Performance Management Regimes in Practice: Examining the Local Agencies Implementing Temporary Assistance for Needy Families

Abstract

Performance management regimes significantly influence public management practice and policy implementation. Yet, within public administration scholarship, there is insufficient attention to how regimes are reified through policy implementation or how they influence management decisions and outcomes. In this analysis, we considered the robustness of policy regime theory to deepen our understanding of performance management. We examine an empirical setting where two competing performance regimes seek to shape local program delivery in social welfare. We use this case to expand regime theory by highlighting the significant role of local managers in interpreting conflicting regime signals. Their interpretation directly shapes operational practices. The analysis highlights that further theorizing about policy regimes should consider various levels within implementation system, particularly the significance of managerial authority.

Keywords

performance management regime theory policy field policy implementation TANF intergovernmental relations welfare

Performance Management Regimes in Practice

Over the past two decades, governments have become reliant on performance management to address accountability concerns across levels of government, including public and private service providers. Performance management scholarship proliferated along with the ideology that government inefficiency can be improved through management reform (Osborne & Gaebler, 1992). This literature documents how the rise of performance management accompanied both a decrease in administrative capability in the public sector and rise of third-party governance (Brewer & Selden, 2000; Fredrickson & Fredrickson, 2007; Heinrich, 1999; Moynihan et al., 2011; Radin, 2006). As of 2004, all states had legislative requirements to create performance information systems to improve public management (Moynihan, 2008). Although performance management systems are intended to both enable accountability and enhance understanding about specific performance indicators, there are often challenges in their implementation. Conflicting goals, causal uncertainty, and task complexity create significant challenges (Hall & Handley, 2011; Hall & Jennings, 2011; Moynihan, 2008; Pollitt, Harrison, Dowswell, Jerak-Zuiderent, & Bal, 2010).

Although there is no unified theory of performance management, scholars claim there is a relationship between governance complexity and performance use (Moynihan et al., 2011). In fact, within this literature, scholars interested in the institutionalization of performance metrics or mind-sets often use the terminology “performance regime” descriptively (Charbonneau & Bellavance, 2012; Grubnic & Woods, 2009; S. Martin, Nutley, Downe, & Grace, 2015; Moynihan, 2008; Pollitt et al., 2010; Talbot, 2010). This article broadens this usage and considers regimes analytically, drawing on a robust theoretical tradition that seeks to explain how institutions and actors operate in relatively stable systems of formal and informal rules (Esping-Andersen, 1990; L. L. Martin & Simmons, 1998; May & Jochim, 2013; Mossberger & Stoker, 2001; Stone, 1989). Although regimes are not directly observable, the theoretical framing allows scholars to focus on the interaction of ideology, institutions, and political interests present during policy development or implementation. In this article, we leverage this approach and investigate whether a policy regime framework (May & Jochim, 2013) might deepen scholarly theory and understanding of performance management.

In this study, we examine the performance management regime developed from the 2005 reauthorization of the U.S. Temporary Assistance for Needy Families (TANF) program in one state. The case is of interest because this particular state developed an alternative regime that challenged federal performance directives. To begin to develop a theory of performance management regimes, we closely investigate this case through its multilevel implementation system. The data gathered were semistructured interviews and observations of local agency managers and staff carrying out operations in 12 counties, which enable a systematic analysis of performance systems in practice. Although regimes ostensibly create a standard of reference for implementers, this research reveals that the conflicting ideas, interests, and institutional arrangements can also create other outcomes.

In our analysis, we begin by considering whether regime strength can predict government service orientation or results. The May and Jochim’s (2013) articulation of the theory stresses this descriptive dimension of regime, emphasizing a binary designation of strong and weak regimes. In our research context, we find two contradictory performance regimes in operation under which local governments must act. One focuses on measuring activities, the other focuses on outcomes. One is bolstered by the federal government, the other by state government. In this empirical setting where two conflicting performance regimes operate concurrently, we first explored whether we can predict which regime influences the organizational practices and outcomes in the local governments charged with policy implementation. However, this analysis led us to further investigate other potential causal mechanisms to better understand how performance regimes operate. We seek to answer the following question:

Research Question 1: How do the performance regimes influence the implementers’ understanding of their roles and their operational strategies?

In this article, we focus on four counties from our data set to illustrate how local program implementers make sense of these contrary regimes, including their perceptions of the strength of each regime and how those perceptions influence the way in which performance management is carried out. This type of analysis is consistent with those undertaken by other policy implementation scholars interested in how sense making influences managerial action in the organizations actually delivering services (Coburn, 2005; Hill, 2003; Spillane, 1998; Sandfort & Moulton, 2015). The rich contextual information helps to illustrate how managers play important roles in weak performance regimes. However, it is important to note that our interest in the explanatory power of managerial sense making developed from field conditions, when it became clear that current articulation of regime theory was not nuanced enough to explain the empirical phenomenon observed.

In fact, our findings do not conform to an often-reported story of local discretion exerted by individual street-level bureaucrats. Rather, our inductive analysis reveals the important ways local managers with administrative authority shape the figuration of performance regimes in practice. Although multilevel policy implementation introduces complexity (Sandfort & Moulton, 2015), in our analysis, we see how local managers play critical roles by interpreting regime signals in the environment, and determining which one influences the daily office operations and service delivery choices, therefore influencing performance. In this way, our research expands the robustness of the policy regime framework and improves its explanatory capability.

Research Relevant to Understanding Human Service Performance Regimes

The tensions between local control and national accountability present in our federalist system have a long tradition in the social welfare programs of the United States (Gordon, 1994; Patterson, 1994; Soss, Fording, & Schram, 2011a). For almost every social welfare concern, state and local governments, nonprofit advocacy and service organizations, and private philanthropy play unique roles depending on the state context (Sandfort, 2010). Amid this puzzling complexity, funders adopt performance measurement as a solution. Since 1974, the federal government has required organizations that serve the poor to document their effectiveness.¹ The United Way—a nationwide network responsible for funding essential safety-net programs—also utilized this approach, in part, to improve public confidence after national scandals of financial mismanagement (Hendricks, Plantz, & Pritchard, 2008; Plantz, Greenway, & Hendricks, 1997). More than 20 ago, they established new outcome measurement standards for their nonprofit grantees and implemented elaborate training programs in logic modeling to assure take-up.

