Bad inventory planning can have a negative impact leading to loss of sales at the retailer end (understocking) or an inventory build-up across the chain (overstocking). This can result in potential losses to all stakeholders in the chain. Forecasting can help demand planners of retail chains make better decisions regarding the right quantity of products to stock on retail shelves.
In the retail business, it is crucial for the firms to accurately forecast sales in the future to prepare themselves and optimize costs. Over-estimating sales can lead to a significant cost of inventory holding and even losses due to expiry in case of perishable items. There could also be a scenario of underutilized resources in manufacturing be it machinery or labour. Underestimation of sales in forecasts can lead to loss of business opportunity.
BASF is currently the world largest chemical company. In 2017, BASF posted sales of €64.5 billion and income from operations before special items of approximately €8.3 billion. They have broad portfolio ranges from chemicals, plastics, performance products and crop protection products to oil and gas.
Heatwave is a swimsuit e-commerce seller on the Tmall.com. They designed and manufactured their swimsuits and sell them on the Tmall platform. In this project, our team collaborated with Heatwave to work on the forecasting job of predicting swimsuit sales for the next month to assist in inventory management.
Introduction of Our Client: SIG In this project, our client is SIG Combibloc. SIG is a leading systems & solutions provider of carton packaging and flexible filling machines for beverages and food, helping bring food products to consumers in a safe, sustainable and affordable way.
In this project, we collaborate with AsiaYo, an online B&B booking platform company headquartered in Taiwan, to work together on solving their business problem by using forecasting methods. One challenge facing AsiaYo is the revenue lost when they are lack of available rooms on holidays or special peak periods. Considering the enterprise level and resource, we find that it will be more affordable and understandable to focus our solution of this business problem on certain popular areas.