The public workforce system, and the workforce boards that comprise it, are often hamstrung by out-of-date public datasets, difficult data-gathering processes, and clunky reporting systems that limit their effective application of data to improve job-seeker outcomes.

The Future of Work Grand Challenge, a competition partnering next-gen job training companies with workforce boards across the country, launched in early 2021, when the economy changed drastically from one week to the next.

During this time, workforce boards’ ability to effectively monitor stakeholder needs became essential to meeting the Challenge’s demands of rapidly standing up and scaling training programs in a virtual environment.

Identifying and creating new data sources, such as user-generated data from partner companies’ digital training platforms, while tapping into existing ones, such as state Unemployment Insurance databases, helped participants stay abreast of emerging trends, find areas for improvement, and maximize program benefits.

In this impact story, we focus on how workforce boards participating in the Future of Work Grand Challenge demonstrated a data-obsessed approach to recruiting participants and providing services, navigating both successes and pain points.

Workforce boards’ ability to access large, sophisticated customer databases such as participant data and unemployment insurance made them ideal partners for training solution providers competing in the Future of Work Grand Challenge.

Most of these solution providers—which included companies such as Pragya, which prepares jobseekers for careers as medical office assistance and direct support specialists, and Colaberry, which prepares jobseekers for careers as medical device sterilization technicians—had no presence in the participating regions and were unaware of the best way to approach outreach and recruitment, support service delivery, and regionally-targeted job placement.

Workforce boards seized the opportunity to use the solutions teams’ data for detailed feedback on cohort performance throughout the training period. Typically, workforce boards receive limited jobseeker demographics, program completion rates, placement, and job retention data from training providers. Often, workforce boards have to track down this data from jobseekers one by one, which is time-intensive and can lead to incomplete data sets if jobseekers don’t respond. Working with solutions teams using digital training platforms, and even novel artificial intelligence applications, Future of Work Grand Challenge workforce boards obtained access to large amounts of data that tracked jobseeker progress with rich datasets that inform learner preferences, trends, and behaviors. The partnerships can reveal opportunities for workforce boards to support jobseekers in exciting, new ways.

Workforce Solutions Greater Dallas tapped into the vast potential of the state’s unemployment claimant database, targeting people with work experience that aligned with their solution provider’s programs.

VITAL, which offers medical device service technician training, included claimants with healthcare experience as well as those with potential crossover skills in fields like personal care and barbering. Dallas only started using this new approach, and novel database, during the pandemic.

With new applicants, Workforce Solutions Greater Dallas also used VITAL’s virtual job interview practice platform to learn more about the job interview readiness of jobseekers. This tool uses artificial intelligence to track speech patterns and eye movement, and offers participants feedback on interview preparedness. These novel forms of assessing jobseeker performance generate new opportunities to allocate resources to services and supports to help participants perform better in interviews and find more opportunities.

Capital Workforce Partners, in Hartford, Connecticut, developed a new data collection process to gain additional insights into their jobseekers’ needs. They then integrated the intake form for the Grand Challenge into their existing data management system. The intake form is now being used across the workforce board to screen jobseekers for interest in other training programs.

Capital Workforce Partners was also able to observe jobseeker participation data collected by their training provider, Pragya, through its virtual platform. This data examined how often someone logged on, how long they interacted with the platform, their completed modules, and their performance. In the future, Capital Workforce Partners expressed an interest in expanding this capability, enabling American Job Center career coaches to identify and offer additional jobseeker supports and enhance customized service delivery.

To inform strong matches between training solutions and workforce boards, XPRIZE used real-time labor market data and feedback directly from the workforce boards to explore the anticipated number of job openings by occupation within each region.

However, given the volatility many industries experienced throughout the pandemic, even the most sophisticated labor market data sources were unable to accurately predict job demand for a variety of occupations. For example, San Diego Workforce Partnership reported that while healthcare employers were making a large push to hire community health workers in winter and early spring of 2021 to assist with the vaccination campaign, by the time recruitment launched in May for their FOWGC training solution, most positions were already filled.

In addition, the data used to inform solution provider and workforce board pairings was not granular enough to take into account the specific skills and certifications required by employers in different communities, even for in-demand target occupations. It was difficult to adjust for these data gaps for several reasons: the volatility of local labor markets at the time, the relative latency of state and federal data sources, and accelerated efforts to respond to the abrupt job displacements spurred by the pandemic. In most cases, the workforce boards were able to fill these gaps by facilitating the discovery of qualitative data with their stakeholders on the ground, connecting solution providers and employers to identify relevant workplace competencies to align curricula with local hiring requirements. In other cases, it was difficult to reconcile the training program with the needs of the region. For instance, while data showed that San Diego had 364 job openings for “installation, repair, and maintenance technicians,” there were few job openings for maintenance technicians within the textile industry—the industry San Diego’s solution provider was training participants to enter. Even cutting-edge tools such as real-time data can lead to misaligned decision-making when devoid of on-the-ground context.

High-quality, accessible, up-to-date data is a keystone of the public workforce system. At their most effective, insights and analytics can help drive impressive program outcomes. Undoubtedly, workforce data collection will increase in speed, volume, and sources in the years ahead. Workforce boards and their partners must commit to managing, interpreting, and wielding it responsibly to address the evolving needs of their customers and stakeholders effectively.