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Internal and external use of performanceinformation in public organizations: results from aninternational surveyGerhard Hammerschmid , Steven Van de Walle & Vid StimacPublished online: 13 May 2013.

To cite this article: Gerhard Hammerschmid , Steven Van de Walle & Vid Stimac (2013) Internal and external use ofperformance information in public organizations: results from an international survey, Public Money & Management, 33:4,261-268, DOI: 10.1080/09540962.2013.799803

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Who is using performance information?Although performance management is not newand has a long history (for example Hood,2007; Van Dooren, 2008), its use grew underthe umbrella of the new public management(NPM) in the early 1980s. Like NPM, the term‘performance management’ has numerousmeanings, comes in different forms, and coversa range of instruments (Van de Walle and VanDooren, 2010). At its core is the idea of usingperformance information for decision-making(Bouckaert and Van Dooren, 2003, p. 132).

The use of performance information isreceiving increasing academic attention (forexample see Heinrich, 1999; de Lancer Julnesand Holzer, 2001; Ho, 2006; Askim et al., 2008;Moynihan and Pandey, 2010; Taylor, 2011;Kroll, 2012). Many of these studies, however,consider performance information use as aunidimensional construct (for exampleMoynihan and Pandey, 2010), whereas inpractice public managers can use performancemetrics for different purposes and in differentforms (for example Hood, 2007). Externally,performance information can be used toshowcase performance, to give account, or tocompare and benchmark. Internally, it can beused for monitoring or to improve operations.In this paper, we use data from an internationalsurvey of 3,134 top executives working in thepublic sector to analyse determinants ofperformance information use. We distinguish

between internal and external use, and searchfor explanations for the variations in use acrossthe six countries involved.

Research on the use of performanceinformationAlong with increasing implementation,institutionalization and sophistication ofperformance management, the debates aroundperformance management have changedconsiderably. Early, polarized discussions haveincreasingly been superseded by more informedquestioning and research focusing onimplementation challenges in practice (forexample Bouckaert and Hallligan, 2008;Moynihan, 2008; Van Dooren and Van deWalle 2008; Moynihan and Pandey, 2010;Walker et al., 2010; Kroll, 2012).

For practitioners, performancemanagement mostly comes in the form ofspecific tools and instruments used toincorporate performance information orindicators into systems (for example Bouckaertand Halligan, 2008): target systems, controlling,balanced scorecards, reporting systems,performance contracts or performancebudgeting. At the individual level, this is visibleas target agreements, performance appraisals,and performance-related pay. Implementationof performance tools and systems has beenshown to differ substantially from formal policy,and the actual use of performance information

GerhardHammerschmid isProfessor of Publicand FinancialManagement, HertieSchool ofGovernance, Berlin,Germany.

Steven Van de Walleis Professor of PublicAdministration,Erasmus UniversityRotterdam, TheNetherlands.

Vid Stimac is is aResearch Associateat the Hertie Schoolof Governance,Germany.

Internal and external use ofperformance information in publicorganizations: results from aninternational surveyGerhard Hammerschmid, Steven Van de Walle and Vid Stimac

This paper analyses how public managers use performance information. Asample of over 3,100 high-level public sector executives from six Europeancountries, provided evidence of significant country variations. Considerablevariations were also found in patterns of use in different policy fields; andperformance indicators were not used as often in central government as inlocal and regional government. Implementation of performance managementinstruments in an organization had a strong effect on the actual use ofperformance information.Keywords: Accountability; comparative public administration; executives; performanceindicators; performance management.

http://dx.doi.org/10.1080/09540962.2013.799803

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can often lag behind its collection (Van Doorenand Van de Walle, 2008; Moynihan and Pandey,2010).

Researching performance information isdifficult because the concept may refer to verydifferent realities across organizations. Usingvery narrow conceptions of performanceinformation, however, forces researchers toanalyse organizations that are very similar, orthat operate in a single jurisdiction, for examplea school performance indicator in a country; ora key performance indicator (KPI) used in aspecific policy field.

