Using an tool we had at our disposal, we looked the at the sales data for the past five years to ascertain what needed to be done. Done for ESCP MBD Master's Big Data and Analytics

1. Team 2
Walton
Emilie Debedde, Ediz Kocabas, Ziae Mustafa, Lorenzo Tozzi, Shivanand Rai, Jonathan Scheepers

2. The board
● Chief Financial Officer
● Chief Supply Chain Officer
● Sales manager
● Store Manager
● Chief Marketing Officer
● Category Manager

3. Chief Financial Officer
Core mission: To drive profitability and growth
KPI Description Measure
Profitability Understand the gross profits on different granularities of data Revenue minus costs
Year over Year Revenue
Growth
Understand the percentage growth on a time series analysis Percentage difference in sales

4. Chief Financial Officer

5. Chief Financial Officer

6. Chief Financial Officer

7. Bremerton

8. Bremerton
90%
95%
100%
105%
110%
115%
120%
2011 2012 2013 2014 2015 2016 2017 2018
Indexed population
Seattle Tacoma Bremerton

9. Bremerton
● Growth
potential
● Subject to
competitive
forces
● Highest
relative share
spent on snacks

10. Chief Supply Chain Officer
Core mission: guarantee in-store product availability while optimising the
supply chain cost trade-off
KPI Description Measure (UoM)
OTIF Delivery capability of assortmentto stores Orders perfectlyfulfilled (%)
OWC Inventory levels on hand Operating current assets (EUR)

11. Delivery capability
KPI: delivery capability
● Warehouse quantity/size trade-off
○ Proximity to stores
○ Size
○ Centre of gravity (units sold)

12. Store locations
City Country Latitude Longtitude Units DC
Salem USA 11.6680 78.1503 5701East
Tacoma USA 47.2354 -122.4525 5311North-West
Seattle USA 47.6735 -122.3315 3815North-West
Los Angeles USA 34.0551 -118.2570 3812West
Spokane USA 47.6600 -117.4058 3651North-West
Portland USA 45.5335 -122.6501 3595North-West
San Diego USA 32.7279 -117.1553 3594West
Hidalgo USA 20.5308 -99.0569 3546South
Bremerton USA 47.5399 -122.7570 3403North-West
Beverly Hills USA 34.0791 -118.4048 3330West
Merida Mexico 20.9842 -89.6208 2706South
Vancouver Canada 49.2819 -123.1187 2623North-West
Orizaba Mexico 18.8502 -97.1036 1907South
Acapulco Mexico 16.8991 -99.8355 1583South
Yakima USA 46.5932 -120.5478 1548North-West
Mexico City Mexico 19.3714 -99.1503 797South
Victoria USA 22.2855 114.1577 740North-West
Walla Walla USA 46.0657 -118.3327 412North-West
Bellingham USA 48.7642 -122.4682 381North-West
San Francisco USA 37.7780 -122.4313 319West
Guadalajara Mexico 20.6736 -103.3513 192South

13. Centre of gravity method (units sold)
DC Units Latitude Longtitude City
East 5.701 42.47128 -70.920761 Swampscott
North-
West
25.479 47.42983 -120.324699 Wenatchee
West 11.055 35.37329 -119.018715 Bakersfield
South 10.731 20.52715 -97.462923 Poza Rica

14. Inventory on hands
KPI: inventory on hands
● Reduce lead time by sourcing locally
○ Short lead time
○ Reduction in safety stock
○ Agile fulfilment
○ Increase in stocking points

15. Safety stock evaluation
𝑆𝑎𝑓𝑒𝑡𝑦 𝑆𝑡𝑜𝑐𝑘 = 𝑀𝑎𝑥 𝑑𝑎𝑖𝑙𝑦 𝑢𝑠𝑎𝑔𝑒 × 𝑀𝑎𝑥 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 𝑖𝑛 𝑑𝑎𝑦𝑠 − (𝐴𝑣𝑔 𝑑𝑎𝑖𝑙𝑦 𝑢𝑠𝑎𝑔𝑒 × 𝐴𝑣𝑔 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 𝑖𝑛 𝑑𝑎𝑦𝑠)

