations?

Research Question 2: What are the required competencies for responsible DDDM

in practice?

To answer this question, we conducted 12 expert interviews, 22 Behavioral Event

Interviews (BEIs) with municipal civil servants, and a focus group, following the com-

petency study method of Spencer and Spencer (1993). This method is used increas-

ingly in public management research and is considered the most scientifically rigorous

approach to identifying competencies (Getha-Taylor, 2008).

With this article, we extend the competency profiles of civil servants by introducing

a specific (cluster of) competencies that are required in DDDM. As a result, we inform

the public HRM literature and more precisely the CBM literature by introducing

insights from digital government literature. Moreover, this study can stimulate practi-

tioners to make better-informed decisions regarding the competency-based profiles of

civil servants. These can inform the recruitment and selection process and the training

and development process, so public organizations can better cope with the challenges

of digital government (Kruyen & Van Genugten, 2020).

Competencies for Responsible DDDM

Data-Driven Decision-Making

The rapid usage and expansion of the boundaries of data collection and analysis

require that civil servants take different steps in decision-making processes. Before we

explain what DDDM means for the competencies of civil servants, we specify what

DDDM entails and how it differs from “traditional” decision-making.