Introduction

Performance measures are tools for managing the performance of an agency, organization, or even a system. Performance measures provide benchmarks about whether or not optimum performance by the criminal justice system (and the entities within it) is being realized and, more importantly, whether the system is achieving what it intends to achieve under the evidence-based decision making (EBDM) framework. The use of performance measures provides a way to understand quantitatively the business processes, products, and services in the justice system. In a nutshell, performance measures help inform the decision making process by ensuring that decisions are based on clearly articulated and objective indicators. Moreover, undertaking and institutionalizing performance measurement throughout the criminal justice system allows policy discussions and decisions to be “data-driven,” which in turn helps build the foundation for additional local evidence about what works.

In general, performance measures for the justice system fall into four categories:

1. Effectiveness and the extent to which the intended outcomes are being produced

2. Efficiency measures that demonstrate whether maximum outcomes are being produced at minimum cost

3. Measures of satisfaction and quality to assess if the right processes are being used and the degree to which there is “satisfaction” with the processes^[1]

4. Timeliness in terms of the extent to which activities or processes occur within predefined time limits

Performance measurement is often confused with program evaluation because both attempt to capture quantitative information about desired goals and outcomes. Some key differences should be noted. First, program evaluation involves the use of specific research methodologies to answer select questions about the impact of a program. Performance measurement, on the other hand, is simply the articulation of performance targets and the collection/analysis of data related to these targets. Second, program evaluation is designed to establish causal relationships between activities and observed changes while taking into account other factors that may have contributed to or caused the changes. On the other hand, performance measurement simply provides a description of a change, but cannot be used to demonstrate causality. Third, program evaluations are usually one-time studies of activities and outcomes in a set period of time, whereas performance measurement is an ongoing process.

As you begin the process of defining performance measures, there are seven rules that need to be kept in mind. Performance measures should be

1. Logical and related to goals

2. Easy to understand

3. Monitored regularly

4. Readily accessible

5. Based on specific benchmarks

6. Quantified and measurable

7. Defined with specific performance targets

Purpose

This starter kit is designed to help jurisdictions understand performance measures and to provide a guide for the development and implementation of performance measures systemwide. Information about the key steps in performance measurement is provided in addition to sample performance measures. It is important to note, however, that performance measures should be locally defined and driven; as such, the sample measures may or may not be relevant in a specific jurisdiction, depending on the focus of the local initiative. Finally, tips are offered for the implementation and use of performance measures.

Participants

Development of performance measures should involve a variety of stakeholders. At a minimum, the leadership of the various components of the justice system, along with some line level representatives, should be part of the process. The leadership can provide the broad systemic perspective about how the system should be performing under an EBDM initiative and how each agency/entity within the justice system contributes to overall system performance. The inclusion of line personnel, however, provides a different level of detail and, to some extent, a reality check about how the system is currently performing and what the capacity is for performance. Participants should also include representation from groups that have an interest in the justice system—city/county government budget officers and managers, health/mental health treatment providers, etc. The community and the media can also be important stakeholders to include as, ultimately, it is through these groups that performance is communicated and legitimacy is established. The point is that for performance measures to have validity (not necessarily in the statistical sense), they must be meaningful for others who judge the performance of the system.

Jurisdictions may wish to consider engaging an outside facilitator with experience in performance measurement to provide guidance and assistance through the process. Local universities are an excellent resource for finding this kind of assistance.

Instructions

To develop and implement performance measures, the stakeholders identified above should undertake four key steps:

1. Identify the goals and objectives of the system under the EBDM framework.

2. Determine what the key indicators of output and outcomes are and what type of data collection will be required.

3. Begin the collection and analysis of the performance measures.

4. Implement a reporting mechanism for communicating performance to stakeholders.

Detailed guidance for each of these steps is provided below.

1. Identify the goals and objectives of the system under the EBDM framework

The first step for articulating performance measures is to define what is meant by “optimum performance,” i.e., establishing harm reduction goals and objectives for the criminal justice system. Several questions can help focus the discussion on what the jurisdiction hopes to accomplish:

• How will the jurisdiction benefit as a whole (i.e., what are the intended harm reduction outcomes)?

• How will the criminal justice system benefit from the movement to an EBDM-based system?

• What is an EBDM system intended to achieve or produce?

• What significant changes does the jurisdiction expect from the implementation of EBDM in terms of system operation?

  • How will the costs to operate the system change?

  • How will case processing change at point of entry into the system, during the adjudication process, while in corrections, and/or at point of release?