Scholars refer to the development and institutionalization of this type of ideology as a “performance regime” (S. Martin et al., 2015; Moynihan, 2008; Pollitt et al., 2010; Talbot, 2010). In this usage, a “regime” is a relatively stable system that provides logic for actors—be they governments, private contractors, program managers, or governance bodies—to help resolve ambiguity and legitimate certain actions above others.

In public policy studies, Peter May and Ashley Jochim (2013) provide an elegant theoretical framework about regimes through examining the development and implementation of national policy (Jochim & May, 2010; May, Jochim, & Sapotichne, 2011). This framework does not focus on public policy as the analytical starting point, but instead, probes how politics and policy interact to address problems. The policy regime perspective shares much in common with the scholarship on policy feedback (Mettler & SoRelle, 2014; Soss & Schram, 2007) and administrative burden (Moynihan, Herd, & Harvey, 2014) that consider how state operation creates unintended consequences. Those literatures concentrate their attention on effects on the citizen, whereas the regime perspective focuses on the institutional and political consequences of public policy. In this way, regime theory provides ways to understand how public management practice may be caused by, and reinforce, regime ideology. It is well suited for more careful analysis of performance management systems and their operational consequences.

To analyze a policy regime, May and Jochim (2013) suggest three forces are particularly important: shared commitment concerning the policy purpose (ideas), constituency support and opposition (interests), and structures of authority, attention, and information (institutional arrangements). Ideas operate as governing principles; analysis should explore the meaning and legitimacy of the central idea of the regime. Interests help to establish the governing ability in a regime; analysis should focus on whether key constituencies are engaged or mobilized in support of the regime. Finally, institutional arrangements reflect the implementation structures, the flow and form of funding, and the public and private entities engaged; analysis should focus on the formal and informal relationships and the cohesion created by these factors in the regime. May and Jochim (2013) stress that policies bundle the ideas, interests, and institutional arrangements of regimes together and create governing instruments.

In their articulation of the framework, May and Jochim (2013) stress the significance of regime strength and develop propositions that strong policy regimes fortify policy legitimacy, foster coherence, and enable durability. From their federal vantage point, regime strength is merely reduced to one dimension (weak to strong), and that only strong regimes effectively provide clear sense making in the face of policy ambiguity. However, they also recognize that much is yet unknown of how regimes operate in multilevel implementation systems where different combinations of ideology and interests may be significant. This study explores such a case.

Research Setting: TANF

Many scholars documented the welfare reform of 1996, when the U.S. federal government ended a 65-year-old entitlement to cash assistance for families with children by imposing time limits for income support receipt through the TANF block grant (Cancian, Haveman, Kaplan, & Wolfe, 1999; Cherlin, Bogen, Quane, & Burton, 2002; Gooden, 2004; Mead, 2001; Posner & Wrightson, 1996). Scholars found this case particularly interesting because of their concerns about how the national law splintered the safety net and devolved policy-making decisions to states and tribes as a block grant, enabling significant variation in implementation (Hahn, Golden, & Stanczyk, 2012; Hahn & Loprest, 2011; Schott, Pavetti, & Finch, 2012). Although many studies described this change, there is little current scholarship about the program or its implementation (see Box 1). Today, although many policy scholars note the rise in the importance of alternative forms of income support, the fact remains that TANF continues to be an important national program for providing minimal cash assistance for those most destitute.

Box 1.

National Implementation Conditions for the TANF Program.

Although the analysis here focuses on performance management within TANF, it is important to note other details of implementation. Nearly 20 years after enactment, the federal government spent US$17 billion on TANF, the lowest inflation-adjusted amount since the program’s origination (CBO, 2015). The block grant loses its absolute value annually and, by 2014, was worth one third less than when it was passed (Falk, 2016). Federal law also allows states to use the block grant for a range of program activities that either ameliorate or address presumed causes of child poverty; as a result, the funding for cash assistance going directly to families has decreased significantly over time. The best estimates suggest that states now distribute less than 30% of their TANF block grant and state funds as cash to families (CBO, 2015; Falk, 2012). Until the end of the Obama Administration, the federal government gathered little information about how states use the majority of the TANF block grant funds.
This lack of transparency is particularly troubling when compared with the implementation activity that is the focus of this article—performance standards that focus on assuring the state tracks program participants’ activities. The federal regulations require states to diligently track and annually report the types of activities that program participants engage in while receiving minimal cash support. As will be described in detail, this information does not document outcomes. Similar requirements do not currently accompany other assistance programs, such as Medicaid or supplemental nutritional assistance. Rather, the misnamed “work participation” standard requires states to document that program participants are engaged in a minimum of 30 hr per week (35-55 hr for two-parent families) of “core” or “noncore” activities. As we will see, this meticulous tracking has had profound consequence on state activities and local service operations.

Note. TANF = Temporary Assistance for Needy Families; CBO = Congressional Budget Office.

