Blame avoidance strategies in governmental performance measurement

• Published date: 01 August 2020
• Date: 01 August 2020
• Author: Tomi Rajala
• DOI: http://doi.org/10.1111/faam.12225

Received: 10 November2018 Revised: 30 July 2019 Accepted:6 August 2019

DOI: 10.1111/faam.12225

RESEARCH ARTICLE

Blame avoidance strategies in governmental

performance measurement

Tom i Raja la

Faculty of Management, University of Tampere,

Tampere,Finland

Correspondence

TomiRajala, Faculty of Management, University

ofTampere,Tampere 33104, Finland.

Email:tomi.rajala@tuni.fi

Abstract

Performance measurement and blame avoidance are significant

forces that shape the development of the public sector. Unfortu-

nately,extant literature has not paid much attention to blame avoid-

ance in performance measurement. Thus, this article aims to show

how blame avoidance strategies can be embedded in performance

measurement. This case study’s results provide theoretical ideasand

empirical examples that demonstrate how a particular performance

measure––central government productivity––enabled blame avoid-

ance. These results will help practitioners and academics view blame

avoidance aspects in performance measurement.

KEYWORDS

blame avoidance,performance management, performance measure-

ment

1INTRODUCTION

Performance measurement and blame avoidance are essential aspects of public sector activities. “Performance mea-

surement,” that is, the act of measuring performance with indicators, often is presented as a tool that leads to improved

public sector performance (Van Dooren & Vande Walle, 2011) and transparent government (Johnsen, 2005). Extant

blame avoidance literature presents blame avoidance as a central feature of public management and administration

(Hood, 2011). In this paper, “blame avoidance” refers to the act of minimizing the expected blame that one must

face when something unwanted happens in the public sector domain (Hood, 2014). Avoiding blame when service-

production operations in the public sector fail is a typical example of blame avoidance (Rajala, Laihonen, & Vakkuri,

2018).

Blaming, as a phenomenon, needs at least two actors: a blamer and a scapegoat. The scapegoat needs to do some-

thing blameworthy,and the blamer must be able to observe the scapegoat’s blameworthy actions. Blame cannot hap-

pen without information that describes someone doing something blameworthy.Performance measurement provides

information about the public sector’s blameworthy actions. Indeed, performance measurement is related to account-

ability (Kloot, 1999) and to the question of who should be blamed when performance falls short (Bovens, 2010). Public

sector actors operate in an environment characterized by a negativity bias (Charbonneau & Bellavance, 2012), and

performance measurement, as an accountability mechanism, may be used to blame public managers (Flynn, 1986) or

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politicians (James, 2010). Because blame is a risk associated with performance measurement (Wholey & Hatry,1992),

risk management can be adopted (e.g., Hood, 2002) and based on blame avoidancestrategies (Hood, 2011).

Until now, scientific research on performance measurement has focused on performance measures’ design (Wis-

niewski & Stewart, 2004), as well as implementation (Collier,2006) and use of such measures (Ho & Chan, 2002). Mea-

surementsystems’ content also has been examined (Van Peursem, Pratt, & Lawrence, 1995). However,extant literature

has not considered what type of measurement system content is an indication of the use of blame avoidancestrategies.

The blame avoidance literaturedoes not provide an answer to this question either, focusing mainly on blame avoid-

ance strategies used in political and administrative functions to mitigate, delegate, or hide blame arising from public

sector failures (Hood, 2011). These strategies explain how public officials and politicians try to avoid blame (Hinter-

leitner, 2017). However, none of these strategies requires performance measures, which partly explains why blame

avoidance strategies used in measurement solutions are an underexamined topic (e.g., Hood, 2011; Weaver, 1986).

Toaddress this research gap, this article studies how performance management systems’ design may facilitate blame

avoidance strategiesand how governments use these strategies in performance measurement systems.

As a result, this article demonstrates that performance measurement solutions can actualize blame avoidance

strategies. This contributes to discourse on performance measurement and blame avoidance, as neither research

stream has demonstrated how blame avoidance strategies can be incorporated into performance measures. A case

study applying a hypothetico-deductive method is utilized to achievethese results.

For practitioners and academics, the contributions offer new ways to understand performance measurement as a

system that utilizes blame avoidance strategiesin its functions. This understanding is important because blame avoid-

ance inhibits the ability to see reasons for failures; thus, it makes learning more difficult in the public sector.The the-

oretical ideas presented here also offer fresh starting points for future studies to examine blame avoidance in other

types of performance measures, not just in productivity measures. Moreover, this study left many blame avoidance

strategies uncovered;therefore, new research is needed to address these.

Inthe next section, the research gap in the previous literature is presented in more detail and the created theoretical

hypotheses on blame avoidance strategies in performance measurement are demonstrated. In the third section, the

research method is described. The fourth section provides an empirical analysis, and the article ends with a discussion

and conclusions.

2THEORETICAL BACKGROUND

Using blame avoidancestrategies in performance measurement refers to what extant literature calls “blame avoidance

behavior,” which severalstudies have examined. Blame avoidance behavior, as a research subject, was examined first

by Weaver (1986), who said blame avoidancebehavior existed in the political domain because politicians used blame

avoidancestrategies for two reasons: Politicians are loss averse, and their constituents had a negativity bias. According

to Weaver(1986), loss averse politicians aim to avoid blame more than they want to claim credit. Therefore, politicians

are willing to giveup opportunities to claim credit. As one can see, Weaver’s focus focused on political decision-making,

not on performance measurement systems enabling blame avoidance.

Since Weaver’s (1986) seminal article, blame avoidancebehavior has been studied in two fields: comparative wel-

fare state research and public policy and administration (Hinterleitner,2017). In comparative welfare state research,

Pierson(1994, 1996) studied blame avoidance behavior and how it was used to pursue out of favor reforms. In Pierson’s

(1994) thinking, politicians have only two objectives: to advance their politicalagendas and ensure their re-election. If

a politician’s political agenda shifts from expansionto cutback politics, cutbacks can cause losses for politically impor-

tant interest groups. Therefore, advancing a political agenda that calls for cutbacks can imperil re-election prospects.

According to Pierson (1994), blame avoidance behavior is used to reconcile tension between retrenchment and elec-

toral retribution to ensure re-election despite cutbacks.