Tag: scope management

  • Pro Tips for Planning an Evaluation

    Pro Tips for Planning an Evaluation

    10 Moves That Prevent Scope Creep and Protect Use

    The fastest way to derail an evaluation is to act (and plan) as if you can answer everything. Strong evaluation plans protect use by making smart choices early. They focus on what matters most for the program and the decisions it needs to support.

    Here are ten practical ways to prevent scope creep and protect use:

    1. Start with the end in mind: Be clear about who will use the findings and what they will do with them.
    2. Name the primary users: You can listen widely, but one group typically owns use. Design for them.
    3. Get clear on what success means: If “good” is undefined, you will end up with opinions instead of evidence.
    4. Build a shared program picture: Do not plan around assumptions. Confirm how the program actually operates.
    5. Make the logic visible: A simple program story beats an overbuilt model. Clarity matters more than polish.
    6. Ask fewer, better questions: A short list of high-value questions will outperform a long list every time.
    7. Match methods to questions, not habits: Do not default to what you have always done. Choose what fits what you need to learn.
    8. Use what already exists: Good planning starts with existing data, documents, and routine reporting, then fills gaps thoughtfully.
    9. Protect feasibility and trust: Time, access, burden, and sensitivity are not details. They are design drivers.
    10. Plan for use, not just reporting: Decide early how insights will travel, who will discuss them, and what will happen next.

    AI² Tips: Upgrade Your Evaluation Planning with AI

    AI can help you move faster in the evaluation planning phase. Use it to generate a first draft of evaluation questions, suggest indicator options, or help you populate a draft evaluation planning grid. Then bring your judgment and the people who will use the findings in to refine what truly fits.

    Two guardrails to keep in mind:

    1) Protect confidentiality: Do not paste raw transcripts, identifiable details, or internal sensitive information into public AI tools. Instead, de-identify, summarize, or use a synthetic example, or reserve sensitive work for approved tools and environments.

    2)Treat outputs as drafts: AI can speed up first passes, but you are responsible for what goes into the plan. Review, refine, and validate before anything becomes “final.”