In 2005, when TANF was reauthorized as part of the Deficit Reduction Act, a new performance management regime was initiated, contradicting the conventional ideology of block grants that reflects devolution. Specifically, new federal rules included mandates for states to report the weekly involvement in required activities by program participants (Allard, 2007; Government Accountability Office, 2010). This performance standard is named “work participation” and focuses on documenting process indicators. States must establish a system to track individuals’ activities, some designated as “core,” such as on-the-job training, work experience, or employment (subsidized or unsubsidized) for 30 hr per week. Although program participants may engage in activities proven to lead to longer term economic success, such as education, rehabilitation services, or high school completion, these are “noncore,” and there are explicit disincentives for states to encourage these activities. Other services that participants need to support their job search and maintain employment, such as mental health and chemical dependency treatment, are not tracked. Most significantly, employment and earnings that put people above the program-eligibility level are not tracked as outcomes. When reflecting on the development of the work participation performance regime in 2007, political scientist Scott Allard (2007) wrote, “ . . . these shifts in welfare policy under the George W. Bush Administration will transform the playing field on which state and local government will formulate welfare programs in the coming years” (p. 305). Such performance measures communicate to states that process indicators are more significant than outcomes, such as increased wages, education for better jobs, or higher incomes; they also fly in the face of a well-established body of economic literature (e.g., Autor & Houseman, 2010; Herbst, 2008) and rigorous program evaluations of welfare-to-work programs (Hamilton, 2002).

Yet, there is also a tension between the structure of a flexible block grant and the structure of this federal performance measurement practice. The measurement system is troubled with technical complexity, and requires considerable state resources to operate. Local governments and nonprofit service providers must track and report individual participants’ weekly activity (Indovino, Kodet, Olson, & Streier, 2008). States must institutionalize verification processes to document adherence to the standards throughout their jurisdictions. Based on what is reported, the federal government establishes a “work participation rate (WPR),” for each state based on its investments of state funds and caseload characteristics. Those states not meeting their WPR must pay financial penalties (Congressional Budget Office [CBO], 2015; Falk, 2012). Therefore, the institutional arrangements in the national TANF performance regime challenge the assumption of a block grant funding mechanism by directing state and local service agencies to meticulously document how program participants spend their time rather than documenting outcomes.

In response to this performance regime, some states developed strategies to work around these directives without damaging their overall WPR scores. Some of these strategies included administrative tactics to change which participants are “counted” in their WPR. Others develop unpaid work programs or institute more earned-income disregards to keep employed families on the program. Still, others develop separate state-funded programs for hard-to-serve populations or create screening programs to keep out those with the most serious employment barriers (Hahn & Loprest, 2011; Schott & Pavetti, 2013).

In Minnesota, state policy and management practices challenge the WPR performance regime and attempt to establish an alternative regime, utilizing all these strategies. Minnesota is a county-administered social welfare system; although the state government sets policy directives—such as establishing performance indicators—considerable administrative discretion resides with the 76 local human service departments. Nonprofit employment service providers contract directly with these counties. Minnesota’s history with this program is also significant. In the mid-1990s, the state designed and piloted the Minnesota Family Investment Program (MFIP), which offers various investments to support low-income families toward achieving self-sufficiency: wage supplements, expansive work supports, and extensive employment services. The model, evaluated by MDRC in a randomized control trial, increased employment and earnings among long-term welfare recipients, increased household incomes, reduced poverty, and had a number of positive benefits for children (Knox, Miller, & Gennetian, 2000). As such, it was one of a small number of national innovations under the federal waivers for Aid to Families With Dependent Children to positively improve program participants’ economic conditions (Hage, 2004; Knox et al., 2000; Michalopoulos, 2005).

This successful experience later led state administrators and legislators to develop their own performance standards during the reauthorization of TANF in 2005, explicitly using the block grant flexibility to challenge the national performance regime. In developing their own standard, the state wanted to reflect certain priorities for their state program: deliver “financial incentives and work requirements to assist the most work-ready participants into employment and off cash assistance” and “provides intensive case management to participants with multiple employment barriers so that they can make progress toward self-sufficiency” (Minnesota Department of Human Services [MN DHS], 2003, p. 3). To meet these principles and allow the state to assess its program performance over the long term, administrators created the self-support index (S-SI). The S-SI reflects how many recipients are meeting desired outcomes, either no longer receiving cash assistance or work at least 30 hr a week while receiving assistance. These metrics are reported at 1 year, 2 years, and 3 years after entering the program. The state also establishes a specific S-SI range for each county to meet, based on local economic conditions and caseload characteristics. The measure is longitudinal in nature, focused on desirable outcome of employment. Reporting of S-SI measures for each county began in April 2003.²

Unlike the federal work participation standards, Minnesota’s S-SI recognized program exit and employment as the desired outcomes for each person receiving cash assistance. State administrators clearly saw the measure as means for both supervising administration of the TANF program by the counties and as supporting counties in assessing the effectiveness of their practices (MN DHS, 2009). Beginning in 2006, 5% of counties’ TANF block grant allocation was held back unless the county exceeded the work participation standard or the expected range of the S-SI. Furthermore, in 2013, program managers embedded the S-SI measure into the statewide Human Service Performance Management System. Consistent with other elements of the performance management system, counties that are not meeting the expected range of performance on the measure are now required to develop a “performance improvement plan” with concrete operational activities to improve their indicator. In addition, the state legislature has since removed any direct financial incentives for counties to achieve the federal performance standards. Counties now receive all their TANF allocation with an incentive of a two and a half percent bonus if they exceed their expected S-SI range.

Although the S-SI more accurately reflects Minnesota’s desired outcomes than the TANF work participation standard, its calculation is difficult to explain and difficult to use for nontechnical audiences. State program managers developed additional tools, such as an employability assessment, sponsored training for frontline staff, and even an explanatory video. In addition, although Minnesota provides an alternative measure and implementation resources to support an alternative performance regime, the TANF block grant still imposes the federal directive for states to monitor the WPR performance standard.

Although a performance management system is designed to create a standard of reference for implementers, this research setting reveals that conflicting ideas, interests, and institutional arrangements in these weak regimes also create outcomes. There are both service outcomes—such as the service orientation of staff and customer experiences in offices—and client outcomes captured in the numeric performance measures. Performance measures define what “counts” and creates incentives for people to orient their work in relation to what is recognized and sanctioned. In fact, some scholars have argued that performance management creates operational machinery honed to “enforce obligations and curtail deviance among the poor” in welfare programs (Soss, Fording, & Schram, 2011b, p. i203). Yet, in multilevel implementation systems, a performance regime may by challenged by other units of government. In the Minnesota context, this certainly happened at the state level. But what about local government’s response to these conflicting regimes? This is worthy of focused investigation.

