Bridging the Skills Movement Data Divide: Moving From Vision to Action

Data Connectivity Is the Bridge for the Skills-Data Divide

Skills-first practices in the workplace, which prioritize experience over academic credentials, continue to shift the narrative about who gets ahead in the workforce, and why. This approach to learning and hiring can dismantle outdated degree norms, unlock opportunities for millions of working people, and offer new pathways to meaningful work, advancement, and equity.

However, the next new challenge is building and maintaining the systems necessary to easily connect and access skills data, which has been historically hard to capture and share. If an employed person has earned valuable skills from a mix of formal education, on-the-job training, and online courses—but there’s no centralized way to document, validate, and proffer their skills and experience—the result is a fragmented experience, where the journey from learning to work is marked by lost records and missed opportunities.  

Connecting Skills Data to the Future of Work

The existing gap is more than a technological issue—it’s systemic. Legacy infrastructures, siloed databases, and conflicting policies inhibit the seamless flow of skills data, making it difficult for learners to prove their abilities, employers to find the right talent, and institutions to support their students effectively.

Without a connected system, the potential of the skills-first movement will remain largely untapped. For example, 45% of firms that removed degree requirements from job postings showed no changes in their hiring practices, and an additional 20% actually decreased the hiring of candidates without degrees. Still, states like Arkansas and Alabama are leading by example with the implementation of state-run job boards built on connected data systems to incorporate shared taxonomies and input from stakeholders, creating a more coherent, inclusive approach to hiring and skills recognition.

Over the course of our work to accelerate the adoption of skills-first practices, JFF has engaged the expertise of more than 40 practitioners, business leaders, tech entrepreneurs, community organizers, and policymakers to explore how we can extend and model the approach for learning and employment. With a focus on clarifying the opportunities to connect data systems, we walked away from those conversations with five key principles that we believe will drive a future workforce system where data nudges opportunity forward. 

Principle 1: Create interoperable data systems that respect privacy

The free movement of data requires navigating a complex landscape of proprietary standards, state policies, and privacy regulations. Currently, skills data exists in silos, such as institutional databases or academic transcripts, which serve institutional needs but often burden learners. Learners accumulate credentials, experiences, and competencies over time, but those are rarely consolidated into one accessible, discoverable, and transferable format.  

The key challenge is that a one-size-fits-all data format isn’t practical at this early stage. Each system—from educational institutions, workforce development agencies, or employers—captures skills data according to its unique purposes and reporting requirements. We need systems that are interoperable and adaptable to exchange secure data across contexts without compromising user privacy or control.

Principle 2: Modernize data systems for integration and value-add

The siloed platforms of legacy systems make it difficult for learners, workers, and employers to share, validate, and leverage skills data effectively. We need modern infrastructure that not only allows the interoperability necessary to enable a free flow, but also gives individuals control over their information and empowers them to make informed decisions as they navigate learning and career pathways. 

That means modernization requires both investment and policy alignment. It means transitioning from fragmented, rigid systems to more flexible, adaptable platforms that work seamlessly together. But it also means centralizing the end-user experience to support learners, workers, and employers with the data they need to track progress, identify opportunities, and make meaningful decisions. 

Principle 3: Prioritize translation over standardization

Across platforms, skills data is captured, collected, and codified for reporting needs and often not in a language that works for another group that may also need it, particularly employers. Just as important, these data records are never fully consolidated for the individual. Although the idea of a standardized taxonomy is compelling, it’s not practical. Each sector, company, and region speaks its own skills language that is heavily contextualized, and we risk losing critical nuances by trying to unify them.

Instead of forcing standardization, let’s focus on translation. Building mechanisms that bridge taxonomies and crosswalk one platform to another allows for the alignment of skills data across varied systems. These “translation hubs” can serve as adaptable frameworks that support skills mobility and reflect the next phase of interoperability by considering system-to-system movement of skills records. 

Principle 4: Build trust through validated skills data

Trust is the core of a successful skills-based ecosystem. Employers need confidence that skills data accurately reflects a candidate’s capabilities, and learners must be assured that their credentials will be recognized and respected. Fragmented and inconsistent validation processes often undermine this trust, leading to skepticism and underutilization.  

To build credibility, systems must ensure transparent validation and data quality to allow skills data to be verified, transferred effectively, and at the same time, protect user privacy and consent. By focusing on transparent validation processes and high data quality, skills data systems can build the credibility necessary to drive a trusted, connected skills-based ecosystem that mutually benefits learners, employers, and institutions. 

Principle 5: Design policy and standards for ethical data flow

Data is the nucleus of a skills-first ecosystem, but policy lays the groundwork for how that data is collected, used, and distributed. When they’re effective, those policies enable the secure, ethical flow of skills data across platforms and institutions. The challenge is to develop policies that support both interoperability and privacy to guarantee that data moves freely while also giving users control over their own information. 

At the federal and state levels, policies should encourage open, interoperable standards that make the seamless sharing of data easy and possible across different systems without locking information into proprietary formats. These standards align skills data and ensure records are easily transferred and accessible across various stakeholders. By developing policies that prioritize open standards and foster cross-sector collaboration, we can ensure that skills data flows securely, ethically, and efficiently to empower learners to value their earned skills and help employers access the talent they need. 

A skills-based ecosystem isn’t an alternative option to the degree inflation that once was. It’s powered by the vision and corresponding action to foster the connectivity that bridges opportunity, mobility, and growth. Building a connected, skills-based economy is a multifaceted effort that goes beyond technology. It requires vigilant analysis and establishment of thoughtful policies, ethical governance, user-centered design, and collaboration across sectors. The shift toward a skills-first economy is already unlocking new pathways for millions, but without integrated data systems to support this movement, much of its potential will remain untapped. With these five key principles, we can lay the foundation for a robust, equitable, and human-centered workforce system where skills data flows freely to empower everyone connected to the evolving job market in a skills-first future. 

This initiative is a part of the Project to Catalyze Skills-First Practices. JFF supports transformational efforts to champion skills-first practices, reshaping how workers, employers, and educational institutions communicate and assess skills, experience, and knowledge. The Project to Catalyze Skills-First Practices, funded by Walmart, seeks to redefine and enhance the way an array of actors—including employers, policymakers, learning and education providers, philanthropy, and workforce development leaders—interpret and utilize information about a worker’s skills and experiences.