  • How will those in the system (victims, witnesses, and defendants) view the process?

  • How will EBDM impact those working in the system?

  • What types of information will convince you and others (including the public and funders) that the system is operating at an optimum level?

  • What types of information will convince you and others that the system is achieving what it is intended to achieve?

The answers to these questions need to then been articulated in terms of quantifiable goals and objectives. It is important to understand that goals and objectives are not synonymous. Goals represent the desired end result of the system. Objectives define the short-term indicators that demonstrate progress toward goal attainment and that describe who or what will change, by how much, and over what period of time. For example, broadly stated, one goal might be that the recidivism rate be no higher than 20%. An objective might be a 5% annual decrease in the percentage of offenders who commit new offenses in a three-year period.

Another important consideration in defining goals and objectives is adherence to the SMART principle:

• Be Specific.

• Make them Measurable (i.e., quantifiable).

• Be Action-oriented.

• Be Realistic.

• Articulate a Time in which the change will occur.

Once goals and objectives have been defined, the stakeholders should compare them to the impacts and outcomes identified in the system-level logic model. Each goal and objective should align with the intended impacts and outcomes articulated in the logic model. Although there does not need to be complete overlap, there should be no contradictions.

2. Determine what the key indicators of output and outcomes are and what types of data collection will be required

The second step in defining performance measures encompasses a number of activities:

• determining what the key indicator data are for each goal and objective;

• identifying where, or if, the data exist and, if not, whether the capacity exists for capturing the data;

• refining the list of performance measures to represent a set of key indicators; and

• establishing performance targets.

Well-articulated goals and objectives should lend themselves nicely to the identification of key indicator data. Using the worksheet in Appendix 1, jurisdictions will need to “break down” the goals and objectives into specific types of data that can be collected. Using the example from Step 1 above, the table below shows the goal, the objective, and the types of indicator data that are needed to measure performance:

As indicator data are being identified, jurisdictions should note if the data already exist; if so, they should identify who “owns” the data and, if not, they should determine whether the capacity for obtaining the data exists. To the extent that data is not already being collected or the capacity to collect the data does not exist, consideration should be given to the relative importance of the indicator. This next step in the process will help refine the list of performance measures.

An ideal performance measurement system must be manageable; as such, the number of performance measures for each goal and objective should be limited. Generally, there should be no more than three or four measures per goal or objective and, in fact, there may be fewer. Jurisdictions should aim to select those measures that are the strongest indicators of performance for which data already exist or for which the capacity for the data to be collected is in place. In refining the list, it is important to consider the following seven questions:

1. Is the indicator logical and directly related to goals?

2. Is the indicator easy to understand (i.e., would a reasonable person agree that the indicator accurately represents what it is intended to measure)?

3. Can the indicator be monitored regularly?

4. Is the data necessary for measurement readily available?

5. Can the indicator be measured against a specific benchmark (i.e., is there a baseline against which performance can be assessed)?

6. Is the performance indicator quantified and measurable?

7. Can specific performance targets be set for the indicator in question?

The question of performance targets is a particularly important one and requires more than a simple “yes/no” answer. As the list of measures is refined, jurisdictions should begin thinking in terms of what the specific performance targets should be. In other words, what is the “magic number” that demonstrates optimum performance? For example, if the intent is to implement pretrial risk assessments in order to decrease jail operating costs, the performance target might be that 90% of release decisions are consistent with assessment results. The logic model may provide some guidance in answering this question.

3. Begin the collection and analysis of the performance measures

Because performance measurement is an ongoing process, it is important to have a well-defined data collection plan in place prior to the actual collection of data. As shown in Appendix 2, the data collection plan should include the following:

• data source: the name of the agency/person responsible for collecting the data and, if the data is already being collected, the name of the report or system from which the data is drawn; and

• frequency of data collection: how often the data will be collected.

Once the data collection plan has been agreed upon by the key stakeholders and the agencies/persons that will be responsible for collecting the data, the jurisdiction should collect baseline data for each performance measure against which progress can later be measured.

It is rare that the data in raw form will be sufficient for assessing performance; quantitative analysis of the data is generally needed. The quantitative analysis will require basic statistical calculations such as ratios, percentages, percent change, and averages (mean, median, or mode). In some instances, depending on the measures selected, more complex statistics will be necessary and may require the involvement of persons with statistical analysis experience. Employees in the city/county manager’s offices may be resources, or even employees within criminal justice agencies that have analysis units. Local universities are also good resources for statistical analyses.

