APT Announces Data Dive Partnership with Capital Area Food Bank

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Applied Predictive Technologies (APT) announced today the results of a data dive partnership with Capital Area Food Bank. The project helped answer two major questions: 'How can we map and optimize distribution to best match hunger and food insecurity across the Washington metro area?' and 'How can we optimize purchasing decisions over time by core food category?'

Applied Predictive Technologies (APT), the world’s largest purely cloud-based predictive analytics software company, announced today the results of their recent data partnership with Capital Area Food Bank (CAFB). CAFB is the largest hub for food sourcing and distribution for those struggling with hunger in the Washington metro area.

At a high level, the project aimed to answer two major questions:
1. How can we map and optimize distribution to best match hunger and food insecurity across the Washington metro area?
2. How can we optimize purchasing decisions over time by core food category?

-Mapping and Optimizing Distribution to Meet Demand-

To best optimize distribution of CAFB resources, APT built a predictive model specifically designed for the Washington metro area to allow CAFB to anticipate food orders by zip code. Drawing upon data comprised of food insecurity rates, CAFB distribution partners’ locations, and food ordering patterns, APT identified areas where residents are struggling with hunger. The APT team used this data to build a hunger heat map, thus visualizing areas with additional need and areas that may have relative spare capacity.

CAFB plans to adapt and employ this map to help determine where to meet hunger needs across the region. This map will be dynamically updated with data from CAFB’s new data warehouse going forward to allow CAFB to externally share the demands with donors and internally shift strategy to meet food insecurity needs.

-Optimizing Food Purchases-

Another area of focus for CAFB was evaluating inventory versus demand levels by product to better prioritize food purchases across the year and recommend food donations to partner organizations and the public.

To determine how well supply meets demand for each product category, APT built a model to evaluate opportunities for each category based on several key factors. These factors included Days to Stock Out (how many days on average a product is held in inventory), Donation Contribution, Purchase Contribution, Yearly Distribution Volume, and Category Growth (year-over-year growth in orders/donations of a category). Each key food category was then evaluated using a “scorecard” combining these factors to determine, at a high level, what action should be taken for each category (e.g., purchase more or less). CAFB can use this scorecard going forward to best meet demand by purchasing food and encouraging specific donations.

Using historical data, the APT team also forecasted fulfilled demand by product for June 2014 to March 2015 to allow for better planning and allocation in the coming year.

Some key findings from this analysis included the following:
•Demand for dairy is highly variable, and is predicted to decline through the end of 2014
•Demand for ground meat is predicted to increase in June 2014 vs. May 2014
•Some categories, such as Poultry and Rice are relatively stable over time—demand does not significantly vary month-over-month

These findings were presented to CAFB in an interactive session. Afterwards, APT and CAFB discussed how these findings and models can be put to best use by the CAFB team in the future. Next steps include integrating the predictive recommendations into CAFB’s existing data warehouse and updating the interactive map with new data.

“We were impressed with APT’s ability to swiftly analyze our data – teasing out some key learnings that we will, without a doubt, draw on,” said Nancy Roman, CEO of CAFB. “I’ve been the fortunate recipient of a lot of pro bono work on behalf of hunger. This was top of the line.”

APT CEO Anthony Bruce said, “We are glad to partner with such a respected and important local institution as CAFB. The findings from this project are interesting and, importantly, are immediately actionable. I hope the project will help CAFB better achieve their essential goal of alleviating hunger in the DC metro area.”

About Applied Predictive Technologies
APT is the world’s largest purely cloud-based predictive analytics software company. APT’s Test & Learn software is revolutionizing the way Global 2000 companies harness their Big Data to accurately measure the profit impact of advertising, marketing, pricing, merchandising, operations, and capital initiatives, tailoring investments in these areas to maximize ROI. APT’s customer portfolio includes Walmart, Staples, Lowe’s, SunTrust, Hilton Hotels, Anheuser-Busch InBev, McDonald’s and others. APT has offices in Washington, D.C., San Francisco, London, Tokyo, and Taipei. For more information, please visit http://www.predictivetechnologies.com.

About Capital Area Food Bank
The Capital Area Food Bank is the hub for food sourcing, food distribution and nutrition education in the Washington metro area, serving those struggling with hunger. In Washington, DC and its six surrounding counties, there are nearly 700,000 individuals at risk of hunger, of which nearly 150,000 are children. Last year, the CAFB distributed 45 million pounds of food – equivalent to 37.5 million meals – to 478,100 people through direct service and a network of more than 500 partner agencies. The CAFB service area includes: Washington DC; Montgomery County, MD; Prince George’s County, MD; Fairfax County, VA; Prince William County, VA; Arlington County, VA; and The City of Alexandria, VA. To learn more about CAFB, please visit http://www.capitalareafoodbank.org/.

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