Prescribing the SBO for HC: Skills Data in Healthcare
When it comes to being a skill-based organization (SBO), EPAM is on the case. Forrester’s recent case study sketches out our three-decade run as an SBO and offers compelling insights into the power of skills data. Systematically capturing, graphing and leveraging workforce skills has been healthy for our business. This has accelerated decision-making, advanced artificial intelligence (AI) readiness, fueled employee growth, improved quality of outcomes and carved out a sharper competitive edge.
But how might these same benefits translate to healthcare, a sector infamously defined by heavy regulation, complex digital transformation roadmaps and a cautious approach to AI adoption? Could skills data help untangle the operational challenges of clinical delivery? Might it empower sprawling provider networks, streamline payor systems and, gulp, support the technology vendors driving the industry forward?
A central question emerges: Why should an industry so focused on licensure and credentials add skills data into the mix?
Faster, More Confident Resourcing Decisions
When organizations have a unified view of their workforce — meaning, clear visibility into who can do what, at what level of expertise and where — they can make decisions about staffing, hiring and development with precision. Instead of relying on outdated credentials, gut feel or siloed human resources (HR) systems, leaders can dynamically match talent to demand in real time.
Says Sandra Loughlin, EPAM’s Chief Learning Scientist, “The big value in [collecting and using skills data] is business agility. Because if people are the engine of your business and you have people in the wrong place, you're not able to move toward your strategy as quickly or effectively.”
Imagine instantly redeploying clinicians with specialized respiratory skills to high-demand units during a pandemic surge, or rapidly staffing compliance and regulatory task forces with internal experts when new rules [like Centers for Medicare & Medicaid Services (CMS) interoperability] begin to influence payor workflows. Health tech companies would surely benefit from the swift formation of cross-functional teams with verified experience in U.S. Food and Drug Administration (FDA)-regulated medical software, ensuring the right mix of expertise before a product launch. The result for all? Fewer gaps, faster response times and more efficient use of scarce talent across the entire care ecosystem.
Smoother, Safer AI Adoption
AI succeeds when organizations understand both the skills of their workforce and the tasks that make up jobs. By mapping work at a granular level, it becomes clear which tasks can be automated and where human expertise is still critical. This avoids disruption and helps organizations proactively redesign roles, retrain staff and introduce AI where it truly adds value. Says Jonathan Rioux, Managing Principal, Artificial Intelligence: “A profitable AI transformation relies on adoption and buy-in at every level of the organization, which in turn depends on a thorough understanding of your people, their work and how it is tied to value.”
Clinical opportunities exist in mapping administrative tasks like prior authorization and charting. Moving beyond theorized use cases, this data pinpoints where AI can safely assist, reducing documentation burden and giving caregivers more time for patients. For payor systems, task intelligence might help target specific claims functions for AI automation and allow staff to move into care coordination roles to improve member experience.
“Healthcare activities require skills that take a long time to acquire and master, orchestrated together in a complex network,” says Rioux. “To win with AI means understanding the skills and knowledge necessary to perform the work first; everything else flows downstream from there.”
A Motivated, Growth-Oriented Workforce
Staffing in healthcare is at an all-time low. A limited talent pipeline and growing competition for specialized skills have organizations struggling to fill business-critical roles. Shifting workforce expectations around flexibility and employee well-being are calling for investments in adaptable work environments. Remember the pandemic? Healthcare is still fighting the lingering impacts of workforce attrition, heightening the urgency for sustainable retention strategies. We’ve read that the application of skills data to hiring practices is making its mark on healthcare. But what about its impact on upskilling and retention?
Says Loughlin says on the matter: “Look, it’s much easier and cleaner to get skills data on new hires. However, the real significant value of skills in an AI world is not talent acquisition, it's talent employment and talent upskilling.”
Employees thrive with clarity — clear pathways for growth, transparent career progression for clinical, technical and business roles, as well as personalized learning plans aligned to individual goals and organizational needs. Skills intelligence makes career development tangible and fair, helping people see where they stand today and what they need to advance. Or better yet, it highlights emerging skills, such as Fast Healthcare Interoperability Resources (FHIR) and cybersecurity, and guides upskilling, with the opportunity for recognition and reward for continuous learning.
Improved Outcomes, Fewer Mistakes
Matching the right people with the right work leads to better outcomes. Think higher-quality care, fewer errors and more efficient operations that drive better experiences for patients, members and customers. Skills intelligence helps ensure teams are built for success from the start.
Staffing misalignment is a common challenge across healthcare. In provider systems, assigning intensive care unit (ICU) or operating room (OR) teams without clear visibility into staff skills can jeopardize patient safety. Payors risk gaps in care when case management teams lack the right clinical or behavioral health expertise, leaving high-risk members unsupported. Health tech companies face costly rework and regulatory delays when product teams aren’t properly balanced with clinical, regulatory and UX/UI expertise (to name just a few).
Business Agility and Market Opportunities
Organizations with deep workforce insight can pivot faster than competitors. They can respond to market shifts, launch new services, adopt emerging technologies and scale without the chaos that comes from guessing at workforce capabilities. Over time, skills intelligence becomes a strategic differentiator — not “just an HR tool.”
Says Loughlin, “To help executives understand the need for this type of framework, I ask them to think about their competitors not being who exists today, but as an AI-native version of whoever they are. Because it’s probably being built in someone’s garage today. Those AI-native businesses are going to be designed, using data, to have a few people as possible doing the task that fits them best, with everything else done by AI.”
Future-ready teams with the right mix of actuarial, clinical and operational talent can be assembled faster and with higher confidence. In an industry where margins, regulations and patient needs shift daily, the agility gained through proper skills insight cannot be overstated.
Says Troy Rask, Head of Healthcare at EPAM, “Healthcare is, and always will be, a people business, and we know workforce skills directly shape outcomes and efficiency. Without good data on the current and future capabilities of these people, leaders risk making critical decisions without a clear line of sight.”
The bottom line? Skills intelligence, and the infrastructure to act on it, bring the clarity needed to align talent with strategy for impact. Its benefits can be pulled through any industry, but we know healthcare is ailing from less-than-efficient talent distribution. SBO might be the pill it needs.
Learn more about Life Sciences and Healthcare at EPAM.