Research Method

In this study, we theoretically sampled 12 counties to be representative of the state’s variety of regions, caseload sizes, and performance on the various performance indicators in use.³ In the full data set, we have data from 27 agencies; some local governments contract with more than one nonprofit to provide welfare-to-work services. The research did not originate with intent to explore the implementation of performance regimes, per se. Our research team conducted site visits to document the implementation of the TANF program across local governments, exploring conditions within the agencies at one point in time (January through March 2015). Within each site, we gathered data systematically from service organizations responsible for providing welfare and welfare-to-work programming. At each site visit, research teams followed clear research protocols to assure comparability of information (Ong and KcKay, 2016; Nightingale & Rossman, 2010).

All team members conducted and recorded semistructured interviews with site managers, supervisors, and frontline staff who were involved in day-to-day delivery of TANF programs, for a total of 136 informants; 44% of those interviewed played managerial or supervisory roles. The interviews focused on describing local office conditions and operations, probing client experience in the office using specific profiles, and documenting relationship with external entities. Across these sites, the interviewees were largely White (84%) and female (79%), reflecting the demographic characteristics of the human service workforce throughout the state. In addition to the interviews, each site-visit team conducted structured observation of setting, space, and frontline management interactions. They also took photographs of site conditions, gathering more than 500 images. Each site-visit team did immediate analysis, summarizing key issues and themes from each agency and local service network in site-visit logs. We gathered administrative data on performance according to the formal indicators during the first quarter of 2015 to correspond to the time fieldwork was completed. During this time, there were no policy changes or events that affected perceptions of implementation and performance regimes.

These multiple sources of information were coded for our exploration of Minnesota’s performance management implementation. Our team began by analyzing the data through deductive coding using NVivo software and analytical matrices (Miles, Huberman, & Saldana, 2013). Table 1 summarizes these 12 counties across several dimensions of county characteristics and implementation conditions. For example, five of the 12 are suburban metropolitan counties, one is a medium metro area, two are small metro areas, and four are rural, varying in political orientation. Although the state’s poverty rate was 11.5%, the counties range from a 5.5% (County B) to 17% (County F). They also vary in terms of their welfare caseloads and means adopted for implementing the mandatory employment services required under TANF. Most counties contract out service provision with one or multiple nonprofit agencies, whereas other counties operate their TANF program themselves. As we will discuss below, our initial analysis focused on trying to apply the elements of regime theory to predict the service approach and success on specific performance measures. In that analysis, we gathered secondary data to supplement our field-based data and deductively coded it into the theoretical constructs of interests, institutional arrangements, and ideas, confirming these codes with the full site-based research teams.

Table 1.

Comparison of Site Visit Counties by Descriptive Characteristics.

County	County characteristics
County	Geographic	Poverty rate	Median household income	Caseload size
A	Suburban large metro	6.0%	US$83,182	>200
B	Suburban large metro	5.5%	US$86,510	<100
C	Suburban large metro	6.0%	US$73,085	>100
D	Suburban large metro	6.2%	US$70,223	<100
E	Suburban large metro	7.3%	US$74,995	>500
F	Medium metro	17.0%	US$47,138	>500
G (Mist)	Small metro	13.4%	US$55,455	>500
H (Potts)	Small metro	9.8%	US$67,089	>200
I	Rural	14.7%	US$47,122	>100
J (Zagimeg)	Rural	11.5%	US$52,043	>100
K	Rural	12.2%	US$46,412	<100
L (Taylor)	Rural	15.7%	US$45,567	>100

Source. Geographic population classification is based on National Center for Health Statistics Urban-Rural Classification Scheme for Counties (2014).

Note. We have used more descriptive labels to add clarity. Poverty and income data are based on U.S. Census Bureau’s 2010 to 2014 calculations, using 2014 U.S. dollars. The state-level poverty rate is 11.5% and median household income is US$60,828.

We also move beyond the variance question, trying to more effectively understand the process at work (Alvesson & Skoldber, 2000; Van de Ven, 2007). We more carefully examined interview data and inductively coded for themes, including managers’ actions, stories of success and failure, consistency and inconsistency in daily activities, and overall program processes. We used memos to document our analysis, paying attention to how themes grouped organizationally. We also held multiple analytical meetings with state agency staff who accompanied us in data collection to check our emerging understandings. We shared the initial descriptive themes with the local organizations within 6 weeks of data collection. The theoretical contribution reported grew from this inductively coded data, as we tried to better understand how people within the organizations responded to the competing performance regimes. Although we conducted in-depth analysis on the full data set, we present here the data from four illustrative counties to make the analytical insights easier to communicate. We select similar counties (in terms of geography and caseload size) that have different outcomes (in terms of service orientation and performance indicator performance) to illuminate how competing performance regimes are reconciled in practice.

Exploring Implementation of TANF Performance Regimes

Before turning to the inductive analysis, we want to recount our exploration of whether the existing constructs of regime theory helps to explain local variation in this case. As we described earlier, two performance regimes developed during TANF policy implementation at the national and state levels that explicitly challenge each other. There are distinct core ideas, political interests, and institutional arrangements at work that are fashioned in internally consistent ways. The national welfare performance regime is held together by the core ideas of personal responsibility and temporary assistance. There are few political interests and, therefore, few challenges to the administrative rules focus on documenting activities, rather than outcomes, under the banner of performance management. Although they contradict the fundamental tenet of block grant flexibility, the institutional arrangements mandate quarterly reporting and fiscal consequences.

In Minnesota, state administrators developed an alternative performance regime, bolstered by a unique experience with prior program success that made salient a different idea of program performance. This idea of self-support was actualized through mobilized interests that developed an alternative measure and invested state resources to assure it would be measured with analytical rigor. They also mobilized disparate political interests through legislative action to embed the alternative measure in the state’s performance management system and create financial incentives for counties showing desired results.

