Company A, a global electronics manufacturer, was looking for ways to increase its sales of home appliances in Germany. The country has a distributed retail structure where each store is owned by each individual who makes operation decisions, instead of a centralized structure where a manger from the headquarters is responsible for store operation. This complex retail structure often results in inaccurate demand forecasts, which in turn leads to missed sales opportunities or excess inventory. To solve the issue, Company A has adopted Cello Demand Sensing of Samsung SDS.
What is Demand Sensing?
Demand sensing is a demand forecasting method that leverages a range of information, such as real-time sales data, previous promotion history, etc., and new mathematical techniques to create an accurate set of demand forecasts.
Cello Demand Sensing is a demand forecasting system that creates weekly sell-out forecasts which can be used in a number of different areas, including sales and marketing, by merging Samsung SDS’ own integrated logistics platform Cello with SCM solution technologies and big data analytics Brightics AI.
Uses of Demand Sensing
Cello Demand Sensing can largely be adopted in the following two ways.
First is sell-out forecasting. Machine learning algorithm analyzes vast volumes of big data, such historical sales data, previous promotions of a customer (store) and its competitors, the store’s promotion plans, consumer benefits, weather, holidays, population, income level, etc.It then figures out how they have affected its sales so far. Based on the results of the machine learning, analytics engines of Cello Demand Sensing runs simulations of how much the store or a certain item will be selling and creates weekly sales forecasts.
To find out more about Cello Demand Sensing of Samsung SDS, visit Cellologistics.com and download the white paper.