Sample Measures

The actual performance measures selected by the jurisdiction should be reflective of the goals and objectives that the stakeholders have identified as part of the EBDM initiative. The following list of possible performance measures are provided for illustrative purposes only:

• XX% of low risk arrestees cited and released

• XX% of defendants screened with a pretrial risk assessment tool

• No more than XX% cases resulting in deviations for pretrial release from risk assessment results

• XX% of jail beds occupied by low risk defendants awaiting adjudication

• XX% of defendants/offenders with low risk assessment scores placed in diversion programs

• Risk assessment information provided to judges in XX% of cases

• XX% of cases in which sentencing conditions align with assessed criminogenic needs

• XX% of offenders placed in interventions specifically addressing assessed criminogenic needs

• XX% of offenders who commit new offenses in a three-year period

• XX% of victims who report satisfaction with the handling of their cases

4. Implement a reporting mechanism for communicating performance to stakeholders

Once the performance data is collected and analyzed, it should be reported to stakeholders in a clear and easily understood manner. Although there is no wrong or right way to report data, the following list of reporting formats should be considered:

• Whenever possible, use graphic displays such as tables, bar charts, pie charts, or line charts.

• In graphic displays, provide legends and labels to clearly identify the information.

• Take care not to present too much information in a single graphic display.

• Use short narrative descriptions to help the audience interpret the data.

• Present both the performance measure (the target) (e.g., risk assessments provided to judges in 90% of cases) and the actual score (risk assessments provided to judges in 75% of cases).

• Provide context for the interpretation that might include discussion of why performance targets were or were not met, how the current performance period compares to previous performance periods, or what recommendations for performance improvement can be made.

Jurisdictions should also establish a regular mechanism for communicating and discussing performance that includes target dates for the release of information. Possible mechanisms include

• publication of a “scorecard,” “report card,” or “dashboard”;^[2]

• monthly, quarterly, or annual reports; and/or

• performance meetings with stakeholders.

Tips

• In deciding on the final list of performance indicators, make sure they are the best indicators of performance related to the specific goal or objective. Don’t “settle” on the easy indicators; instead, work toward a set of indicators that will provide the most compelling evidence of performance.

• Make sure that indicators are clearly defined (e.g., how is recidivism being defined, or what constitutes a case—a defendant, a charge, or a case number?) and that there are specific guidelines in place for their collection. Refer to Appendix 3 for a list of definitions that you might draw from or at least use as a starting place for the development of your own definitions. It does not matter whether you use the provided definitions or definitions of your own. What matters is that your team agrees that these are the right terms and agrees on their meanings.

• Consider “pilot testing” the performance measures by doing a preliminary data collection, analysis, and reporting to ensure that the data is interpreted consistently and that the performance measures actually measure what they are supposed to.

• When data is being collected from multiple sources, consider the use of Memoranda of Understanding (MOUs) or some other form of agreement to ensure that it will be collected and reported in the manner specified and within the established time frames.

• Use the performance measures to inform decision making. Where performance is lacking, dig deeper to understand why optimum performance is not being met and then make the appropriate adjustments.

Example:
Milwaukee County, Wisconsin,
EBDM Initiative Monthly Project Dashboard
(A Work in Progress)

In addition to developing a scorecard to communicate to the public its progress in reaching its harm reduction goals, Milwaukee County’s policy team is also developing a dashboard for use by its policy team and its more immediate stakeholders involved in the EBDM initiative.

The dashboard will serve as a managerial tool that provides a quick snapshot of the County’s progress towards its short-term goals.

Example:
Milwaukee County, Wisconsin, Harm Reduction Goals and Objectives

Goal: Reduce by 25% the number of people with mental health needs who lose their benefits due to being jailed or losing housing, and increase by 25% the number of individuals with mental health needs who are reconnected, within 20 days of arrest, to the services they require.

Measures:

• Percentage of MPD officers with CIT training

• Percentage of chronic consumers identified

• EDs for CCs

• Aggregate cost of EDs for CCs

• Number of CCs in special needs pod

• Aggregate cost of housing CCs in special needs pod

Goal: Safely release and/or supervise 15% more pretrial detainees in the community rather than in jail, generating at least $1,000,000 in savings that can be reinvested in the community and, at the same time, reduce by at least 40% the already low rates at which defendants waiting for trial fail to follow pretrial rules.

