2. Collect Data

This play helps organizations measure what truly matters for young adults: outcomes that reflect their growth, opportunities, and well-being. By co-defining success with participants, selecting practical indicators, collecting data ethically, and embedding continuous learning, programs can make clear, actionable decisions. The focus is on using credible data alongside young adult voices to improve participation, skill development, job and education outcomes, and the quality of relationships and support while keeping evaluation lightweight, equitable, and directly useful for program improvement.

Jump to: Takeaways

Who is this play for?

image of 2 team members. should have a comic book effect and afrofuturism graphics effect

Organizational Leaders

image of what a youth organization staff member who is a person of color and has a comic b

image of an office worker. should have a

Young Adult Employers

Why this
matters:

Clear priorities

help teams focus effort where impact matters.

Structured planning

turns ideas into action with realistic timelines.

Breaking down change

makes complex improvements achievable and sustainable.

Thoughtful pacing

prevents harm while strengthening outcomes for participants.

Put it into action

Co-define “success” with young adults, then map it with a simple logic model.

Start by asking participants and frontline staff what a “good outcome” looks like in the short term (weeks to months) and longer term (6–12 months). You’ll hear goals that go beyond placement—e.g., consistent attendance, completing a credential, better transportation stability, feeling welcome, having a mentor, or landing a quality job (enough hours, predictable schedule, decent pay, benefits). Capture these as plain-English outcomes alongside any funder requirements.

Convert that shared understanding into a one-page logic model: inputs → key activities → outputs → outcomes (short, intermediate, long). Keep it simple and phone-friendly. This gives you a shared map for choosing indicators and avoiding “metric sprawl.” For step-by-step templates, see the W.K. Kellogg Foundation Logic Model Guide and examples you can adapt: https://www.wkkf.org/resource-directory/resources/2004/01/logic-model-development-guide.

If you want young adults to co-create the map, draw from participatory evaluation guides in the Memphis YPAR Collaborative and youth.gov’s Positive Youth Development resources:

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Choose right-sized indicators that blend credibility and practicality.

Pick a small set (8–12) of indicators you can collect well and use often.

Combine:

Participation & progression: enrollment, attendance, retention, on-time milestone completion, measurable skill gains.
Education & employment outcomes: credential attainment; employment/education in Q2 and Q4 after exit; median earnings. (These mirror WIOA Youth measures and make external reporting easier: https://www.dol.gov/agencies/eta/performance/wioa-performance.)
Job quality: hourly pay, hours/week, stability, benefits, schedule control; the Aspen Job Quality Tools Library offers practical rubrics and employer conversation guides: https://www.aspeninstitute.org/programs/job-quality-center/job-quality-tools-library/.

Program quality & belonging: perceptions of safety, welcome, adult support, and voice; the Youth Program Quality Assessment (YPQA) provides validated observation and self-assessment tools: https://forumfyi.org/weikartcenter/.

Right-size your ambition. If a measure requires heroic effort to collect every month, replace it with a proximate indicator you will track and use.

3) Collect data ethically, equitably, and in ways that fit real life.

Use mixed methods: quick mobile surveys (attendance barriers, satisfaction), structured observations (YPQA), and short interviews or “story cards” that capture context. Disaggregate results by race/ethnicity, age, gender, ZIP, and caregiver status to spot inequities; then review them with youth to shape responses. Build consent and dignity into your process—explain what you collect, why, and how you’ll protect it. The American Evaluation Association’s Statement on Cultural Competence and the We All Count data equity framework offer practical checklists: https://www.eval.org/About/Competencies-Standards/Cultural-Competence • https://weallcount.com/.

Train staff on trauma-informed data collection (e.g., opt-out options for sensitive questions, “why we ask,” and no-surprises surveys). Brief, free primers from the National Child Traumatic Stress Network can help you align scripts and consent language: https://www.nctsn.org/trauma-informed-care. If you track staff wellness (to prevent burnout), consider the ProQOL self-assessment and pair it with debrief routines: https://proqol.org/.

Build a 60-day learning rhythm: small tests, data walks, and visible changes.

Move from annual reports to continuous improvement. Use a simple Plan-Do-Study-Act (PDSA) cadence: pick one change (e.g., text reminders, earlier office hours), test for 2–4 weeks, review the data/stories, and decide whether to scale. The Institute for Healthcare Improvement offers clear PDSA how-tos that apply well outside healthcare: https://www.ihi.org/resources/Pages/HowtoImprove/default.aspx. The Carnegie Foundation also has accessible improvement science primers: https://www.carnegiefoundation.org/topics/improvement-science/.

Interpret results with participants. Run quarterly youth-led data walks: print a few key charts, ask “What do you see? What explains it? What should we try?” This practice shifts feedback from complaint to co-design and surfaces practical fixes quickly. A how-to is available from the Urban Institute: https://www.urban.org/research/publication/data-walks-innovative-way-share-data-communities. Close the loop publicly each month with a short “You Said / We Did” update.

Tell a balanced story—and use it to make decisions.

Pair numbers with narratives. Report outcomes (e.g., retention + credential attainment + job quality) alongside two or three short participant stories that show how changes happened. For choosing and collecting credible stories, see Most Significant Change technique overviews and toolkits at BetterEvaluation: https://www.betterevaluation.org/en/plan/approach/most_significant_change. Always obtain consent and protect identities if sharing publicly.

Make decisions from the evidence. For example, if disaggregated data shows lower completion for a subgroup, test an intervention (bus passes, morning cohorts, on-site childcare referrals) and track the effect. If job quality lags in certain sectors, adjust employer outreach and coaching targets using the Aspen job-quality tools . Summarize what you’ll keep, change, and stop doing—and share that back with staff, youth, and partners so everyone can row in the same direction.

Takeaways:

Co-define success with young adults – Engage participants and staff to identify meaningful short- and long-term outcomes and map them in a simple logic model.
Track practical, actionable indicators – Focus on a manageable set of measures across participation, education/employment, job quality, and program experience.
Collect data ethically and equitably – Use mixed methods, disaggregate by demographics, and ensure transparency, consent, and trauma-informed practices.
Use data to drive improvement – Interpret results with youth, run small tests, share insights, and make evidence-based changes to strengthen programs.

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What's next

Final Module

3. Prioritize Findings