A Fluid Workforce Model is a strategic framework that treats talent as a variable resource rather than a fixed overhead. Instead of relying solely on a headcount of permanent staff, companies build a ...
In the wake of the pandemic, healthcare leaders were compelled to implement innovative and resilient solutions to support their teams in caring for patients. While these quick fixes served their ...
AHA's 2026 Workforce Scan highlights six pressures that will define workforce strategy in the coming years: financial stress that limits flexibility; demographic shifts that increase demand; rapid ...
Madison, WI (BUSINESS WIRE) - Indeavor, the leading provider of enterprise employee scheduling and workforce management solutions, today announced a strategic partnership with Kahuna Workforce ...
Hospital leaders are rethinking workforce design to create hybrid care models that improve patient outcomes while sustaining and supporting clinical teams. Hospital executives are redefining how care ...
The persistent volatility of today’s economic landscape presents a formidable challenge for global business leaders. For many, the knee-jerk reaction is often to scale back staffing through hiring ...
UKG Reveals 2026 Trends Reshaping the Workforce: AI Without Trust Fails, Talent Models Must Flex, and the Employee Enablement Era Begins UKG, a leading global AI platform unifying HR, pay, and ...
Forbes contributors publish independent expert analyses and insights. Jeanne Meister writes about trends impacting the workplace We are moving from the hybrid workplace, with the flexibility to work ...
Anesthesiology is heading into a pivotal year, as workforce volatility, reimbursement pressure and policy shifts collide with rising surgical demand and expanding outpatient care. After a period of ...
Health care organizations must do things differently to combat rising rates of nurse burnout. Embracing hybrid workforce models for nurses is an excellent start. Processing Content It's an approach ...
The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...
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