Partner Awards | Business Insight
About This Award
This award recognizes a partner who has developed and implemented a point solution — such as pre-built applications or an industry offer — that uses any analytic data platform, including Teradata, Teradata Aster, and/or one of our analytic applications to deliver analytic insights to customers. This solution must be in production and must deliver measurable return on investment for the customer.
Capgemini and Coca-Cola Refreshments
Predictive Ordering for Global Beverage Company
Capgemini has been and is currently providing a host of services in multiple areas across the Coca-Cola Refreshments’ (CCR) value chain and system including its several bottlers for over eight years. During this journey we have partnered with the client to evolve a tailored approach to deliver these services and innovations, enabled by a host of capability centers setup in line with the client needs.
In this case, the client is a large bottler based out of North America where Capgemini is providing application development and project services in numerous technology areas, including business Intelligence where Teradata is heavily used.
Our client wanted to develop the solution for its retail customers who want to assess each store’s performance on supply vs. demand management and to implement an analytical solution to predict the order placement for the store. This application provides order entry support to an account manager when visiting a customer store location. Hosting the solution on CCR’s CRM customer enabled cloud allows the account managers to make informed decisions based on global, real-time data visibility across category, account and segment. This also enabled the business to respond to industry and market trends and use consumer insights and point- of- sale data more effectively.
Order data from the predictive order application is stored in Teradata along with pricing, POS, settled Invoices and weather details. A set of complex algorithms uses this information to predict order quantities by outlet and SKU and provides these suggested order amount values to Frontline Sales and Call Center Ordering applications.
Future sales predictions were made using the weather details and events data provided for each location. This also helped Coca-Cola Refreshments to look at new ways to improve sales (for e.g. introduce promotions) based on history order/sales information provided and in-turn the added efficiency in company’s manufacturing and distribution process.
The goal of this solution is to drive down the order prediction vs. actual deviation ratio to under 2%, thereby increasing forecasting accuracy, reducing out-of-stock scenarios, improving delivery planning, and ultimately driving down distribution costs..