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Donald P.
Moynihan
REFLECTIONS ON CASES IN CONTEXT OF US EXPERIENCEPRESENTATION, JANUARY 9, 2014, COPRBM
Cases at micro level, move back to macro level adoption of performance systems
Relate their experiences to US context
Can you learn something from our experience and mistakes?
Please jump in with questions, comments and examples
MY ROLE
Background Creation of performance systemsPerformance management as interactive
dialogue Different types of performance information
useFactors associated with purposeful
performance information use
OUTLINE
BACKGROUND
OECD 2012 surveySeems to be less use of performance data than in past
Performance targets not consequential
General sense of disappointment: we have systems in place, have not delivered desired results
IS THE IDEA OF PERFORMANCE MANAGEMENT RUNNING OUT OF
STEAM?
We define performance systems by the benefits we hope will occur (more rational budgeting, more effi cient management)
The gap between our aspirations and the observed effects of these rules are usually large, resulting in disappointment
More grounded and accurate description: performance systems are a set of formal rules that seek to disrupt strongly embedded social routines
EXPECTATIONS PROBLEM
GOVERNMENT-WIDE REFORMS
Government Performance and Results Act - GPRA (1993-2010)
Program Assessment Rating Tool (2002-2008)
GPRA Modernization Act (2010-)
State level variations on these models
GPRARoutines of strategic planning and measurement at agency level
Program Assessment Rating ToolEach program evaluated by central budget office, given feedback and ranked on scale from “ineffective” to “effective”
GPRA Modernization ActRecognition of problems with previous systems
GRADUAL CHANGE IN SYSTEMS
CREATION OF PERFORMANCE
SYSTEMS
Elected offi cials motivated by symbolic values (Moynihan 2008)
Managing for results has intuitive appeal for elected offi cials and international institutions
Limits of high-level design Your tools are procedural rules and incentives Create rules to measure and disseminate data Perhaps set up incentives Say you are doing performance management Diffi cult to design rules that change underlying beliefs,
organizational culture or leadership May be politically contentious – changing organizational
flexibility may be opposed by public sector unions
POLITICS OF ADOPTION
DOCTRINAL LOGIC FOR CHANGE
ACTUAL PATTERN OF CHANGE
We are constrained (and sometimes enabled) by high level designs and their characteristics
We are constrained about expectations of public sector and behavior of elected offi cials
How do you work within these systems? Minimize dysfunctional behavior Minimize transaction costs that do not provide
value Create environment where positive things might
happenHow do you know if you are succeeding?
FACTS ON THE GROUND
PERFORMANCE MANAGEMENT AS AN
INTERACTIVE DIALOGUE
We fail to understand the nature of performance data
We assume data areComprehensiveObjective Indicative of actual performanceConsistently understoodPrompts a consensus
ONE BASIC REASON FOR CONFUSION
Examine same programs but disagree on data
Agree on data but disagree on meaningAgree on meaning, but not on next
action steps/resources
THE AMBIGUITY OF PERFORMANCE DATA
Actors will select and interpret performance information consistent with institutional values and purposes
Greater contesting of performance data and less potential for solution seeking in forums featuring actors with competing beliefs
THE SUBJECTIVITY OF PERFORMANCE DATA
DIFFERENT TYPES OF PERFORMANCE
INFORMATION USE
INATTENTION TO THE USE OF DATA
Performance data by itself does not do much
Implementation of performance management means using the data
Why focus on performance information use? Difficult to connect public actions to outcomes Intermediate measure of effectiveness Without it, good things we want don’t happen
There are different types of use
Passive – minimal compliance with procedural requirements
Purposeful –improve key goals and effi ciency
Political – advocate for programsPerverse – behave in ways detrimental
to goals (goal displacement and gaming)
THE FOUR TYPES OF USE
IMPLICATIONS OF DIALOGUE MODEL: POLITICAL USE
Performance data is socially constructed by individuals subject to
personal biases, institutional beliefs, and partisan preferences
These qualities make performance management likely to operate as part of political process, not as alternative to it
EVIDENCE OF ADVOCACY
“Spinning” (Hood 2006) Claim credit when things go well, deny
responsibility when things do notAdvocacy by agents seeks to avoid blame and
respond to “negativity bias” disproportionate citizen dissatisfaction with missed
target (James 2011) political offi cials pay more attention to high and low
performers (Nielsen and Baekgaard 2013) more bureaucratic explanations of failed performance
(Charbonneau and Bellavance 2012)
WHEN DOES PERVERSE USE OCCUR?