Measures:

• Percentage of defendants considered for bail who are screened

• Percentage of cases in which bail = Praxis recommendation

• Pretrial jail bed days

• Average length of stay

• Average daily population (pretrial)

• FTA rate

• Rearrest rate

Goal: Divert or defer prosecution in 10% more cases than we do currently, holding offenders accountable, compensating victims, and reducing recidivism, while generating at least $350,000 in savings that can be reinvested in the community.

Measures:

• Diversions/DPAs screened annually

• Diversions approved annually

• Diversions successfully completed annually

• DPAs approved annually

• DPAs successfully completed annually

• Jail bed days avoided by successful diversion

• Jail bed days avoided by successful DPAs

• Arrests resulting in new charges during diversion period

• Arrests resulting in new charges during DPA period

Goal: Demonstrate in a pilot project that by terminating probation as soon as an offender in need of treatment has received sufficient treatment, we can cut the cost of probation by at least 50% and at the same time reduce probation recidivism by 50%.

Measures:

• Diversions/DPAs screened annually

• Diversions approved annually

• Diversions successfully completed annually

• DPAs approved annually

• DPAs successfully completed annually

• Jail bed days avoided by successful diversion

• Jail bed days avoided by successful DPAs

• Arrests resulting in new charges during diversion period

• Arrests resulting in new charges during DPA period

Additional Resources/Readings

Boone, H. N., Jr., & Fulton, B. (1996). Implementing performance-based measures in community corrections (NCJ 158836). National Institute of Justice Research in Brief. Retrieved from https://www.ncjrs.gov/pdffiles/perform.pdf

Boone, H. N., Jr., Fulton, B., Crowe, A. H., & Markley, G. (1995). Results-driven management: Implementing performance-based measures in community corrections. Lexington, KY: American Probation and Parole Association.

Bureau of Justice Statistics. (1993). Performance measures for the criminal justice system. Retrieved from https://www.bja.gov/evaluation/guide/documents/documentI.html

Dillingham, S., Nugent, M. E., & Whitcomb, D. (2004). Prosecution in the 21^st century: Goals, objectives, and performance measures. Alexandria, VA: American Prosecutors Research Institute.

Hatry, H. P. (2007). Performance measurement: Getting results. Washington, DC: Urban Institute Press.

Hoyle, B. (2011). Dashboards help lift the ‘fog of crime.’ Retrieved from https://docplayer.net/13839392-Dashboards-help-lift-the-fog-of-crime-by-chief-bence-hoyle.html

National Center for State Courts. CourTools. Retrieved from https://www.courtools.org/

National Research Council. (2003). Measurement problems in criminal justice research. Washington, DC: National Academies Press.

Pennsylvania Commission on Crime and Delinquency: Office of Criminal Justice Improvements. Criminal justice performance measures literature review calendar years: 2000 to 2010. https://www.jrsa.org/pubs/sac-digest/documents/PA_PerformanceMeasures.pdf

Rossman, S. B., & Winterfield, L. (2009). Measuring the impact of reentry efforts. Retrieved from https://cepp.com/wp-content/uploads/2015/12/Measuring-the-Impact-of-Reenty-Efforts.pdf

Appendix 1:
Performance Indicator Worksheet

Appendix 2:
Data Collection Plan Worksheet

Appendix 3:
Sample Glossary of Criminal Justice Terms

This glossary defines key terms that are commonly used in the criminal justice field.^[3]

• Community corrections: The supervision of offenders in the resident population, as opposed to their confinement in secure correctional facilities. The main types of community corrections supervision are probation, parole, and pretrial. Community corrections is also referred to as community supervision.*

• Cost analysis: A type of economic analysis that provides a complete accounting of the costs related to a given policy or program. Cost analysis offers the most rudimentary cost information required by both decision makers and practitioners, and also serves as the foundation of all other economic analyses.^[4]

• Criminogenic: Attributes of offenders that are directly linked to criminal behavior, have predictive qualities (of a new offense), are dynamic or changeable in nature (such as employment and peer interaction), and therefore can be influenced through circumstances, programming, or changes in an offender’s attitude.

• Data: A collection of observations or statistics used to measure and analyze interventions.

• Data-driven: The use of regular and ongoing data collection and analysis to track performance and inform policy and practice.

• Defendant: A person who has been formally charged with a crime.

• Direct expenditure: All expenditures except those classified as intergovernmental. It includes "direct current expenditure" (salaries, wages, fees, and commissions and purchases of supplies, materials, and contractual services) and "capital outlays" (construction and purchase of equipment, land, and existing structures). Capital outlays are included for the year when the direct expenditure is made, regardless of how the funds are raised (for example, by bond issue) or when they are paid back.*

• Evidence-based: Conclusions drawn from rigorous research studies that have been replicated numerous times with defined, measurable outcomes about the effectiveness of an intervention or process.