Our analysis explores the operation of these two contradictory regimes and what results in service delivery. It is important to note at the onset that none of the professionals involved in this system challenge the legitimacy or desirability of performance management, generally. As other scholars note (Moynihan, 2008; Radin, 2006), performance standards are understood to be an appropriate tool of public management. In other words, the variation we describe in service conditions or results documented by the measures themselves are not caused by subverted or aborted implementation (Lin, 2000). Yet, our analyses of the 12 representative counties illustrate that performance management in the TANF system is not straightforward.

In the writing about regime theory framework, May and Jochim (2011, 2013) suggest it should provide analytical leverage across levels of government. In Table 2, we present our descriptive findings of our attempts to apply the approach. We classified different relevant factors into the theoretical constructs: interests (% voting for Obama in the county during the 2012 presidential election), institutional arrangements (employment service provision), and ideas (organizational espoused beliefs). We also documented two dimensions of regime outcomes: service orientation and county performance on the two established performance indicators. These measures were developed through both secondary data (interests, performance indicators) and site visits. In classifying the performance indicators, we considered each standard in relation to the expected range of performance as done in administrative practice, either in relation to the whole state (federal WPR) or adjusted for local economic conditions and size (state S-SI). In the site visits, we learned about the form and function of how county offices provided mandatory employment services to TANF program participants. We also drew on interviews and photographs to document how the organizations had developed working ideas about the overall purpose of the program.

Table 2.

Descriptive Comparison of Site Visit Counties by Regime Characteristics and Two Outcomes—Service Orientation and Performance Measure.

County	Regime characteristics			Service orientation	Outcomes
	Interests	Institutional arrangement	Ideas		Performance indicator(first quarter of 2015)
	Votes for President Obama	Employment service providers	Espoused beliefs program purpose		Federal measure (WPR)	State measure (S-SI)
A	49.4%	County provision	Organizational artifacts stress success and diversity	Process accountability	Achieved	Achieved
B	41.5%	County provision	Staff value bureaucratic rules Insulated and oriented internally to county system	Process accountability	Exceeded	Exceeded
C	38.0%	One nonprofit	Rigid, rule following	Process accountability	Failed	Exceeded
D	42.5%	One nonprofit	Unwelcoming; critical signage stresses fraud and use of inappropriate language	Mixed	Exceeded	Exceeded
E	50.4%	One nonprofit and county provision	Preponderance of signs with rules for clients Collocated financial and employment services in various locations across county	Mixed	Exceeded	Exceeded
F	63.5%	Five nonprofits and city provision	Multiple locations, siloed from each other Inconsistent and vague goals visible in artifacts	Process accountability	Achieved	Achieved
G (Mist)	42.8%	One nonprofit	Clear physical separation of services Uniform processing rules for all clients	Process accountability	Exceeded	Failed
H (Potts)	50.2%	Two nonprofits	Customer service mission and language visible Use technology and tools to improve timeliness	Customized	Exceeded	Failed
I	53.7%	Four nonprofits	Sterile and institutionalized office space Rigid, rule following	Process accountability	Failed	Failed
J (Zagimeg)	45.7%	One nonprofit	Flexible with policy to keep clients off WPR Services collocated	Process accountability	Failed	Achieved
K	40.6%	Three nonprofits	Office environment accessible and welcoming to families	Mixed	Achieved	Achieved
L (Taylor)	42.5%	Two nonprofits	Access best practice models and training Value intergovernmental collaboration	Customized	Failed	Achieved

Source. Presidential election results by county are based on “2012 Election Results” from the Office of the Minnesota Secretary of State.

Note. In all, 52.7% of statewide votes went to President Obama. Output data from Quarter 1, 2015 (period of qualitative data collection). Self-sufficiency performance was determined using state performance measure calculations for the Quarter 1, 2015, 3-year S-SI calculation, compared with the calculated expected performance range. Counties performed over, within, or lower than their individual expected performance ranges. All counties’ S-SI values were above the state S-SI (0.69), but S-SI is dependent on local economic factors addressed in the expected range calculation. Workforce participation rate was calculated using the monthly average rates from Quarter 1, 2015. WPR = work participation rate; S-SI = self-support index.

Although there is considerable variation in regime characteristics at the local level, this variation does not relate to either service orientation or performance on the actual measures. Either as individual attributes or in combination, there is no discernible pattern between the characteristics of local regimes and either type of outcome. For service orientation, some counties embody a clear orientation toward customer service, using the resources such as training and assessment tools provided by the state to better customize their service responses to participant needs. Others adhere closely to the directives embodied in the federal work participation standards to assure process accountability for mandated “core” activities. Still others demonstrate attributes that mixed these two approaches. Something other than regime attributes is driving the service orientation being implemented.

There also is not a systematic way to explain how variations in regime characteristics influence ratings on the performance indicators themselves. There is no organized relationship between the dimension of the local regime and these indicators, or even any clear relationship between the competing performance measures. Although a few counties achieve their benchmark on the national WPR and the state’s “SS-I,” there are no commonalities in regime characteristics. The same is true of the counties that fail to achieve either benchmark. What is more substantively disconcerting is the lack of relationship between the indicators themselves. Although some counties that failed to achieve the desired WPR also failed to achieve the S-SI, others achieved or exceeded their expected rates in one measure and underperformed in the other. The variation does not follow any discernible pattern. In fact, when analyzing data summarized in this way, it did not seem there was any way to understanding how the competing regime ideologies at the state and federal levels were reconciled in local service delivery or performance on either indicator. It appeared chaos reigns in the face of two competing performance regimes.