A link between performance measurementand the use of this information in decision-making is often assumed (Moynihan andIngraham, 2004; Pollitt, 2006). Yet, Lægreid etal. (2006) have described ‘use’ as the Achilles’heel of performance management systems andmany researchers are indeed very scepticalabout the usefulness of performance indicators(for example Askim, 2007). Until recently theactual use of performance information was notvery high on the public management researchagenda (Pollitt, 2006; Van de Walle and VanDooren, 2008, p. 2). Since then, quite a lot haschanged. Moynihan and Pandey (2010, p. 849)noted that ‘understanding public employeeuse of performance information is perhaps themost pressing challenge for scholarship onperformance management’. The use ofperformance information is a topic that is nowreceiving increasing academic attention withresearch focusing on who is using performanceinformation, how it is being used, and whatfactors are influencing that use.

Internal and external use of performance informationIn 2003, Behn listed eight different managerialuses of performance information: evaluate,control, budget, motivate, promote, celebrate,learn, and improve. Some of these uses have amore external and some a purely internalfunction and these uses come with differentdata requirements. Performance informationcan be used to learn about what is working andwhat is not, to improve processes and activities,to evaluate how an organization is performing,or to celebrate successes. When performanceinformation is used externally, then it is used topromote the work of the organization and toshow outsiders what a good job the organizationis doing. In a public sector that has becomeincreasingly dominated by rankings, andvarious versions of ‘naming and shaming’,performance indicators have become importanttools for politicians and managers. Rather thanhaving to explain an organization’s

performance in detail, it is now often sufficientto report KPIs (Van de Walle and Roberts,2008). Reputation and legitimacy are also, atleast partly, built on an organization’s positionin league tables. Performance indicators thusfunction as communication tools and not just asmeasurement tools. When one organizationstarts using performance metrics externally,similar organizations will have to do so as wellin order to maintain or create legitimacy in acompetitive environment (DiMaggio andPowell, 1983). This is part of a wider trend inwhich (public) organizations are required togive account for their dealings, often throughperformance reporting (Van de Walle andCornelissen, 2013). This is why performancemanagement systems are sometimes labeled as‘accountability systems’ (Radin, 2006).

Internal and external uses of performanceinformation are related. One of the assumptionsbehind the increased use of performanceindicators, and especially of rankings, is thatexternal performance reporting is believed tocreate pressure to reform organizationsinternally. This is thought to happen in twodifferent ways. Bad performance would benoticed by principals (for example politicians)or clients who would put pressure onorganizations to reform and force organizationsto improve services (Moynihan, 2008). Stronginternal use of performance indicators issupposed to lead to better performingorganizations, which in turn makes externalreporting about performance easier. In ourresearch we looked whether different groupsof public executives put a different emphasison both uses of performance metrics, and howthis can be explained. We assume performanceinformation use is to some extent determinedby individual (socio-demographic) andorganizational factors.

What determines performance information use?Who is actually using performance information,and who isn’t? Public managers’ socio-demographic characteristics is a first set ofdeterminants to consider, and includes factorssuch as age, education, previous experiences,leadership, attitudes, skills, and resources. Suchdeterminants have been used in studies lookingat how managers use performance information(see for example Moynihan and Ingraham,2004; Moynihan and Pandey, 2010; Taylor,2011; or Kroll, 2012 for a systematic overview)and have shown the relevance of such factors asindividual beliefs, attitudes and social norms.Much of this works builds on earlier researchtraditions, looking at the use of information

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more generally by public officials. This includesresearch on the use of evidence, scientificresearch, and evaluations by publicorganizations, and on the role of informationin decision-making more generally (for exampleFeldman and March, 1981).

A related body of research has looked athow politicians use performance information(ter Bogt, 2004; Brun and Siegel, 2006; Pollitt,2006; Askim, 2007). A common finding is thatpoliticians often do not value performanceinformation: for example the best educatedand most experienced local politicians inNorway were found to make the least use ofperformance information (Askim, 2009). Someof these findings are likely to be transferable tothe performance information use behavioursof public managers.