• Failure to appear: A defendant’s absence for a scheduled court hearing when the defendant was notified in advance and deemed able to attend the hearing (e.g., the defendant’s absence was not a result of being held in confinement and not transported from jail to the hearing, hospitalized, etc.); “absence” from the hearing is defined as having not attended at all while court is in session (vs. late for the hearing).

• Goal: The desired long-term result of an effort.^[5]

• Incarcerated population: The population of inmates confined in a prison or a jail. This may also include halfway houses, boot camps, weekend residential programs, and other facilities in which individuals are confined overnight.*

• Institutional corrections: Secure correctional facilities. There are many different types of correctional facilities, operated by different government entities. Local jails are operated by county or municipal authorities, and typically hold offenders for short periods, ranging from a single day to a year. Prisons serve as long-term confinement facilities and are usually administered by the 50 state governments and the Federal Bureau of Prisons. Private correctional facilities also operate under contracts for a wide variety of local, state, and federal agencies. Other correctional facilities are operated by special jurisdictions, such as the U.S. Armed Forces, U.S. territories, and federal agencies such as Immigrations and Customs Enforcement (ICE).*

• Jurisdiction: A unit of government or the legal authority to exercise governmental power. In corrections, it refers to the government (state, federal, local, or tribal) that has legal authority over an inmate. Prisoners under a given state's jurisdiction may be housed in another state or local correctional facility.*

• Objective: Measurable, short-term indicators or benchmarks that indicate progress toward a goal is being made.^[6]

• Offender: A person convicted of a criminal charge.

• Offense: An act or actions that constitute a violation of one or more criminal statutes. Such actions may result in an individual being charged and prosecuted, and result in a court disposition. Some offenses may not result in formal charges and may result instead in dropped charges, referral to a precharge diversion program, etc.

• Operational capacity: The number of inmates that can be accommodated based on a facility’s size and space distribution, staff, existing programs, and services.*

• Performance measure: A quantifiable measure that is used to assess whether or not optimum performance is being achieved and to identify where adjustments in performance or strategy are necessary.

• Recidivism: A measure of failure of an individual or group of individuals who have been or are under criminal justice authority. Individuals who have been charged with any new offense in any jurisdiction that proceeds past a probable cause hearing are considered to have “recidivated” unless those individuals are subsequently determined to be “not guilty.”

• Research: The systematic collection and analysis of data, using scientific methods, to study the effect of an intervention.

• Technical violation: A finding that an individual has not complied with a court-ordered condition (or, if this authority is delegated by the court to another entity such as pretrial justice or community supervision, a condition established by this entity) that does not constitute a new criminal offense. For the purposes of this definition, a finding of a positive (“dirty”) urine test is (or is not) considered evidence of the commission of a new criminal offense.

• Victimization: The effect of a crime on an individual person or household. For personal crimes, the number of victimizations is equal to the number of victims involved. The number of victimizations may be greater than the number of incidents because more than one person may be victimized during an incident. For household crimes, each crime is assumed to involve a single victim, the affected household.*

• Victimization rate: A measure of the occurrence of victimizations among a specified population. For personal crimes, this is based on the number of victimizations per 1,000 residents age 12 or older. For household crimes, victimization rates are calculated using the number of incidents per 1,000 households.*

• Violation (any type): A finding that an individual has not complied with a court-ordered condition (or, if this authority is delegated by the court to another entity such as pretrial justice or community supervision, a condition established by this entity).

• Violation (new crime): A finding that an individual has not complied with court-ordered conditions of community release by being arrested for (or being found guilty of) the commission of a new crime that occurred after being placed on supervision.

Glossary of Cost-Benefit Terms

This glossary defines key terms that are commonly used in the field of cost-benefit analysis. These terms are taken in whole from the Cost-Benefit Knowledge Bank for Criminal Justice (CBKB)^[7].

Average costs:

Total cost divided by the quantity of output. For example, the average cost of probation is calculated by dividing total probation department expenditures by the average probation population. See also marginal costs.

Benefit-cost analysis (BCA):

Refer to cost-benefit analysis (CBA).

Benefit-cost ratio (BCR):

A common means of reporting CBA results that is calculated by dividing total benefits by total costs. If the ratio is greater than one, it means that the benefits outweigh the costs. If it is less than one, then the costs outweigh the benefits. If it is equal to one, then the costs equal the benefits and the initiative breaks even.

