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Process

Process Readiness Levels

ProML · 5 levels · R&D-cycle equity

ProML describes how the R&D process itself carries equity through every phase: from equity defined as a goal (Level 1) through equity in dissemination & governance (Level 5). Use ProML when the question is: does the way this team studies, measures, iterates, and disseminates produce evidence that's trustworthy for the populations the product is meant to serve?

1
Goal-setting
Equity defined
▸

Equity goals are explicit, measurable, and tied to the specific population the project is meant to serve.

Self-assessment questions

  • Are equity goals explicit and measurable for this R&D project (specific subgroups, specific outcomes, specific decisions they should shape)?
  • Can the team articulate which subgroup-level outcomes the project is responsible for — not just population-level averages?
  • Is at least one team member accountable for keeping equity goals visible across phases, not just at concept stage?
To advance to ProML 2: translate equity goals into design choices with a documented decision trail. Name equity-relevant tensions explicitly (fidelity vs. access, simplicity vs. adaptability).
2
Design
Equity in design
▸

Design choices systematically reflect equity goals. The R&D plan documents how equity considerations shaped at least one design decision per phase.

Self-assessment questions

  • Have design choices in at least one current phase been visibly shaped by equity considerations, with a documented decision trail?
  • Does the R&D plan explicitly address how design choices serve — or fail to serve — the priority subgroups, not just the average user?
  • Are equity-relevant tensions (fidelity vs. access, simplicity vs. adaptability) named explicitly in design decisions, rather than glossed over?
To advance to ProML 3: wire equity into the data layer. Design data collection from the start to support disaggregation; power sample sizes for subgroup analysis, not average effects; pre-specify subgroup analysis questions before data collection.
3
Measurement
Equity in data
▸

Data collection and analysis are designed from the start to support disaggregation, subgroup learning, and detection of differential effects.

Self-assessment questions

  • Is data collection designed from the start to support disaggregation by all priority subgroups (including subgroup combinations where relevant)?
  • Are sample sizes and recruitment plans powered for subgroup analysis, not just for average effects?
  • Does the analysis plan pre-specify subgroup questions (including null and counter-hypotheses) before data are collected?
To advance to ProML 4: create a plan to close the loop. When subgroup analysis reveals differential effects, the R&D process must respond with documented design or measurement changes, rather than deferring them to a future report.
4
Iteration
Equity in iteration
▸

Iteration cycles use subgroup evidence to improve the prototype. When subgroup analysis reveals differential effects, the R&D process responds with documented design or measurement changes.

Self-assessment questions

  • When subgroup analysis reveals differential effects, does the R&D process respond with documented design or measurement changes in the next iteration cycle?
  • Are iteration decisions adjudicated against equity criteria, not just against average performance?
  • Is there a mechanism for community partners and team members to raise equity concerns mid-cycle and have them acted on, rather than deferred to a future report?
To advance to ProML 5: extend equity into how the work is shared and governed. Disseminate findings to the communities served, in formats they can use, and embed community decision rights in scaling, monetization, and continued use.
5
Dissemination & governance
Equity in dissemination & governance
▸

Findings flow to the communities served, in formats and languages they can use. Decision rights about scaling and continued use sit (in part) with the populations the project serves.

Self-assessment questions

  • Are findings disseminated to the communities served in formats and languages they can use, not only to funders and academic audiences?
  • Do decisions about scaling, monetization, and continued use of the product reflect input or shared decision rights with the population the project serves?
  • Is there a governance mechanism (board representation, community standing on key decisions, formal accountability) that gives the community served continuing standing?
Top of the ladder. A process at ProML 5 carries equity all the way through dissemination and governance. PRL and PeoML are the next questions: does the prototype maturity and team standing match the process discipline?
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Open PRISM Self-Assessment Compare with PRL & PeoML Prototype Readiness → People Readiness →
PRISM · Portfolio Readiness Insight & Scoring Methodology · SETA-ED
ProML developed by SETA-ED, drawing on equity-centered evaluation methodology and ARPA tiered-support practice. Citation: Uncapher, M. (2026). Education Process Readiness Levels (ProML). SETA-ED.