Nisum consolidated historical data for effective forecasting and helped determine the best market segments to forecast sales and future demand with an effective marketing plan.
The client is able to create effective marketing plans to forecast sales and future demand, resulting in:
|
+40% |
-55% |
+8-10% |
Business Challenge
A multinational consumer goods client had a business need to improve the accuracy of their sales and inventory predictions based on historical data to improve their sell-in and sell-out forecast because the client was experiencing:
-
A drop in segment sales
-
Difficulty analyzing and providing proper forecasting
-
Manually processed inventory management
-
A manual process of an MS-Excel based approach for forecasting the sales for future and inventory needs to maintain stores
-
Solution
Nisum consolidated historical data as well as additional sources for effective forecasting and helped the operations and marketing team determine the best market segments with an effective marketing plan to forecast the sales and the demand for the next 6 months, resulting in:
-
An improvement in sales by taking a rapid, robust, and modular approach for the construction of machine learning models for client-segment-brands in weeks
-
Boosting segment sales by maintaining the inventory for all seasons by utilizing various time series components such as trend, seasonal and cyclical for the effective decomposition of time series data
-
The ability to predict the next 3 years of sales using data that is highly accurate with near real-time values by utilizing an advanced machine learning algorithm such as ARIMA to produce optimal simulations
-
Improved ROI by optimizing inventory management by measuring the forecast accuracy and tracking the model performance periodically using MAPE, MSE, RMSE, and R-Square (measure values to reduce errors in the predictions) based on the CRISP-DM model for better demand forecasting
Feel free to contact us for more information on how Nisum can drive results for your company.