Various Ways of Resolving Ambiguity

Generally, it is not surprising when a public program’s core purpose is contested and competing regimes are developed that local interests, institutional arrangements, or ideas would not be sufficient to resolve them. However, although two contested performance regimes create ambiguity, county governments still employed operational strategies to implement the program in light of performance incentives. This raises the question of how performance regimes actually influence implementers’ understanding of their roles and these operational strategies. To illustrate our exploration of this question, we turn to four counties within our larger data set. Although operating within the same performance regimes, we find these agencies have distinct understandings of the terms of accountability and performance, which creates distinct outcomes in terms of both service orientation and performance standards. In two of the sites, Mist and Zagimeg, managers assure that staff focus their attention on documenting client activity consistent with the directives in the federal work participation standards. The other two, Potts and Taylor, managers reinforce staff activities that respond to the incentives in the state performance regime.

Mist County

Mist County is in the central region, with a mix of a small metropolitan city, small towns, and rural farmland. The small metropolitan area has a city bus system and direct commuter bus and rail connections to the Twin Cities, which is the state’s main economic center. The local economy is strong, based on agriculture, manufacturing, and retail. The main low-skilled employment opportunities are found in local agriculture processing and, in recent years, refugees from Somalia and other African countries have moved into to the county because of these opportunities. In fact, this county is one of the fastest growing in the state.

Mist County Human Services illustrates how a local county government can strongly adhere to the federal work participation performance regime. They work with a large number of TANF participants and invest resources and staff attention on accurately documenting their adherence to the mandated activity standards stressed by the federal regime. For example, county workers do not see their role as assessing client need, but rather, to relegate any notion of responsive customer service to the contracted employment service provider. People are served on a “first come, first served” basis, with no differentiation in terms of responding to crisis or level of need. The two welfare supervisors believe the program does not have the capacity to provide anything more than merely case processing. As Julia, a program supervisor, said, “It’s not our job to have relationships with our clients because that approach brings in all types of personal judgment.” In their opinion, the county should focus its attention on processing case applications and assuring the employment service provider gathers the documentation required by the federal standard. Throughout the site visit, there was virtually no mention of the state’s alternative performance measure.

The nonprofit contracted to provide employment services clearly understands that the county emphasizes standardization and process efficiency; managers see meeting these demands as a top priority. All tasks are to be focused on “making” the federal performance metric, even though many question the effectiveness of this approach when probed. As Barb, one of the employment service managers, reflected in an interview, “The county really focuses on [the federal performance standards] and that’s how they review their documents and contracts [with us].” In fact, the former contracted service provider abruptly lost its contract because of its inability to achieve the work participation standard. Because of this, the current provider does not contest the terms of performance, even though some frontline staff worry about how it influences their ability to work with clients. Clients with job search barriers, such as the African refugees who relocate to this community for agricultural work opportunities, are believed to interfere with efficient case processing and documentation of activities, which are understood to be primary program objectives. The skill deficits of these clients are understood by staff and managers to be the source of the county’s problem in meeting the federal performance standard.

Public managers do not engage with the county board of commissioners (an elected body in Minnesota counties with considerable authority in determining funding levels and programmatic priorities) in local program implementation. Because the terms of performance are not contested, information about the work participation standards is merely included in materials shared with the board and rarely discussed. When asked, supervisors expressed surprise by the idea that board engagement might be more substantive. In their understanding, the board is focused on controlling costs and providing all county human services efficiently; the work participation standards seem to offer a tool consistent with this aim.

Zagimeg County

Zagimeg County is also in the central region, comprised of small towns dispersed across rural farmland. The local economy is based on agriculture, manufacturing, and seasonal recreation. The largest employers of low-skilled jobs are poultry hatching and processing corporations. Public transit is a limited circular with four daily trips between towns. Zagimeg’s employment opportunities have attracted refugees from Somalia and other African countries. Compared with other counties, the TANF program is a moderate size.

Unlike Mist County, staff and supervisors clearly expressed uncertainty about the performance measures to which they were held accountable. County managers want professional discretion for their staff to work with clients and they recognize this is challenged by the measures. They note that the WPR approach overlooks behaviors and successes related to achieving sustained employment. Managers express fundamental confusion about the program goals and strategies that should be instituted, they are not focused on efficient processes. One supervisor, Peggy, concluded,

[the program] is not what it was meant to be. It was an antipoverty program and we encouraged our customers to stay in school. When we changed, we said they could go to school but they have to work too; yet, [when I received assistance] I had a hard time doing that and I had support systems . . . We are setting them up to fail.

Her understanding of reasonable performance goals is rooted in her own experiences.

Although the state’s performance regime (S-SI) is more focused on this type of long-term change, she and her colleagues did not understand it as a viable alternative. The calculation of the S-SI was too difficult to understand. The staff and managers who were interviewed during site visits still believed the county’s financial incentives were to achieve the federal standard, although state policy had changed to provide financial bonuses for achieving the desired state standards; senior managers had not communicated the change. There were many competing messages in the performance regimes, which were difficult to track. Although they were told that the federal measures assure clients’ accountability to the system, supervisors and staff doubt the effectiveness. One frontline worker was blunt in his assessment, “[The federal requirements] are the stick that gets people to move. We need some of that, but as far as what it does for us [employment specialists], it is really nothing.”

Because the employment service provider holds contracts with many other counties, the managers draw on knowledge from these other counties and use it to shape operational practices in Zagimeg County. They efficiently document client activities with standardized paperwork. Yet, there is no illusion that these activities are substantively valuable. Instead, employment services managers encourage staff to use other programmatic options. State policy allows counties to provide a diversionary program designed to provide short-term assistance. In Zagimeg, employment services staff embrace it, and direct clients who can find their own jobs to this option. There is also a state-funded program for unemployable clients developed for families who have adults or dependents with short-term or chronic disabilities. Employment services staff also routinely utilize it for lower skilled clients. Neither state-funded program is measured according to either the federal or state performance measures. As a result, staff systematically direct both clients who are easy to serve and those who are difficult to serve into program classifications that assure they are not counted in performance metrics. This also excludes these clients from any focused employment counseling and appears to be a perversion of the program’s intent; many supervisors and staff complained about this fact. However, they also believe it is necessary if they are to report a WPR without penalty and they settle on operational processes that focus half-heartedly on this accountability.