Performance information, and its use, ismore embedded in some organizations andsectors than in others (Askim, 2007). VanDooren (2004) found similar differences acrosspolicy domains in the use of indicators in astudy of parliamentary questions in the Belgianparliament. In a comparison of how evidenceguides policy in a number of sectors in the UK,Davies et al. (2000, p. 3) observed that ‘theaccepted rules of evidence differ greatly betweenresearch cultures’ and the nature of therelationship between evidence and policy varieswith the policy area (Nutley and Webb, 2000,p. 14). International comparative research(Pollitt et al., 2010) has also confirmedconsiderable country differences in the use ofperformance information. Such differences canbe attributed to a number of factors, eventhough large-scale empirical testing remains tobe done. These include organizationaldeterminants such as organizational culture(Moynihan, 2005a; Moynihan and Pandey,2010), information availability (de Lancer Julnesand Holzer, 2001; Moynihan and Pandey, 2004,2010), or the existence of information useroutines and the institutionalization ofinformation (Van de Walle and Van Dooren,2010). Van Dooren (2006) distinguishedbetween demand and supply of performanceinformation, and spoke about ‘demandfrustration’ or ‘supply frustration’ whendemand and supply of performanceinformation are not in equilibrium. In a similarvein, Taylor (2011) identified the state of theperformance measurement system in theorganization as a supply side factor determiningthe utilization of performance information.This has also been confirmed in other research(for example Moynihan and Pandey, 2010).Askim suggests using analogies to herd

behaviour in studying the use of performanceinformation, which means that support fromorganizational leaders is important (Askim,2009). Moynihan and Pandey (2004, 2010)similarly confirmed the relevance of leadership.Further research evidence stressed the needfor having routines in an organization forexamining and interpreting performanceinformation (Moynihan, 2005a, p. 205).

Data and methodA striking feature of research on governmentperformance is a strong reliance on evidencefrom Anglo-Saxon countries and Scandinavia(see Boyne, 2010). To balance this, our data isfrom six European countries. Our survey tookplace in mid 2012 as part of the EU SeventhFramework programme research projectCoordinating for Cohesion in the Public Sectorof the Future (COCOPS, see www.cocops.eu).Fieldwork is ongoing in a number of additionalcountries. Based on a questionnaire jointlydeveloped by an international research teamand translated into different languages, thesurvey was distributed to public sectorexecutives in European countries based on acommon sampling strategy for all countries.The survey targeted all high-leveladministrative executives (mostly in the twotop hierarchical levels) at central governmentministry/department and agency level,irrespective of the specific policy field (forGermany, ministries at state level were includedbecause they have responsibilities similar tocentral government ministries in othercountries). There was an additional sample ofexecutives from the health and employmentsectors. This article is based on data from thefirst six countries where the survey was finishedin summer 2012 (Estonia, France, Germany,Hungary, Italy and Norway). These sixcountries cover the main administrative culturesin Europe. For these countries the survey wassent (both via post and email) to about 12,000executives. We received answers from 3,134people. The overall response rate of 26.2% washigh for this type of survey, particularly giventhe high level positions of the respondents.

The distribution of respondents over thesix countries studied was: Germany (N = 566,18.1%), France (N = 1,193, 38.1%), Italy (N =316, 9.7%), Estonia (N = 320, 10.2%), Norway(N = 388, 12.4%) and Hungary (N = 351,11.2%). In terms of employment, 33.4% werefrom a ministry; 30.4% from an agency orsubordinate government body at centralgovernment level; 15.1% were in a ministry atstate or regional government level; 10.6% at an

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agency or subordinate government body atstate government level; and 10.6% were from asubnational public sector body. Roughly two-thirds of the respondents were male, and nearly90% had a postgraduate degree.

Dependent variables: internal and externaluse of performance indicatorsWe asked eight questions. Our measurementfollows earlier research which also concentratedon self-reported performance information use(see, for example, Moynihan and Pandey, 2010).Table 1 reveals that our managers mainly usedperformance indicators to know whether theyhad reached their targets and to identifyproblems needing attention. Managers wereless likely to use performance indicators toengage with external stakeholders, or tocommunicate what the organization does tocitizens and service users. Overall, roughly30% of respondents were using performanceinformation regularly (6 and 7 on the Likertscale), whereas about 15% either did not useperformance information at all or only to avery limited degree (scale points 1 and 2).

