Understanding the frontline worker perspective
Throughout 2020, SkillRise led an edtech learning circle in collaboration with the Retail Opportunity Network (RON). The monthly calls brought together 15 partner organizations from within the RON to explore various themes related to edtech and adult learning. After each call, a host organization developed a blog post to capture and reflect upon the monthly theme. The following post is written by Sarah Cacicio and Sierra Nokes from Digital Promise as they helped the group explore data interoperability during the April call.
An inclusive research design approach
Authors: Sarah Cacicio & Sierra Noakes, Digital Promise
The need to more efficiently match job seekers and incumbent workers to available jobs is increasingly critical. Prior to the COVID-19 outbreak, an estimated 25 percent of all U.S. jobs were deemed at high risk of automation, particularly among frontline workers who perform routine tasks in industries like retail, hospitality, healthcare, and manufacturing. The coronavirus pandemic has exacerbated these challenges for workers who face increased risk of illness, instability, and unemployment. Now more than ever, workers must be able to identify, communicate, and apply their skills and credentials to pursue career pathways.
Like many adult learners, it took years for Angela Walker, a single mom in the Cincinnati region, to navigate the education, workforce, and social support systems needed to become a social worker. She describes the current context: “The workforce system is chaotic and people just don’t know where to start.”
Digital Promise is working to understand how data interoperability could potentially strengthen collaboration and connect disparate systems across education and training providers, workers, and employers.
As it stands, employers are struggling to find and retain skilled workers. Education and career service providers are trying to develop programs to meet employer demands and learner needs, and government agencies are positioned in long-standing silos between education and workforce development.
Could data interoperability—the ability to exchange information between people and systems in a seamless, safe, and controlled way—be a solution?
What the research says
Digital Promise has explored this question in a two-phase research project. We have learned that data interoperability is an integral part of the solution, but, in and of itself, will not solve the challenge of connecting talent to upskilling and job opportunities.
Our research in the first phase, “Tapping Data for Frontline Talent Development” (2019), mapped the landscape of the adult learning ecosystem that serves frontline workers. Through this work, we identified key stakeholders, including employers, providers, ecosystem drivers, and workers themselves. We learned that the ecosystem is complex and siloed, and it removes agency from the worker by taking data without returning any value. For example, workers spend a lot of time sharing their personal information and professional history in multiple applications for multiple agencies in an effort to access services, programs, or jobs, but do not always benefit from this process.
Our 2020 report, “Building Networks for Frontline Talent Development” (forthcoming), identifies what it would take to increase demand for data-sharing practices to collectively advance the frontline workforce. The following provides a sneak peek of our process, findings, and recommendations for next steps.
Amplifying the frontline worker perspective
Our team prioritized the perspectives and experiences of frontline workers to understand their incentives for upskilling, by including workers throughout interviews and focus groups.
The initial phase of this research revealed a stubborn and alarming reality: worker perspectives were absent from adult learning literature. Instead, assumptions about experiences and incentives were provided by those who either worked closely with workers, or, in some cases, supported direct service agencies. We found that the language used to describe frontline workers throughout the literature was deficit-based and, in some cases, demeaning and discriminatory. For the next phase, our team was committed to including workers in multiple aspects of the research process—in interviews, case studies, and our expert advisory group—and showcasing the experiences, skills, and attitudes that our current systems often neglect to acknowledge.
To accomplish this work, we reached out to workers through three primary networks:
- Education and career service providers who serve frontline workers
- Case study leads to include workers in focus groups
- Family, friends, and friends of friends, working in frontline industries
We provided gift cards to participants to demonstrate our appreciation of their time and expertise. We also included a frontline worker from the healthcare sector on our expert advisory committee to support data analysis and provide strategies for worker advancement based on lived experience. By prioritizing the frontline experience, we identified findings that have otherwise been missing from research reports.
We recognize specific limitations to this approach, including the challenge of recruiting frontline workers who are men of color and/or immigrant-origin to participate in interviews. We interviewed workers from retail, healthcare, and hospitality industries, but were unable to recruit worker representatives from manufacturing or construction. We will continue improving outreach and recruitment methods to include an even more representative sample of frontline workers moving forward.
Key findings: Stakeholder incentives for data interoperability
Our research revealed that many of the key stakeholder groups, from direct service providers to government agencies and employers, viewed data sharing as an important part of their ability to improve services for frontline workers. But factors such as competing priorities and limited resources often prevented them from establishing cross-sector partnerships and achieving data interoperability to collectively advance opportunities.
So what would incentivize each of the key stakeholder groups to demand and participate in a more collaborative, data-driven, and worker-centered ecosystem?
Workers: Income mobility
Workers are highly incentivized to participate in a data-driven workforce, but struggle to communicate their skills and find opportunities for advancement. They shared that paid, contextualized learning opportunities were the most valuable and support their goal of income mobility.
Employers: Recruit and retain a skilled workforce in the digital age
Employers want to hire and train staff who can readily apply digital skills alongside core professional skills. Most employers said they want to improve internal training programs for better retention and promotion rates.
Providers: Program completion and long-term worker success
Education and career service providers want to improve outcomes for learners through increased program retention and completion. They also want to integrate data interoperable systems to better match workers to jobs, track long-term outcomes, and measure participant success, such as increased earnings.
Key takeaway: Involve workers in design and development
Today, leaders in government, education, and industry are exploring ways to use technology to better match talent to employment opportunities. These efforts are promising for frontline workers who are looking to leverage their skills and advance in their careers. But, in order for workers to successfully access and use technologies, they must be part of the design and development.
Involving workers in the development of systems, programs, and technologies to support their advancement is a critical step to ensure racial, gender, and digital equity across frontline sectors. For this reason, Digital Promise recommends that communities engage in the process of Inclusive Innovation to collaborate directly with workers in designing the solutions that meet their needs, alongside employers, educators, and community members.