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Impact & KPIs

This page documents Boot Up's measurement approach and Year 1 targets. The honest framing matters.

Year 1 numbers are planning hypotheses, not commitments

[HYPOTHESIS] All Year 1 targets below are planning goals derived from blueprint estimates. They are not promises to funders, not predictions, and not validated yields. They represent what a successful first year could look like at the scale the program is designed for. Real outcomes will be measured against these targets and reported honestly — including when the program falls short.

Year 1 targets

Metric Year 1 target Status
Laptops collected & processed 100 [HYPOTHESIS]
Devices awarded to graduates 75 [HYPOTHESIS]
Participants enrolled in seminars 150+ [HYPOTHESIS]
Partner organizations active 6 [HYPOTHESIS]
Graduation ceremonies held 4 (quarterly) [HYPOTHESIS]
Marginalized workers trained in hardware tech 10+ [HYPOTHESIS]

The 75/100 ratio is intentional: not every donated device becomes an award unit (some are parts-donors, some non-recoverable, some loaners or training units). A 75% award yield is the planning hypothesis; actual yield depends on donor mix and device quality.

The 150/75 ratio is also intentional: not every enrolled participant completes a track. A 50% completion-to-enrollment ratio is the planning hypothesis.

What we will actually measure

Pipeline metrics (operational): devices received per month by donor type; triage outcomes (A/B/C grade distribution); repair cycle time (collection to award-ready); per-device wipe certificate issued (target: 100% of devices containing data); device disposition (awarded / parts / recycled).

Cohort metrics (program): enrollment per cohort by partner and audience; session attendance; module completion; track completion (Starter / Full / Youth / Seniors / Mentor Grad); time to completion per track.

Workforce metrics (people): Hardware Trainees enrolled; trainees reaching paid status; trainees exiting to external employment; Peer Instructors trained; Peer Instructors actively teaching.

Follow-up metrics (outcomes) — the metrics that matter most and are hardest to measure honestly: a 3-month post-award check-in (is the device working and used?); a 6-month voluntary survey (confidence, skills used, employment status where relevant); a 12-month alumni event for informal long-term data.

[HYPOTHESIS] Self-reported outcomes from these follow-ups will tend to overstate program benefit (response bias — people who had positive experiences are more likely to respond). Acknowledge this in any reporting; supplement with partner-org data where possible for cross-validation.

What we will not measure (or claim)

  • "Lives changed" — not a measurable claim; keep it out of funder materials.
  • Recovery outcomes — Boot Up is not a recovery program; we do not measure relapse or claim contribution.
  • Recidivism reduction — not claimed without longitudinal partnership with researchers who can actually measure it.
  • Income increase — too many confounding variables; we measure employment placements where they happen without claiming Boot Up caused them.
  • Health outcomes — outside scope.

The Epistemic Honesty directive applies most strongly here: Boot Up's failure mode is overclaiming benefit to vulnerable populations in funder applications. Discipline at the measurement layer is the first defense.

Measurement methods

Method Used for Limitations
Internal database Pipeline + cohort metrics Trustworthy if discipline holds; depends on consistent intake-staff data entry
Facilitator session notes Cohort engagement Subjective; helpful for adjustment, not external reporting
Post-cohort participant survey (optional) Confidence, skills used Self-report bias; response bias
Partner organization data Cross-validation Available only where partner systems exist and partners are willing
12-month alumni event Long-term informal check Voluntary attendance; not representative

Reporting cadence

Internal — monthly to the BNI Foundation board and operational leads. Partners — quarterly cohort reports per partner. Public — an annual impact report, published on this site, including what didn't work. Funders — per grant requirements, with honest distinction between targets, validated outcomes, and planning hypotheses.

Known unknowns

In keeping with the Epistemic Honesty directive, Boot Up publicly tracks what it does not yet know:

  • Whether "earned, not given" produces better long-term outcomes than direct giveaways in this population
  • Whether peer instructors produce better cohort engagement than outside instructors at the same skill level
  • Whether the Seniors track in-home setup visit improves device-use persistence vs. no visit
  • Whether the local AI (Ollama) integration in Module 04 has measurable curiosity or skill carryover beyond the session
  • Whether the workforce pipeline ratios (trainees → paid roles → external employment) are realistic at our scale
  • What the realistic donation-yield curve looks like beyond initial pilot donors

These are not problems with the program — they are the things Boot Up will learn as cohorts run. They are documented here so they can't quietly turn into confident claims later.