Although they report a solid relationship with the county board, public managers’ interactions around TANF are transactional, focused on updates on legislative policy changes or work participation metrics included in formal reports. Still, they believe it is important to educate elected officials about how families experience public assistance. The lead manager, Susan, developed an experiential exercise for orienting the new commissioners. Commissioners experience what it is like to apply for the assistance, assuming a family’s circumstances and going through the application process including gathering the paperwork, sitting in the waiting room, and waiting for an eligibility decision. As Susan said, “Most of them are really shocked . . . They learn what is expected in the . . . programs.” Despite signals from both federal and state authorities on performance management, managers want to instill in local decision makers an understanding how complicated the program process is for clients to receive cash support.

Potts County

Potts County is situated in the southern region and has a comparable community size and structure to Mist County, with a mix of small metropolitan city, small towns, townships, and rural farmland. There is a public city bus system and private regional bus lines, but no public transport to the Twin Cities. A strong local economy exists comprised of food processing and agriculture, health care, technology, and hospitality industries. One major challenge for the county’s large TANF program is the local market demand for high-skilled workers, whereas lower skilled jobs are scarce. Like other examined counties, there have been several waves of refugee resettlement, the most recent from East Africa and Eastern Europe.

It is notable how Potts County managers have a fundamentally different interpretation of the performance regimes, compared with Mist and Zagimeg. Although the activities required by the federal performance standards are documented, the managers do not see it as significant in shaping operations or interactions with clients. Instead, they are focused on a different aim. As the county director of family assistance, Rebecca, explained,

We are the safety-net and we want to try to serve. The people coming in are customers, or clients . . . [We know] there is power in our word choice. We serve “customers” and aim to truly and genuinely ask people “what is it that you need?” We have to not assume we know what people need . . . [because] they can come up with surprising answers about what they really need to be successful.

This orientation is reflected in operational choices made by the county and the two contracted employment service providers. For example, managers developed their own process measure of timeliness to assure customer service: The quicker applicants’ cases are opened, processed, and benefits delivered, the more likely they are to find employment and stabilize their family circumstances. In daily operations, this measurement is much more significant than the federal WPR mandate. In addition, contracts enable providers to customize services, with one agency that specializes in working with refugees and immigrants. The county and providers also coordinate their practices to reduce administrative burden for customers. For example, although each organization has distinct information technology platforms, frontline staff at the county and provider agencies are required to check both systems’ platforms for accuracy and to complete necessary documentation in real time. This helps to ensure continuity for clients and avoids trivial sanctions. They also have regular joint meetings in which supervisors help workers focus on the long-term goals, despite the extensive documentation required.

In addition, the customer service orientation informs how the managers work with their county board. Managers work actively with the board to strengthen the program’s relationships and legitimacy using data and presenting the realities of their context to build awareness. Although the state’s self-support measure is difficult to understand, county managers choose to report it to the board to represent performance, rather than the federal standard. When the county dipped below the desired range, they took the opportunity to educate members about the impact of local labor market conditions in its calculation. Given this explanation and knowledge of the organizational commitment to customer service, the board did not question the effectiveness of the contracted providers; instead, it praised the partnerships and quality of services. This is a contradictory strategy and response to underperformance, compared with Mist County’s response.

Taylor County

Taylor County is a rural county located in the north with some comparable features with Zagimeg. There a few small towns and an Indian reservation within its boundaries. A large and diverse American Indian population resides within and outside of the reservation; services to families are affected by jurisdictional contingencies based on household location tribal membership of individuals within the household. A recent county–tribal nation partnership created public transportation to and from the reservation for residents; there is little other mass transit available. The local economy is depressed and dependent on seasonal recreation and tourism. The tension between the residents and vacation home owners is clear; the “city people” do not engage with the community or local economy beyond hiring locals as domestic workers. Like Zagimeg, the county operates a moderately sized TANF program.

Despite the very different environmental context from Potts County, the public managers in Taylor share a similar emphasis on providing customer service. Supervisors are clear in their expectation that services should focus customized interactions to support success, this echoed in the reception room procedures and resources, staff assignments for processing applications, and connecting people to employment opportunities. Although managers recognize both self-sufficiency and efficiency are essential goals, they see neither the federal nor state performance measures as valid measures. They understand that the “structural” barriers to success for clients and the TANF program are the local job market’s reliance on seasonal tourism, multigenerational poverty, and historical trauma experienced by American Indian communities. To resolve the contradiction between local barriers and goals, local managers make sense of their purpose in terms of their values. As Mark, the county director explained, “Nobody wants to be where they have to ask for help. We need to be able to meet those needs in a way that still allows people to retain their respect and dignity.” This ideology does not convert to the type of practice used in Zagimeg, moving hard-to-serve clients to a state program with minimal service. In Taylor County, workers rarely assign clients to that option. They invest in clear communication with the two contracted employment service providers for each client’s individual needs, expedite necessary paperwork, and search for employment.

Like Potts County, this commitment to customized services is repeated by the two contracted providers, one which provides services for enrolled members of local tribes across the region. This provider openly contests the federal standard by refusing to sanction families who do not report their hours; county managers support the decision. The second provider also shares the county’s belief in customer service, yet recognizes other counties it contracts with do not hold this belief. Mark and supervisors have built a strong relationship with the county board, which supports focusing on customized solutions for clients given in the tough economic reality of the region. There is open discussion about the county’s scores on the two measures and shared understanding of the inadequacy of both; the bonus funding attached provides little incentive. The local contextual circumstances create legitimacy for a different path. Managers invest resources in historical trauma training for staff, strategies to expand transportation and education opportunities for clients, and workflows for open communication with providers.

