Retail

Forecasting Store-wise Sales for Smart Sales Incentives

Application Area: 

Project Details

Term: 

2019

Students: 

Anamika Yadav, Harish Bommerla, Lasya Priya, Nisha Kumari, Padmini Durvasula, Vipul Soni

University: 

ISB

Presentation: 

Report: 

Problem Description

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.

Forecasting Product Demand for a Retail Chain to Reduce Cost of Understocking and Overstocking

Application Area: 

Project Details

Term: 

2019

Students: 

Konpal Agrawal, Prakash Sarangi, Rahul Anand, Raj Mukul Dave, Ramchander G, William D’Souza

University: 

ISB

Presentation: 

Report: 

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.

Optimizing Operational Spend by Predicting Product Sales

Application Area: 

Project Details

Term: 

2019

Students: 

Aditya Verma, Amit Kumar Gupta, Neeraj Nathany, Prateek Singhvi, Varsha Shridhar, Vishal Abraham

University: 

ISB

Presentation: 

Report: 

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.

Sales Forecasting for Rossmann Stores

Application Area: 

Project Details

Term: 

2019

Students: 

Debajyoti Sarkar, Nishant Toshniwal, Ravi Batra, Raunak Singh, Vibin Varghese, Eeha Ashok

University: 

ISB

Presentation: 

Report: 

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

Forecasting restaurant sales using data from iChef, weather forecasts, and holiday information

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Nicholas Danks, Isaac Martinez, Mahsa Ashouri, Paul Rivera

University: 

NTHU

Presentation: 

Report: 

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”.

Forecasting the daily number of customers in each restaurant

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Edison Lee, Celia Chen, Sehyeon Jeong, Guan-Jie Chen, Web Yuan

University: 

NTHU

Presentation: 

Report: 

Business Problem

We are going to let manager of each restaurant know how busy they will be tomorrow by this business forecasting. The forecasted value would be used as a mental preparation of manager.

Data

Inventory Management through Sales Forecasting

Application Area: 

Project Details

Term: 

2017

Students: 

Anand Abhishek, Bharath Sankaran, Mayank Thapliyal, Rohan Chakraborty, Urvashi Surana Sunil, Varun Madnani

University: 

ISB

Presentation: 

Report: 

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

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