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Engineering

Smart sales forecasting solution increased forecast accuracy and optimized inventory costs for Nigerian Food and Beverages Company

Smart sales forecasting solution increased forecast accuracy and optimized inventory costs for Nigerian Food and Beverages Company Banner

Client Profile

The client is the Nigerian division of the Coca Cola company. They cater high quality and healthy fruit drinks, juices, dairy products and snacks from thousands of depots to both urban and rural areas across the nation.

Business Need.

The beverage company used legacy systems to forecast sales for its multiple product lines and retail openings across regions.

However, sales forecasts of the company were inaccurate because:

  • The parameters feeding into the forecast such as seasonality, location, economic conditions etc. were incorrect and not regularly updated.
  • Limited visibility across existing systems to manage raw materials procurement, location-based promotions and accurate delivery of finished products.
  • Lack of consistent data to predict adjustments in demand spurred by marketing promotions and discounts that resulted in inadequate supply of in-demand products.

To manage product manufacturing lines and match demand and supply for every SKU at every store, the company was looking for a smart demand and sales forecasting solution to accurately forecast sales for six months in advance.

Challenges.

Hitech data scientists had to find a way to gather appropriate data from relevant data sets, while meeting challenges like:

Solution.

We delivered a sales forecasting solution using Time Series forecasting, regression, boosting algorithms and Machine Learning models to predict sales and likely effect of marketing promotions with accuracy for each SKU at every location.

Approach.

Business Impact.

Enhanced brand level 6-month forecast accuracy to 97%
Enhanced location level 6-month forecast accuracy to 95%
Better allocation of inventory per SKU
Reduced inventory costs
Increased re-construct rates to maximize sales productivity and average revenue per user
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