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Grupo Fleury Improves Demand Planning with FICO Analytics, Saving Millions Annually

Brazil’s leading diagnostic medical company wins FICO® Decisions Award for AI, machine learning and optimization using FICO® Advisory and Analytics

SÃO PAULO, June 16, 2020 Highlights:

  • Grupo Fleury is using mathematical optimization to save millions annually.
  • Grupo Fleury has reduced the time taken to create sales forecasts from one month to half an hour.
  • Grupo Fleury has built a platform that integrates business knowledge into dynamic demand planning calculations.
  • Grupo Fleury won a 2019 FICO® Decisions Award for AI, Machine Learning and Optimization.

Grupo Fleury, one of Brazil’s largest diagnostic medical companies, has further refined its demand planning management tool known as the Fleury Forecaster built on the FICO® Xpress Platform to optimize its operations and reduce the time taken to create sales forecasts from one month to half an hour. The optimization improves resource allocation and planning across multiple time horizons and identifies opportunities to generate value.

For its achievements, Grupo Fleury won a 2019 FICO® Decisions Award for AI, Machine Learning and Optimization.

More information:

A robust demand planning process is critical to effective resource and offers allocation at different detail levels to ensure operations are fulfilling the company’s business plan.

To achieve this, a joint team of Grupo Fleury and FICO experts further improved on the existing Fleury Forecaster to manage continuous growth in demand and to improve the level of automation, detail, reporting and user-friendliness of the platform.

“With over 3,500 tests being performed across 300 sites, FICO had already helped us design a robust platform which could handle the complex dynamics of demand management,” said Eduardo Bianchetti, pricing, intelligence and commercial planning manager at Grupo Fleury. “The biggest challenge this year was to further adapt it to the business peculiarities of diagnostic medicine and to capture the deep industry knowledge of our analysts. Between our teams and FICO, we managed to balance a wealth of detail with performance speed to create a high-performance solution capable of ‘Augmented Intelligence’, the ability to integrate AI with the business knowledge of our specialists.”

Another important aspect of the solution is the ability to analyze the performance of past forecasts to help improve future forecasts. Users can view this in intuitive dashboards that help them understand forecast accuracy and how each stage of the forecasts construction process adds value to the result.

A further enhancement was estimating potential demand – essentially the sales possible, if it weren’t for offer restrictions – which was important in finding opportunities for increasing revenue. The solution created an automated, more accurate sales forecast which made the entire demand planning process faster and more reliable. As a result, the company is more confident about the forecast which forms the basis of the revenue budget.

“Grupo Fleury has built a business intelligence engine that significantly enable gains in profitability,” said Alexandre Graff, FICO’s president for Latin America and the Caribbean. “This solution is a great example of how we can apply artificial intelligence and machine learning techniques on a platform to optimize the company’s performance and processes.”

“FICO is really proud to be working with Grupo Fleury,” said Nikhil Behl, FICO’s chief marketing officer. “Helping to optimize the work of Brazil’s largest diagnostic medical companies takes on special meaning this year as they work on faster and more accurate tests for COVID-19.”

“Grupo Fleury had continued to build on its analytic platform to achieve exceptional results,” said Les Yeamans, RT Insights founder and one of the FICO® Decisions Awards judges. “Analytic projects like this can be like writing a great novel, each chapter completed leads you to the next idea. They have definitely capitalized by authoring their own success.”

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