The eight questions examined internal useand external use. The first five questionsmeasured internal use (see table 2) and the lastthree external use. The values of Cronbach’salpha for the two sets of items—0.92 and 0.87

respectively—show that the internal consistencyof the constructs was good to excellent (Kline,1999). The correlation between the rotatedfactors was 0.741, indicating a strong positiverelationship between the two constructs.

FindingsInternal and external use of performanceinformation was found to differ considerablyacross countries. Self-reported performanceinformation use was significantly andconsistently lower in Germany and in France,while it was higher in Italy and Estonia. Thiswas especially marked for external use. This isin accordance with Bouckaert and Halligan(2008) who described Germany and France ascountries that practice ‘performanceadministration’. This is a model of performanceindicator use characterized by administrativedata registration, some incorporation ofindicators into wider systems, but limited use inpractice. Performance information is mainly atechnical or administrative matter without astrong link to management or policy.

To explain the differences in performanceinformation use, we constructed two sets ofinfluence factors. The first set consisted oforganizational factors and described theorganization in which a respondent worked(type of organization, policy sector, and

Table 1. Frequency counts of performance indicator items.

Question: In my work I use 1 2 3 4 5 6 7 No. of Meanperformance indicators to… ‘Not at all’ ‘To a large extent’ observations

Assess whether I reach my targets 251 254 273 422 621 596 457 2,874 4.578.7% 8.8% 9.5% 14.7% 21.6% 20.7% 15.9%

Monitor the performance ofmy subordinates 250 258 343 520 630 560 306 2,867 4.37

8.7% 9.0% 12.0% 18.1% 22.0% 19.5% 10.7%

Identify problems that needattention 220 217 286 406 634 665 430 2,858 4.66

7.7% 7.6% 10.0% 14.2% 22.2% 23.3% 15.1%

Foster learning and improvement 254 248 347 523 652 530 304 2,858 4.368.9% 8.7% 12.1% 18.3% 22.8% 18.5% 10.6%

Satisfy requirements of mysuperiors 253 273 320 501 606 559 330 2,842 4.38

8.9% 9.6% 11.3% 17.6% 21.3% 19.7% 11.6%

Communicate what myorganization does for citizensand service users 496 439 414 458 472 369 205 2853 3.67

17.4% 15.4% 14.5% 16.1% 16.5% 12.9% 7.2%

Engage with externalstakeholders (for exampleinterest groups) 618 469 435 454 415 298 145 2,834 3.37

21.8% 16.6% 15.4% 16.0% 14.6% 10.5% 5.1%Manage my organization’s image 394 336 350 473 603 472 218 2,846 4.00

13.8% 11.8% 12.3% 16.6% 21.2% 16.6% 7.7%

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organizational size). We also included an indexof performance management implementationas perceived by the respondents. This indexmeasures the extent to which the organizationhas implemented a number of performancemanagement instruments (such as the use ofcost accounting systems, internal contracts,management by objectives, benchmarking orperformance related pay). The second setconsists of respondents’ socio-demographiccharacteristics, including gender, age,hierarchical level, length of tenure, prior privatesector experience, level of education and degreetype.

In order to assess the relative impact oforganizational and individual factors oninternal and external use of performanceindicators, we produced three multivariateregression models for both sets of estimatedfactor scores (internal and external use). Model1 included as independent variables a set oforganizational factors, model 2 individualfactors and model 3 both organizational andindividual factors. We also controlled forcountry-level differences by including countrydummies.

Because our two factors were allowed tocorrelate—we performed an oblique promaxrotation on our factor loading matrix (see table2)—it seems plausible that the residuals fromthe internal use and external use regressionswould also correlate. To allow for thiscorrelation between the two equations, weestimated them simultaneously using theseemingly unrelated regression (SUR) method.

Table 3 presents the SUR estimates for theregression models. For the sake of readability,estimates of those sets of control variables thatwere jointly insignificant at 5% (Wald coefficientrestriction test) in Model 3 were excluded fromtable 3. These variables are age, organizationsize, degree type and public sector tenure. Wealso tested the influence of the variable policyfield, following the OECD COFOG classificationof government functions. Statisticallyinsignificant policy field effects—i.e. foreignaffairs, infrastructure and transportation,defense, health, social protection and welfare,education, environmental protection andculture and religion—were omitted.