UK case provides example – managing the measure not underlying goal, don’t use pay for performance
Goal displacement – e.g. cream-skimmingData manipulation – including outright
cheatingBecomes more likely when
Complex tasks have simple measures High-powered incentives attached to measures
Can observe if agencies comply with requirements (passive use), but not other types of use
Performance systems encourage passive use, not purposeful (Moynihan and Lavertu 2012)
Cases: Passive use creates transaction costs
EFFECT OF PERFORMANCE REFORMS
Very little evidence of systematic attention by elected offi cials or performance budgeting
Variation in purposeful use seems to be shaped by agency, unit or individual level variables – how they respond to systems
Start a purposeful dialogue about performanceCases offer some insights that align with other research
IMPLICATIONS FOR PURPOSEFUL USE
LEARNING FORUMS DISCRETION
CULTURE
Part of the problems we have created routines to measure and disseminate data
Need to design routines to facilitate use of data
Australia: learning circles, practicums, learning teams learning conversations, future circles
UK: Implies ongoing discussion about system, how to improve, double loop learning
Belgium: spatial design to foster interaction, leave time for creativity and problem-solving
ROUTINES OF LEARNING
Create learning forums: routine discussions of performance data with supervisors/peers associated with use
GPRA Modernization Act: quarterly performance reviews
Cases: not just routines, also learning culture (Moynihan 2008) Tolerates error – allowance for making mistakes Rewards innovation and experimentation Brings together multiple perspectives – cannot exclude those who
know processes best and must implement change Gives discretion to users – more likely to use data Mix exploration and exploitation – look for new ideas while
improving what you are doing Needs continuity
CONTINUING CHALLENGE: HOW TO MAKE USE OF PERFORMANCE DATA
When people feel they have discretion, more likely to use data (Moynihan and Pandey 2010)
Formal limits to discretion in public sector, but Sometimes overestimate constraints Organizational culture can overcome these
tendencies (Pandey, Coursey and Moynihan 2007)
DISCRETION AND CULTURE
GOAL CLARITY
FOSTER GOAL CLARITY
Cases: clarify purpose – what are you doing here?
Clear goals increase performance information use (Moynihan and Pandey 2010)
May not be easy if:Service has many different aspectsTension between:
Few enough measures to generate attentionEnough measures to avoid encouraging workers to ignore unmeasured aspects
APPEAL TO ALTRUISM
Cases: Be wary of the demotivating effects of targets Create work environment where workers feel like
they are making a difference Celebrate achievement
Extrinsic direction can create crowd out intrinsic desire to help others Removes sense of moral judgment
CROWDING OUT EFFECTS
Not an option to get rid of measurements
Appeal to altruistic motivations, not extrinsic reward (Moynihan, Pandey, and Wright 2012)
Select goals that motivateClear line of sight between goals and actions Celebrate achievementConnect to beneficiariesEasier for some tasks than others (you have customers, and your job is to help them)
APPEAL TO ALTRUISM
LEADERSHIP
Cases: Importance of leadershipLeadership matters in a variety of ways
Political leadership needed for adoption Leadership commitment needed for implementation (Dull 2009; Moynihan and Lavertu 2012) Performance system aligns with their goals Authenticity: more than talk
Do they devote time and resources to goals? Do they model the behavior they ask of others?
