How Data Sharing Can Improve Frontline Talent Development

Jan 30, 2019 9:45 AM ET

Frontline workers, or the workers who interact directly with customers and provide services in industries like retail, healthcare, food service and hospitality, help make up the backbone of today’s workforce.

However, frontline workforce talent development presents numerous challenges. Frontline workers may not be receiving the education and training they need to advance in their careers and sustain gainful employment. They also likely do not have access to data regarding their own skills and learning, and do not know what skills employers seek in quality workers.

Today, Digital Promise, a nonprofit authorized by Congress to support comprehensive research and development of programs to advance innovation in education, launched “Tapping Data for Frontline Talent Development,” a new, interactive report that shares how the seamless and secure sharing of data is key to creating more effective learning and career pathways for frontline service workers.

The research revealed that the current learning ecosystem that serves frontline workers—which includes stakeholders like education and training providers, funders, and employers—is complex, siloed, and removes agency from the worker.

Although many data types are collected, in today’s system much of the data is duplicative and rarely used to inform impact and long-term outcomes. The processes and systems in the ecosystem do not support the flow of data between stakeholders or frontline workers.

And yet, data sharing systems and collaborations are beginning to emerge as providers, funders, and employers recognize the power in data-driven decision-making and the benefits to data sharing. Not only can data sharing help to improve programs and services, it can create more personalized interventions for education providers supporting frontline workers, and it can also improve talent pipelines for employers.

In addition to providing three case studies with valuable examples of employers, a community, and a state focused on driving change based on data, this new report identifies key recommendations that have the potential to move the current system toward a more data-driven, collaborative, worker-centered learning ecosystem, including:

  1. Creating awareness and demand among stakeholders
  2. Ensuring equity and inclusion for workers/learners through access and awareness
  3. Creating data sharing resources
  4. Advocating for data standards
  5. Advocating for policies and incentives
  6. Spurring the creation of technology systems that enable data sharing/interoperability

We invite you to read our new report today for more information, and sign up for updates on this important work.