Through literature review and collaborative design, we propose the Focus, Activity, Statistic, Scale type, and Reference (FASStR) framework to provide a systematic approach to health care operation ...

As we continue to emerge from the Covid-19 pandemic, the global economy is facing a new set of challenges: inflation, fragile consumer loyalty and, finally, a possible recession. In such an uncertain ...

Suggested Citation: "Chapter 4 - Case Examples." National Academies of Sciences, Engineering, and Medicine. 2023. Third-Party Contracts for Fixed-Route Bus Operations and Maintenance: Performance ...

According to Aaron Young, SVP of Branch Operations and Retail Banking at Credit Union of Southern California (CU SoCal), the key to delivering smoother experiences is feedback from their Members.

Restaurant franchise performance management has followed a predictable pattern: review financial results, identify underperforming locations, and work with operators to correct course. The challenge ...

There are several metrics we prioritize. Our highest priorities are outcomes of quality, and metrics that reduce cost. The most important metric, therefore, is readmissions. We are cognizant of ...

The American Transportation Research Institute (ATRI) recently invited for-hire motor carriers to participate in its annual Operational Costs of Trucking report for 2026. The inst ...

Dive into the world of basic accounting metrics and key performance indicators (KPIs) to optimize your property’s profitability. From analyzing cash flow to measuring return on investment (ROI), these ...

Setting employee and team performance goals is an essential responsibility for business owners and managers. However, measuring and improving an employee’s performance can be complex and daunting, ...

As noted in Finding 1.1, two critical components are needed to evaluate the effectiveness of the Global Nuclear Detection Architecture (GNDA): a new strategic plan with outcome-based metrics and an ...

Artificial intelligence systems are only as powerful as the data they are trained on. High-quality labeled datasets determine whether a model performs with precision or fails in production.