Looking at model 1’s results in table 3,which includes only organizational factors, thetype of organization is seen to have a significantimpact on the use of performance information.Compared with executives in centralgovernment (reference category), executivesworking in agencies, regional ministries, orother sub-national bodies reported a

significantly higher use of performanceinformation, both internally and externally.So the actual use of performance informationwas generally lower in central governmentministries. Policy fields also mattered.Internal performance information use washigher among respondents working inemployment services, economic affairs andfinance. External performance informationuse, in contrast, was higher among thoseworking in justice, public order and safety,and employment services. The degree ofperformance management instrumentsimplemented in the organization had—notsurprisingly—the strongest effect on the useof performance information. In contrast,our analysis showed that organization sizedid not matter, and the variable thereforewas not displayed in table 3.

In terms of individuals, respondents atlower hierarchical levels made less use ofperformance indicators than those at thehighest hierarchical level. This was especiallythe case for external use. As already shownfor polit ical users of performanceinformation (Askim, 2007), having apostgraduate or doctoral degree wasassociated with a lower use of performanceindicators. One explanation for this could bethat these groups have a larger set ofinformation sources (and not justperformance information) at their disposalwhen making decisions, yet the exact reasonneeds further examination. The main findingat the individual level was that publicmanagers with prior—and especially withlong (over 10 years)—experience in theprivate sector were more active users ofperformance information. Overall, model 2,analysing individual factors, has a relativelylow explanatory value with an R2 of 0.08 forinternal use, and R2 0.12 for external use.

Our most interesting finding, however,emerged from model 3. In model 3, which

Table 2. Exploratory factor analysis, estimated loadings.

Rotated (Promax)Factor 1 Factor 2 Cronbach’s

alpha

Internal useAssess whether I reach my targets 0.865 0.014 0.915Monitor performance of subordinates 0.871 0.020Identify problems that need attention 0.775 0.111Foster learning and improvement 0.692 0.203Satisfy requirements of my superiors 0.630 0.156

External useCommunicate what organization does for citizens 0.042 0.786 0.866Engage with external stakeholders 0.023 0.769Manage my organization’s image 0.147 0.716

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combines individual and organizationaldeterminants, almost all individual level factorsbecame insignificant. In other words, the extentof internal and external performanceinformation use depended almost exclusivelyon organizational factors, notably the type oforganization, policy field and the degree ofimplementation of performancemanagement instruments. Differences indeterminants of internal and external usewere also relatively marginal for this model.With regard to policy field, employmentservices and justice, public order and safetyhad a significantly higher use of performanceinformation. In addition, for public sectororganizations in the economic affairs domainwe found that performance indicators were

less likely to be used externally, whereas inthe finance domain executives were moreactively using performance indicators forinternal purposes. The most relevant variableinfluencing the public managers’ use ofperformance information was the degree ofimplementation of performancemanagement instruments (i.e. informationavailability) in their organization. This is inline with other research confirming theimportance of information availability (deLancer Julnes and Holzer 2001; Moynihanand Pandey, 2004; 2010). However, ouranalysis demonstrates that although theavailability of information is an importantfactor, it does not entirely explain the use ofperformance information.

Table 3. Seemingly unrelated regressions (SUR) on estimated internal and external use factor scores.

Model 1 Model 2 Model 3

Covariates Internal External Internal External Internal Externaluse use use use use use

Agency at central government level 0.17 0.118 0.134 0.094(reference category ministry centralgovernment level) [0.048]*** [0.048]** [0.060]** [0.059]Ministry at state or regional level 0.207 0.222 0.22 0.164

[0.055]*** [0.055]*** [0.072]*** [0.071]**Agency at state or regional level 0.042 0.192 0.128 0.15

[0.074] [0.073]*** [0.095] [0.094]Ministry or other public sector body atsubnational level 0.504 0.316 0.463 0.302

[0.067]*** [0.066]*** [0.085]*** [0.084]***Finance 0.156 0.051 0.181 0.09(reference category general government) [0.056]*** [0.056] [0.069]*** [0.068]Economic affairs 0.097 -0.083 0.09 -0.159