Capital cost:

The cost of purchasing and/or developing tangible property, including durable goods, equipment, buildings, installations, and land. This cost includes any interest paid on the funds borrowed to finance a capital expense.

Contingent valuation:

A method that uses surveys to estimate the monetary value of something that is not commonly traded in the marketplace, such as environmental preservation or crime reduction. For example, a contingent valuation survey might ask individuals what they are willing to pay for a reduction in crime.

Cost analysis:

A type of economic analysis that provides a complete accounting of the costs related to a given policy or program. Cost analysis provides the most rudimentary cost information required by both decision makers and practitioners, and also serves as the foundation of all other economic analyses.

Cost-benefit analysis (CBA):

Also known as benefit-cost analysis (BCA). A type of economic analysis that compares the costs and benefits of policies and programs over a long-term period. The hallmark of CBA is that both costs and benefits are monetized, permitting the comparison of initiatives with different purposes and outcomes.

Cost-effectiveness analysis (CEA):

A type of economic analysis that compares the costs relative to the outcomes of programs and policies. Cost-effectiveness analysis indicates which option produces a desired outcome for the lowest cost.

Cost-of-illness approach:

A method that measures tangible victim costs, such as medical costs and lost earnings, using information from hospital databases and typical salary rates.

Direct costs:

Costs that are directly related to a specific activity. General categories of direct costs include but are not limited to salaries and wages, fringe benefits, supplies, contractual services, travel and communication, equipment, and computer use.

Fiscal impact analysis:

A type of economic analysis that comprehensively examines all governmental costs and savings that will result from a proposed policy or program. Referred to as a “fiscal note” when prepared by legislative staff to report the impact of draft legislation on the government budget.

Hedonic valuation:

A technique to estimate the dollar value of items that are not commonly traded in the marketplace by measuring their impact on the prices of other goods and services. Hedonic valuation can be used to estimate the value of crime by measuring how changes in crime rates affect local property values, for instance.

Indirect costs:

Also known as overhead. Indirect costs refer to central administrative expenses, such as accounting and legal services, that are necessary for the continued functioning of an organization but cannot be directly allocated to a specific activity.

Intangible costs:

Costs that cannot be measured directly in dollar terms. Examples of intangible costs include pain and suffering and lost confidence in the justice system.

Jury-compensation method:

A method to estimate the intangible costs of crime using the money awarded to victims by juries.

Marginal costs:

Used to describe the costs that are incurred because of changes in units of activity at the margin of an existing level of operation. Short-term marginal costs include those costs that change with a slight change in units of activity. Long-term marginal costs are costs that change as a result of more substantial changes in activity. Marginal costs are generally a more accurate measure to use in a cost-benefit analysis than average costs. See also average costs.

Monetize:

To convert something, for instance, program outcomes or intangible benefits, into dollar terms.

Net benefits:

Total benefits minus total costs. The net benefit is a common means of reporting CBA results.

Overhead:

Refer to indirect costs.

Per diem rate:

A daily allowable expense rate, for example, the daily rate for keeping people in prisons or jails.

Regression analysis:

A statistical technique used to model how changes in one or more variables, called independent variables, affect changes in a variable of interest, called the dependent variable. In CBA, this technique can be used to estimate marginal costs.

Tangible costs:

Costs that can be measured directly in dollar terms. Tangible costs to crime victims include medical expenses, property damage and loss, and lost wages.

Victim costs:

The monetary value of the physical, psychological, and financial harms experienced by crime victims. Victim costs typically include tangible and costs.

[1] Satisfaction can be measured on different levels but generally represents the satisfaction of justice system “consumers” such as victims, witnesses, and defendants. However, in certain instances, it may be desirable and important to measure satisfaction among those working in the justice system.

[2] For more information on developing a scorecard, see 6b: Developing a Systemwide Scorecard.

[3]Definitions noted with an asterisk (*) are drawn in whole or in part from BJS’s terms and definitions: http://bjs.gov/index.cfm?ty=tda.

[4] Cost-benefit analysis and cost effectiveness analysis are two types of cost analyses. See the glossary below for additional terms related to cost-benefit analysis.

[5] For purposes of this initiative, “goal” is synonymous with the term “impact” in the logic model.

[6] “Objective,” as it is used here, is synonymous with the term “outcome” in the logic model.

[7] See https://www.vera.org/research/making-sense-of-the-bottom-line-a-guide-to-reading-cost-benefit-analysis.