The problem we are tackling here is “Design Compensation Incentives Based on performance of the Store Managers”. We can take the store sales as a proxy to indicate the performance of the manager. The model can be used to set sales target to their respective store managers. The variable payout is dependent on the manager’s ability to exceed the target.
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.
Problem description Business Problem: Rossman is Germany’s second largest drug store chain with more than 1000 stores across the country. Every month, the store manager needs to set targets for the sales team and design incentives for them. Currently, the managers set the targets based on their intuition of how much the sales are going to be in next month- which often leads to wrong target settings. Setting targets that are too high or unrealistic can lead to failure of
One of the largest challenges facing small and medium restaurants is that of competing against big chains with better information infrastructure – an advantage that allows the big chains to plan resource allocation more precisely based on demand and other factors. iChef provides this platform for small restaurants “making enterprise level technologies affordable and understandable for small restaurants”.
Problem Description: FMCG companies like Nestle face trouble in forecasting demand for smaller
regions which comprises nearly 50% of their business and is highly critical. This is due to high volatility in
demand. Due to this problem more often than not the sales force in these regions face a situation
wherein they are either short of inventory and unable to meet demand or have piled up inventory at
warehouses. A model that effectively forecasts sales can be tested on a small region (in this case