This document provides an overview of data science and its applications in retail. It discusses how a retail company in Kazakhstan was previously using Excel to determine what and how much to purchase from suppliers, but faced challenges with taking too much time, making mistakes, and difficulty scaling up. A case study is then presented on using data science to help the retail company with inventory planning and management by analyzing past sales history, demand forecasts, stock levels and purchasing parameters to avoid stock outs and optimize purchasing decisions.

1. Understanding of data science & career opportunities
DATA SCIENCE

2. A Retail Story
Electronic Retail in Kazakhstan
❏ Since 1992
❏ 80 stores & 20 warehouses
❏ 10,000+ orders per day
❏ 60,000+ SKU
❏ 1C ERP software

3. ❏ Take a lot of time
❏ Do the mistakes
❏ Scale-up is too hard
Problem
1. What items should we purchase from suppliers?
2. How many items should we purchase?
→ Using excel to find which items should purchase

4. What is Data Science

5. Data Science vs Business Intelligence

6. Retail Story - Recommend of purchasing

7. Case study in retail
● Sales History
● Same year
● Past year
● Usage per day
● Sales History Adjustments
● Sales Demand
● Zero Days
● Minimum
● Maximum
● Estimated usage per day
● Effective Inventory
● Store Stock Cover Days
● Warehouse Stock Cover Days
● Buying Unit
● Minimum Order Quantity
● Multiple Purchase Order
● Multiple Transfer Order
● Cross Docking Quantity

8. Case study in retail

9. Case study in retail
I. What happened?
A. Store A sales decreased 15% vs same day last year
II. Why did it happen?
A. Sales of key department decreased 20% due to key products out of stock.
The key products contributes 30% of department sales
B. Number of customers (invoices) decreased 15% due to heavy rain yesterday
III. What will happen?
A. Suppliers can’t deliver incoming orders of these key products within this
week
→ Sales continues decreasing 18% next week
I. What should I do?
A. Find & purchase the alternative products to store.

10. Case study in retail

11. THANK YOU
Alex Nguyen
CTO, Product Manager & Co-Founder Magestore Technology JSC.
E: alex@magestore.com
P: +84 93 792 9396
twitter.com/alexmagestore