THE ROLE OF LEADERSHIP
Transformational leadership: Frank Van Massenhove Stimulates creativity, shapes culture, models
behavior, make goals inspirational
Leadership creates environment where performance information use is more likely to occur (Moynihan, Wright and Pandey 2012)
TRANSFORMATIONAL LEADERSHIP
Goal Clarity
Transformational Leadership
Developmental
Culture
Purposeful Performance Information Use
INDIRECT EFFECTS OF LEADERSHIP
0.31*
0.60*
0.67
0.13*
0.55
0.22*Reported
Performance Information
Use
E
E
0.15*
Goal
Clarity
Developmental
Culture
TransformationalLeadership
0.60*
0.13* Performance
AvailabilityInformation
0.64
E
0.84
E
Leader Tenure
Number of Employees
NS
NS
0.07*
NS
FollowerTenure
External service providing agency
NS
0.14*
0.07*
0.16*
NS
0.11*
0.99*
E0.28*
FollowerGender
STRUCTURAL EQUATION MODEL WITH CONTROLS
Goal Clarity
Transformational Leadership
Developmental
Culture
Purposeful Performance Information Use
INDIRECT EFFECTS OF LEADERSHIP
How do you create commitment?GPRA Modernization Act (Moynihan
2013)Reputation: public commitments and responsibility (high priority goals)
Create leadership positions with oversight for performance (COOs, PIOs)
Each goal has a goal leaderSelect leaders based on ability to manage
performance
INDUCE LEADERSHIP COMMITMENT
Welcome your feedback and questions
Performance Information Project: http://www.lafollette.wisc.edu/publicservice/performance/
index.html
CONCLUSION
REFERENCES
Charbonneau, Etienne, and François Bellavance. 2012. Blame Avoidance in Public Reporting. Public Performance & Management Review 35(3): 399-421
Dull, Matthew. 2009. Results-model reform leadership: Questions of credible commitment. Journal of Public Administration Research & Theory 19(2): 255–84.
Hood, Christopher. 2006. Gaming in targetworld: The targets approach to managing British public services. Public Administration Review 66(4): 515–21.
James, Oliver. 2011. Managing Citizens’ Expectations of Public Service Performance: Evidence from Observation and Experimentation in Local Government Public Administration, 89 (4), 1419-35.
Moynihan, Donald P. 2008. The Dynamics of Performance Management. Washington DC: Georgetown University Press.
Moynihan, Donald P. 2013. The New Federal Performance System: Implementing the New GPRA Modernization Act. Washington D.C.: IBM Center for the Business of Government.
Moynihan, Donald P. and Stéphane Lavertu. 2012. “Does Involvement in Performance Reforms Encourage Performance Information Use? Evaluating GPRA and PART.” Publ ic Administrat ion Review 7(4): 592-602
Moynihan, Donald, and Sanjay Pandey. 2010. The big question for performance management: Why do managers use performance information? Journal of Publ ic Administration Research and Theory 20(4): 849–66.
Moynihan, D., Pandey, S. , & Wright, B. (2012). Prosocial values and performance management theory: The l ink between perceived social impact and performance information use. Governance , 25(3), 463–83.
Moynihan, Donald P. , Wright, Bradley, and Sanjay Pandey. 2012. “Sett ing the Table: How Transformational Leadership Fosters Performance Information Use.” Journal of Publ ic Administration Research and Theory 22(1): 143-64.
Nielsen, Poul A. and Mart in Baekgaard 2013. Performance Information, Blame Avoidance, and Pol i t ic ians’ Att i tudes to Spending and Reform: Evidence from an Experiment. Journal of Publ ic Administration Research and Theory doi: 10.1093/jopart/mut051
Pandey, Sanjay K., David Coursey and Donald P. Moynihan. 2007. “Overcoming Barr iers to Organizational Eff ectiveness and Bureaucratic Red Tape: A Mult i -Method Study” Publ ic Performance and Management Review 30(3): 371-400