Understanding Local Variation

These four cases exemplify what our in-depth analysis of the 12 counties revealed; there is considerable variation in how federal and state performance regimes are reconciled in daily operations, service networks, and oversight of elected governing boards. To clarify, all counties in this study implement detailed policies on program eligibility and benefit levels, comply with reporting standards of federal and state mandates, and submit required information to relevant authorities. Still, because they work in implementation systems with competing performance management regimes, managers must interpret these regime signals.

Local actors mediate contested performance directives to create daily operations and service orientations. Some local managers, like Julia and Barb in Mist County, develop processes to assure that clients are accountable for daily activities consistent with federal direction. Others, like Susan and Peggy in Zagimeg County, find it difficult to respond because of the conflict between the financial incentives in federal standards and their belief that these activities do not help clients reach successful outcomes. Still others, like Rebecca in Potts County and Mark in Taylor County, focus on longer term outcomes and develop operations appropriate for local conditions to reach their goals. Interestingly, in the counties that carry out customized service orientations, managers developed strong intergovernmental networks, perhaps to guard against any potential backlash that might come from not strictly following federal directives. The conflicting ideas, interests, and institutional relationships in the two regimes land at the feet of local county managers, and require them to develop an understanding of the “real” terms of performance and assemble local resources to support that interpretation. Their discretion is not random, but rather, an integration of personal beliefs, shared organizational values, and a strategic assessment of the context.

This in-depth comparison also suggests the use of performance standards in public management is not always predictable or oriented toward narrow self-interest or market competition. For example, an employment service provider who fails to attain the federal performance standard can have very different consequences. Mist County rescinded its contract with the prior provider and reminds the current provider of this fact; in Potts, the county board praised local leadership and partners for their focus on long-term results and community needs. In daily operations, waiting room procedures must be created, paperwork must be completed, communication with contracted service agencies must occur, and local elected officials must be briefed. Our fieldwork revealed the rationale that guides these activities is developed, not from blind adherence to the incentives of a performance regime, but by local public managers’ interpretations of directives shaped by local context.

As originally passed, TANF had high performance bonuses rewarding states for achieving employment, job retention, and earnings measures. The Deficit Reduction Act replaced these longer term outcomes with process measures that merely document the daily activities of TANF program recipients. Reflecting on the implications of the change, a researcher at the Congressional Research Service wrote in a 2012 report,

The choice of measures can change behavior—in this case, the behavior of those who design and implement state TANF welfare-to-work rules . . . Performance measures can have both intended and unintended effects. Their course creates incentives to states to behave such that they are ‘hitting the target but missing the point. (Falk, 2012, p. 57)

Although true, this interpretation assumes a linear, top-down influence. Emboldened by their own experience with improved client outcomes, Minnesota state leaders developed an alternative performance regime that attempted to focus on “the point.” This resulted in a dual focus across the performance management systems in the state. This research documents the fundamental contradictions in the regimes are resolved by local managers who interpret directives and legitimate certain actions in light of their own local, contextual factors. This allows local service organizations to carry out daily operations in the face of ambiguous performance standards. It also highlights the independence of local public service organizations in social policy implementation (Coburn, 2005; Garrow & Grusky, 2012; Sandfort, 2003; Lin, 2000) even when performance measures are articulated from the top.

Conclusion

Our analysis focused up exploring the utility of a public policy regime theory for understanding performance management across the multiple levels in an implementation system (Sandfort & Moulton, 2015). In the field sites, support for performance management is not contested, even though the terms of performance create inconsistency in important management and policy outcomes. However, the tenets of policy regime theory (May & Jochim, 2013) enable us to see that in TANF policy implementation, a weak national regime enabled state actions that challenged it and created a competing regime. Perhaps it is not surprising that when a public program’s core purpose is contested at the national and state levels, local interests, institutional arrangements, or ideas are not sufficient to resolve them. However, our analysis shows that local service managers play essential roles in mediating the ambiguity created. By investigating what practitioners say and do, and the consequence of that on service and policy outcomes, we see how critical these actors’ interpretations are in shaping the operations of performance regimes in practice (Coburn, 2005; Lin, 2000; Spillane, 1998).

This study moves us one step closer to developing a theoretical account of performance management, a better understanding of how relatively stable systems of formal and informal rules shape operational decisions (Kroll & Moynihan, 2015; Moynihan et al., 2011). This account is consistent with other studies that document that the characteristics of performance regimes matter in how they shape behavior (Charbonneau & Bellavance, 2012; Grubnic & Woods, 2009; Moynihan, 2008). However, we considered the robustness of policy regime theory—which focuses not on what policies say but what they do—to deepen our understanding. In the original articulation of their policy regime framework, May and Jochim (2013) posit that much can be learned through investigating multilevel systems and considering the agency of implementers in shaping regimes. And, we took that charge in this analysis to good ends. Further theorizing about policy regimes should include various levels of analysis and systematic data about the processes underpinning implementation. In this field setting, when there are competing notions of performance, managerial authority matters. However, additional research should continue to explore these dynamics in other social welfare policy domains because of the unique morally and politically charged attributes of these programs (Riccio & Hasenfeld, 1996; Soss & Schram, 2007). However, our findings document that local managers interpret contradiction and shape operational practices to resolve the ambiguity of performance regimes.

Footnotes

Acknowledgements

We would like to thank Erika Martin, Jeanne McGovern-Acuna, Leslie Crichton, and Deborah Schlick for their partnership in the research reported here. In addition, we appreciate the time taken by managers and staff in local service organizations to help us understand their successes and challenges.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Family Self-Sufficiency Research Consortium, Grant Number 90PD0273, funded by the Office of Planning, Research, and Evaluation in the Administration for Children and Families, U.S. Department of Health and Human Services. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the Office of Planning, Research and Evaluation, the Administration for Children and Families, or the U.S. Department of Health and Human Services.

Notes

Author Biographies

Jodi Sandfort is Professor of Public Affairs at the University of Minnesota’s Humphrey School.

Sook Jin Ong is Director of the Future Services Institute, a program at the Humphrey School.

Catherine McKay works at the Minnesota Department of Human Services.

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