16. Safety stock reduction
𝑆𝑎𝑓𝑒𝑡𝑦 𝑆𝑡𝑜𝑐𝑘 = 𝑀𝑎𝑥 𝑑𝑎𝑖𝑙𝑦 𝑢𝑠𝑎𝑔𝑒 × 𝑀𝑎𝑥 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 𝑖𝑛 𝑑𝑎𝑦𝑠 − (𝐴𝑣𝑔 𝑑𝑎𝑖𝑙𝑦 𝑢𝑠𝑎𝑔𝑒 × 𝐴𝑣𝑔 𝑙𝑒𝑎𝑑 𝑡𝑖𝑚𝑒 𝑖𝑛 𝑑𝑎𝑦𝑠)
25% reduction in lead time

17. Sales Manager
Core mission: set target to the store manager, nurture high performance sales teams,
manage budgets, adapt selling strategies
KPI Description Measure
Sales Target Ratio Measures seasonal performance & understand whether
the store is outperforming or underperforming during the
period
%Actual Revenue / Forecasted revenue
ARPV (Average
revenue per visitor)
Measures customer profitability and propensity to spend.
Allows to assess the store marketing & merchandising
strategies.
sales revenue / # customer
Sales
department product
performance target
Understand which department generates the higher
revenue and set sales target for the most profitable
product categories.
# of Sales per product Department

18. Dashboard
2013 2014
Average
Revenue
Average
Unit
Sold
Bremerton
State or Province : WA
Year : 2014
Av.Revenue per visit: 13.52$
Av. Revenue per unit 3,44$
Av. Unit sold : 4,052
Walton Global Sales

19. Forecasts
RealisticSales target: 2.5%increasein salesfor the followingyear
Targetratio n+1= % / n*1.0025
Prevision interval : 95%
Sales Forecasts
Bremerton

20. Zoom on Product Departments
Product Department :Produce
Revenue per unit : 3,911
Total revenue : 1043

21. Store Manager
Core mission: Manage in store activity
KPI Description Measure
OVA (Group of KPIs):
• Margin
• Margin by category
• Units Sold
• Units Sold by
department
• Measure of the profitability of the store
• Measure of the profitability of a product category
• Goods sold in a certain period
• Measure of the sales of the products belonging to each
department
Financial trends and performance
Client income
distribution
Measure of the wealth of the store customers Number of customers by revenue by income
range
Store frequentation Measures store visits over time Number of visits
Active Customers Number of loyal customers Number of Active Customers

22. Dashboard
Track Store Activity – General Info to answer management
needs

23. Dashboard
Visits in the Store and Number of active Customers

24. Global Category Manager for Vegetables
Core mission: Maximize sales of responsible category
KPI Description Measure
Category
Revenue Growth
(CRG)
Category Revenue performance overtime 1- (CategoryRevenue per year/
Category Revenue last year)
AVG Units Sold
(AUS)
Comparisonof store-specific categorysales
performancewith worldwide performance
1- (Local AVG Units Sold /
Worldwide AVG Units Sold)

25. Global Category Manager for Vegetables
Revenue of vegetables globally increasing

26. Global Category Manager for Vegetables
KPI:CRG

27. Global Category Manager for Vegetables
KPI:AUS

28. Chief Marketing Officer
Core mission: Knows the customer inside out
KPI Description Measure
Demographic Spending Understand the spending pattern of each demography and
decide which one is the most profitable and to focus on
Demography Spend/Visit
Segments Buying
Patterns
Understand what items each Segment is buying and how often Product Categories consumption by
demography
Market Share Understand how the organization is performing for demographics
compared to other brands
Revenue of company against all the total
market share
Customer Loyalty Understand the number of store visits per segment and
understand how to improve it
Number of visits by demographics/unit time

29. Chief Marketing Officer

30. Chief Marketing Officer

31. Chief Marketing Officer
1.336% Average Penetration
2.032% BrementonPenetration
Rentals
Small Family Big
Spenders
Big Family Big
SpendersBig Family Small Spenders
High income Small
Spenders

32. Chief Marketing Officer
1.336% Average Penetration
2.032% BrementonPenetration
Rentals
Small Family Big
Spenders
Big Family Small Spenders
High income Small
Spenders

33. Chief Marketing Officer
1.336% Average Penetration
2.032% BrementonPenetration
Small Family Big
Spenders
Big Family Big
Spenders

34. Thank you for your attention
Appendix for code (Cluster Analysis and Regression):
https://github.com/Shivanandrai/IBM-Retail-Analysis-Data