Fairfax County
Ashley Luck, Communications Specialist

THRIVE, the Virginia Alcoholic Beverage Control Authority's (ABC) Logistics Division's forecast and demand planning software, was implemented to predict future retail sales, improve delivery accuracy to meet demand and decrease the amount of out of stock products in retail stores.

The initial implementation was a monthly forecast based on sales data per product and store for the prior two years. This past year, Virginia ABC modified the forecast to a weekly basis and included modifiers for planned promotions, promotions and events from prior years, stock outs within stores and product trends. The objective was to increase the in-stock percentage to increase revenue and consumer satisfaction.

This improvement in data quality meant Virginia ABC could also deliver far more accurate demand forecasts to suppliers and hold them accountable for meeting demand plans with supplier scorecards. The scorecard measures a supplier's performance, ability to deliver products on time with the demand and without incident. The supplier's scores are taken into account for listings and promotional decisions.

Virginia ABC successfully implemented and improved the two business operation systems, resulting in:

• Increased sales by predicting high selling products and reevaluating slow moving products in retail stores, as well as estimate sales amounts for product promotions.
• A collaborative effort between Virginia ABC's logistics, marketing and retail divisions to make more constructive store inventory, product sales and promotion decisions.
• A more effective, transparent partnership between Virginia ABC and its suppliers.
• Forecast and demand planning (or THRIVE) allows Virginia ABC to take an in-depth look at the retail environment with product trends and predicted sales. The software displays product sale estimates based on store performance categories and delivery dates.
• The forecast unit was decreased from a calendar month to a week as that matched the repeating pattern of activity (promotions, number of weekend days, peak sales, delivery cycles and most holidays)
• Prior stock outs were adjusted so that they did not incorrectly reduce the current demand
• Prior promotions sales lifts were separated from normal demand to get a more accurate demand baseline
• New promotions are planned with a volume lift to be fulfilled more accurately in store

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