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Developmental Evaluation

Developmental Evaluation
Also known as: DE、Developmental evaluation

Evaluation that supports adaptation during development of an uncertain program through frequent information gathering and reflection. Record what was tried, learned and changed in decisions. [1]

Developmental evaluation embedded-support worksheet — openReferences and checked sections
Difficulty
Advanced
Cost
High
Duration
Illustrative estimate (adjust for scale and staffing): embedded support throughout the program (several months to years), with monthly to quarterly reflection sessions
Content updated: 2026-10-07Source checked: 2026-09-13 (includes AI cross-checking)No documented human reviewIncludes fictional examples

How it works at a glance

Developmental evaluation continuously connects program development and evaluation when solutions and change pathways remain unsettled. It returns information close to the time of implementation and captures emerging challenges and unexpected changes. [1]

Evaluators organize questions, examine evidence from trials and support subsequent judgments. This approach does not suit every program; consider other designs when the purpose is only to assess achievement in an established program. [1]

  1. Decide whether DE is appropriate
  2. Design the evaluator’s role and relationships
  3. Understand the program through a complexity lens
  4. Collect data and make sense of it continuously
  5. Support adaptive decisions
  6. Document learning and move to the next phase
Sequence of implementation steps. See “Implementation steps” for details of each stage.

When to use it and when it is unsuitable

When to use it

  • Evaluating social innovation or new models where objectives themselves may change
  • Multi-agency programs addressing complex social issues such as homelessness or climate adaptation
  • Pilot programs built around experimentation and pivots that need learning and real-time decision support
  • Contexts without a single correct answer where evaluators can serve as thinking partners

When it is unsuitable

  • When design is settled and demonstrating implementation effects for accountability is the main purpose; summative evaluation or rigorous causal inference is appropriate
  • Evaluations requiring evaluators to remain independent and external; DE assumes internal involvement, creating tension with independence

Participants, roles, and deliverables

Participants and roles

An evaluator with complexity and evaluation expertise joins the core team. Outside experts are often involved in periodic reviews.

Main deliverables

  • Program hypothesis map (systems map)
  • Periodic reflection reports
  • Learning summary by phase
  • Recommendations for moving to the next phase

Implementation steps

  1. Decide whether DE is appropriate
    Check whether the program is complex, emergent and innovative. Conventional formative evaluation is more efficient when objectives are clear and methods established.
  2. Design the evaluator’s role and relationships
    Explicitly agree on involvement, including meeting attendance frequency and participation in decisions. Define boundaries maintaining independence as a critical friend.
  3. Understand the program through a complexity lens
    Organize relevant people, organizations, change hypotheses and feedback. Use diagrams and text as needed and update them through learning from implementation.
  4. Collect data and make sense of it continuously
    Collect information on implementation and resulting changes, check its quality and limits, and use it in reflection. Attend both to learning speed and the strength of evidence supporting decisions.
  5. Support adaptive decisions
    Use reflection findings to provide questions supporting modifications, pivots, expansion or reduction. Final program decisions belong to the team and users; evaluators interpret evidence and provide grounded evaluative judgments.
  6. Document learning and move to the next phase
    Document learning, remaining hypotheses, plan changes and reasons. Reconsider evaluation designs according to program maturity and intended use; do not universally require transition to a particular method.

Strengths and limitations

Strengths

  • The only systematic approach to evaluating complex, emergent programs
  • Real-time learning support enables early identification and correction of program failures
  • Embedding the evaluator in the team fundamentally resolves the problem of evaluation not being used in the program

Limitations

  • Requires advanced evaluation expertise and complexity thinking, limiting available practitioners
  • Deep involvement reduces independence and can raise doubts about credibility as rigorous external evaluation
  • Combine with additional evaluation where causal questions or institutional accountability requirements cannot be answered by adaptation records alone.

Common pitfalls

  • Abandoning all indicators and logic because the program is complex, leaving only informal conversation and reflection
  • Evaluators become assimilated into the team and lose critical perspective (going native)
  • Failing to document learning from embedded evaluation allows it to disappear when staff change

Conditions of use and evidence

  • Its main purpose is supporting adaptation and program development under uncertainty, rather than applying to every evaluation. [1]
Fictional example; not actual results

Adjusting participation through short trials

The following fictional example explores whether bookings or drop-in participation are more accessible in a new youth community space.

Element of complexitySpecific manifestation in this programImplications for evaluation
Diverse motivations for useSome want conversation; others want quietAsk separately about different experiences, rather than only average attendance
Changing operating conditionsIntake capacity varies with volunteer numbersAlways record staffing on pilot days

Common errors in judgment

Common mistake

Assuming that changing policy every time constitutes developmental evaluation

How to revise

Record reasons for changes, trial conditions and findings

ReasonEvidence enabling learning from trials is necessary.

Common mistake

Having the evaluator take all operational decisions

How to revise

Separate analytical advice from decision-making roles

ReasonThis maintains responsibility and critical examination despite close involvement.

Organize your thinking by writing

Developmental evaluation embedded-support worksheet

A practical template is available to fill in and print on A4 paper.

Open worksheet

Related practical guides

Theory of change

Related methods

Utilization-Focused EvaluationRealist EvaluationTheory of ChangeOutcome MappingContribution Analysis

References and checked sections

  1. Developmental evaluation
    BetterEvaluation
    Section consulted
    Main text; Purpose; Complexity & uncertainty
    How it relates to the text
    Its main purpose is supporting adaptation and program development under uncertainty, rather than applying to every evaluation.
    Source checked: (includes AI cross-checking)

Editorial and checking information

Content updated: Source checked: (includes AI cross-checking)No documented human reviewIncludes fictional examplesEditorial policy and scope of checkingCite this pageReport a correction

How to cite this page

EvalCompass Editorial Team. “Developmental Evaluation”. EvalCompass, updated 2026-10-07. https://evalcompass.jun-nakatani.com/en/methods/developmental-evaluation/
Add the date you accessed the page. Text created by this site is available under CC BY 4.0. Quotations, external materials, and bundled fonts have their own terms of use. When reusing content, credit the source, link to the license, and indicate any changes.

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Change history
  • — Corrected statements and procedures identified during content checks (U08). Preserved the order, number and labels of input fields and the section structure.
  • — Updated explanations to correspond to the sources and added method-specific fictional completed examples, judgment examples and a change log.