Introduction to Performance

Information

The City’s performance management work and reporting intends to answer the following questions:

  • What do we intend to accomplish?
  • What did we accomplish?
  • How efficiently did we accomplish it?
  • What impact did our accomplishments have on Portland communities, in particular, Black, Indigenous and other Communities of Color, and those with disabilities?

Logic Model

This logic model is a representation of the way we expect a program or service to work: it explains how we intend to use our resources to reach a desired outcome.

Our logic model is circular to highlight the iterative nature of performance management: we should constantly be reassessing our approaches (i.e. our inputs and outputs) as we are learning if we are achieving our intended results (i.e. getting efficiency, quality, or outcome data).

CBO Logic Model: Input > Output > Outcome meaures pictured in a loop. Efficiency measures are pictured connected to Input and Output, and Quality is pictured connected to Output. Contextual measures surround all other measures.

Types of Measures

Input

Inputs measure the number of staff, resources, or requests to produce an output. They typically measure either:

  • Demand or need, which is the externally driven quantity of work coming in such as requests, calls, applications, etc.; or
  • Resources, which is internally driven quantity of resources we invest such as budget or staffing.

Output

Outputs measure the quantity of work “produced”. They answer the question: “How much did we do?” Outputs are activity-oriented and usually under managerial control. They typically measure:

  • Activities, such asnumber of people served, number of cases processed, number of buildings serviced, number of items repaired, etc.

Efficiency*

Efficiency measures are a comparison of inputs used to produce an output. They tell at what cost the units were produced, typically in terms of either:

  • Monetary value,such as average cost per item repaired (in dollars), median per person served, etc.; or
  • Time or staff time, such aspeople served per hour, buildings serviced per FTE, cases processed per staff hour, etc.

* We urge careful consideration of the use of efficiency measures for programs with equity impacts.  For example, an efficiency measure such as cost of service may encourage focus on the cheapest outreach and engagement option for a program, as opposed to the most inclusive option.

Quality*

Quality measures are a comparison of specific outputs to total outputs and help us answer the question: “How well did we do our work?”. They tell us how much of our work meets certain criteria as determined by a program goal, policy, professional standard, etc. Quality measures can focus on, but are not limited to measures around:

  • Timeliness, such as thepercentage of cases processed within 30 days, calls answered within 20 seconds, etc.;
  • Inclusiveness, such as the percent of participants who identify as BIPOC, percent of applications from households under 150% of area median income, etc.;
  • Completion, such as the percentage of employees that completed training; or
  • Availability, such as thepercentage of system up-time.

Outcome

Outcome measures show the impact of our programs and services by answering the question “Is anyone better off?”. They can help show if we are achieving the intended results as stated in mission statements, strategic plans, City Core Values, program goals, and other similar documents. External forces, such as those tracked by contextual measures, can limit managerial control. Outcome measures can be:

  • Proxies for hard-to-measure outcomes, such aspercentage of Portlanders who rate the city’s streets and public spaces as clean (as a proxy for amount of trash and graffiti), the City’s unlimited tax General Obligation bond rating (as a proxy for sound fiscal management), etc.
  • Short-term results critical to bureau operations, such as response times to high-priority incidents, number of cases cleared, percentage of people connected to health services, customer service rating, etc.
  • Long-term circumstances, such as number of people who had an increase in earnings after program participation, the homeownership rate for BIPOC households, etc.

Contextual

Contextual measures speak to larger external forces that influence outcomes in Portland. These are tracked if they provide information that helps us understand broader trends and their potential local impacts.

  • Societal factors, such as population growth, migration, metro area demographics, etc.
  • Economic factors, such as inflation, interest rates, commodity prices, etc.
  • Environmental factors, such as wildfires, extreme weather events, etc.
  • Legal, political, and institutional factors, such as state and federal laws, healthcare system, education system, etc.