[0.051]* [0.051] [0.060] [0.059]***Justice, public order and safety 0.083 0.15 0.158 0.201

[0.057] [0.056]*** [0.066]** [0.065]***Employment services 0.266 0.215 0.294 0.228

[0.049]*** [0.048]*** [0.060]*** [0.059]***Index of performance managementimplementation 0.376 0.335 0.376 0.32

[0.014]*** [0.014]*** [0.017]*** [0.017]***Second hierarchical level in organization 0.034 -0.134 0.093 -0.05(reference category first hierarchical level) [0.054] [0.050]*** [0.054]* [0.053]Third hierarchical level in organization -0.213 -0.211 -0.038 -0.072

[0.065]*** [0.061]*** [0.064] [0.063]Female -0.017 0.027 0.034 0.065

[0.047] [0.044] [0.045] [0.044]Postgraduate degree (master’s degree) -0.205 -0.207 -0.023 -0.061(reference category first degree) [0.069]*** [0.064]*** [0.067] [0.066]PhD/doctoral degree -0.284 -0.241 -0.054 -0.055

[0.083]*** [0.078]*** [0.080] [0.079]Private sector: 1–5 years 0.069 0.072 0.064 0.066(reference category private sector < 1 year) [0.049] [0.046] [0.045] [0.044]Private sector: 5–10 years 0.102 0.185 -0.004 0.061

[0.085] [0.080]** [0.080] [0.079]Private sector: 10–20 years 0.288 0.349 0.016 0.119

[0.099]*** [0.093]*** [0.093] [0.092]Private sector: over 20 years 0.366 0.465 0.01 0.219

[0.167]** [0.157]*** [0.149] [0.148]R2 internal equation/external equation 0.39 0.34 0.08 0.12 0.41 0.36Observations 2,099 1,978 1,461

Suppressed estimates: Country dummies, age, degree type, organization size, public sector tenure and policy fields: foreign affairs, infrastructureand transportation, defence, health, social protection and welfare, education, environmental protection, and culture and religion.* p<0.1; ** p<0.05; *** p<0.01, standard errors in brackets.D

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ConclusionStudying the use of performance informationis key factor to understanding and improvingperformance management in administrativepractice. Our study has contributed newempirical data and provides evidence forsignificant country variations in the use ofperformance information. We haveconfirmed a more hesitant use in continentalEuropean administrations.

We looked for determinants of internaland external use of performance informationat the individual (executive) andorganizational level. Some people-relatedfactors were initially found, as expected fromthe literature. When organizational factorswere added, however, people-related factorsdisappeared. The absence of an effect ofpeople-related factors is in line with earlierwork (for example de Lancer Julnes andHolzer, 2001; Moynihan and Pandey, 2004;Kroll, 2012) indicating that managers’ socio-demographic characteristics do not matterin performance information use. In contrast,we found clear evidence for the relevance oforganizational factors such as policy field(for example a significantly higher use inemployment services or justice, public orderand safety) and type of public sectororganization (central versus other levels ofgovernment; ministry versus agency). As withprevious research in Anglo-Saxon countries,our study clearly confirms that theimplementation of performancemanagement instruments, such as strategicplanning, management by objectives,performance contracts and performance-related pay, are major influencing factors onthe use of performance information.Instruments that l ink performanceinformation to management systems andprocesses are a factor triggering publicmanagers’ use of performance information.A limitation of the article is that, even thougha distinction was made between internal andexternal performance information, theconcept of use itself was not further specified,leaving the respondents to interpret thisconcept as they saw fit. Some other variableswere also perception-based.

Our results show that in order to stimulatethe use of performance information, effortshould initially focus on organizationalroutines for information use and less onperson-related factors such as education,training or experience.

Future research needs to concentratemore on country differences and on

organizational factors that determineperformance information use.

AcknowledgementThe research leading to these results hasreceived funding from the EuropeanCommunity’s Seventh Framework Programmeunder grant agreement No. 266887 (ProjectCOCOPS), Socio-Economic Sciences andHumanities.

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