What the Technology Does When Every Part of the Ecosystem Is Connected
A workforce director at a tribal college described it simply: her students were completing rigorous programs in healthcare administration, IT support, and environmental science, and then disappearing from the data. Their credentials existed on paper. They existed in her office's tracking system. But the moment a student walked out the door and began applying for work, those credentials were unreadable to the employers and sponsors operating on the other side of the labor market. The technology to read them did not exist in the systems those employers used.
That gap is not a policy failure. It is a data infrastructure failure. And pēpelwerk's platform is built to close it: by connecting every part of the workforce ecosystem into one shared, machine-readable data layer.
The Technology Step by Step
When a credential enters the pēpelwerk registry (whether it is a tribal vocational certification, a CTE program completion, a military occupational specialty, or a four-year degree), the platform immediately generates a Learner Employment Record (LER). The LER is a structured, portable, digital representation of what that credential means in terms of skills, competencies, and verified work experience. It does not live in a single institution's database. It lives in the shared ecosystem.
Once the LER is generated, the matching engine activates. Employers on the platform post skills-based job descriptions, not generic degree requirements, but specific competency maps built around what the role actually demands. The platform runs the LER against those descriptions in real time, surfaces qualified candidates the employer would never have found through a traditional ATS, and initiates the connection. A credential enters. A match fires. A hire happens.
The entire sequence runs without a recruiter manually reviewing a résumé for keywords, without a candidate needing to know the right terminology to pass a filter, and without a sponsor needing to guess whether their workforce investment is reaching the employers who need it. The World Economic Forum has identified skills-based matching infrastructure as one of the highest-impact tools available to close labor market inefficiency at scale. (Source: WEF, Future of Jobs Report, 2025.)
What Sponsors and Employers See on Their End
For a sponsor, a foundation, a tribal government, a state workforce agency, the connected ecosystem produces something that isolated program funding never could: a continuous, real-time view of outcomes. Every learner who earns a credential through a funded program and enters the platform generates an LER that the sponsor can track. Which credentials are producing hires? Which employers are engaging with that credential set? Where are the remaining gaps between the skills being trained and the skills being demanded?
Sponsors no longer have to wait for an annual program report to answer those questions. The data is live. The outcomes are visible. And because the platform connects every grantee's data into one layer, a foundation funding programs across multiple states can see aggregate outcomes across all of them in one place. According to McKinsey Global Institute, organizations that operate on shared data infrastructure reduce reporting overhead by an average of 30% while improving decision quality. (Source: MGI, The Age of Analytics, 2023.)
For employers, the connected ecosystem means the candidate pool is no longer limited to whoever happened to apply. When the platform's LER database includes tribal credentials, rural CTE completions, and military transition records alongside traditional university degrees, the matching engine surfaces candidates with verified skills that degree-only filters would have screened out. The U.S. Chamber of Commerce Foundation has documented that skills-based hiring increases workforce diversity and reduces mis-hire rates when built on verified credential data rather than self-reported résumé claims. (Source: U.S. Chamber Foundation, Work-Based Learning Report, 2024.)
The Ecosystem Only Works When Every Part Is Connected
A single tribal college connecting to pēpelwerk adds value. A single CTE district adds value. But the power of the shared data layer compounds with every new partner. When tribal credential data sits alongside CTE data alongside military transition data alongside employer job demand data, all in one machine-readable ecosystem, the platform can do things that no single dataset can support: cross-sector matching, skills gap analysis at a regional level, employer demand forecasting, and sponsor outcome attribution across an entire workforce development portfolio.
The CTO consortium is building that ecosystem now. With 7 tribal organizations, CTE programs across 3 states, several state workforce agencies, and 500+ employer partners already connected, the data layer has the density to produce real results. The March 31 deadline is not a cutoff. It is the moment the ecosystem reaches the next tier of matching precision.
If your organization is holding credential data that belongs in this layer, pēpelwerk is ready to connect it. See how the technology works at pepelwerk.com and book a demo to walk through the full ecosystem view with our team.
