Case Study

Keeping health workers safe with accurate protective-equipment predictions

A global healthcare company adapts commercial analytics to forecast equipment demand

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The safety of frontline health workers makes headline news when organizations fail to meet the demand for personal protective equipment (PPE) in the battle against COVID-19. For this global healthcare services company, getting an early, clear view of where it would experience spikes was of paramount importance.

By adapting the work of its financial planning and commercial analytics team to develop new forecasting models, it knew exactly where demand for PPE would surge. So when the Federal Emergency Management Agency (FEMA) requested help, the company was already one step ahead.

Challenge

Getting PPE to where it's needed most

The company set out to determine which hospitals would have the highest demand, ensure that it had enough inventory, and adapt its supply chain to respond.

Once it had identified the hot spots, the healthcare firm had to match PPE demand to supply. For pharmaceutical companies, this is relatively straightforward because the UN has established standard classification codes to help companies get the right drugs to the right places.

Unfortunately, PPE is not standardized using a universal code across manufacturers, making it difficult to understand total supply. Expertise in cross referencing available products across distributors would also be necessary.

Solution

Bringing together new forecasting models and industry expertise

Our Genpact commercial analytics team was up to the challenge. On a typical day, this team supports the business with forecasting, salesforce planning, performance management, incentivization, and targeting.

The team got to work to understand where demand for PPE would come from and determine inventory levels. It combined its knowledge of the industry, categories, products, and distribution with its technical skills. Specifically, it drew on its clinical product cross-referencing capabilities across manufacturers and distributors, and developed a machine-learning powered forecasting capability. The results were fast and accurate.

Impact

Accurate predictions keep more workers safe

Our forecasting model quickly predicted a spike in the northeast of the US. We added that information to the company's planning and allocation engine, and the business set to work to get PPE to those who needed it most.

One day later, FEMA made its request for PPE supplies targeting the very same area. The healthcare firm could confirm that it was already on the case.

By adapting our analytics team to generate fast, accurate analysis and predictions, we helped the company and its supply chain respond, getting PPE to frontline workers.

During a pandemic, being just a day ahead of any request makes a difference to businesses, communities, and people's lives.

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