Comparing basic vs advanced inventory model in supply chain management for retail store operations

1. Choosing the
right inventory model
in
Supply Chain Management
Basic Vs Advanced
AMAL DEV M

2. Basic: Discount Hypermarket
• Hypermarket chain consisting of 25 stores across the country and a small
ecommerce presence
• Providing a wide variety of products: Fruits & Vegetables, Beverages, Grocery, Meat,
Fish & Poultry, Dairy, Apparels, Plastics, Utensils, & Crockery, Home Furnishing
• Inventory model of FMCG business is taken under consideration here as it the only
category under complete automation
• FMCG business consists of about 5000 SKUs consisting of Food plus Home &
Personal Care selling throughout the year
• Vendors supply to the Distribution Center where stocks are stored (WH), cross-
docked(CD) and also direct to stores(DTS) in boxes with inner and outer case pack

3. Basic : Min Max Model
• The Min/Max inventory ordering method is a basic reordering mechanism that is
supported by many ERPs and other types of inventory management software
• The “Min” value represents a stock level that triggers a reorder and the “Max” value
represents a new targeted stock level following the reorder at SKU level
• Before setting up the Min-Max the core and non-core items need to arrived at
Min Reorder Point Order is triggered once the On Hand is below the min
Max Upper Limit The maximum quantity that can be kept
Core Top Seller The item contributing to 70% of sales
Non-Core Bottom Seller The item contributing to remaining 30% of sales

4. Basic : Arriving at the Min-Max
All min-max calculations are based on last 6 months sales in an excel template by the SCM team and input to
the system
Min Quantity
• For Core items, Min is taken as stock cover up to 21 days
• For Non core items ,Min is taken as stock cover up to 14 days
Max Quantity
• Min Quantity + outer case pack, for DTS supply
• Min Quantity + inner case pack, for WH supply
When OnHand < Min , Order Quantity = Max – OnHand , rounded to case pack
All min-max calculations are based on last 6 months sales in an excel template by the SCM team
Core and Non-Core items are revised annually
Review time and Vendor Lead times are taken as 7 days as FMCG supply happens every week

5. Advanced : Mainline Department Store
• Department store chain consisting of 650 stores and ecommerce presence
• Providing a wide variety of apparel, home and living products in women’s
accessories,men’s,children’s,jewelry,bags and footwear
• The department store chain has a range of 3000 Basic SKUs diversified across the
product divisions which run for 52 weeks
• Vendors supply to the Distribution Centers for imports and Store Service Centers for
domestic vendors where stocks are cross docked respectively to stores
• All the domestic product divisions follow a single forecast driven inventory model

6. Advanced : Forecast Driven Model
• The output of the Time Series Forecasting module is a forecasted, regular and total
(regular plus promo) demand by week, by SKU-Location
The Unit Regular Demand Forecast = The Average Rate of Sale x the Seasonal
Factor ,for a Given Week for a Given SKU/Location
• The forecast generated at SKU-Location level is rolled up at multiple levels of
merchandise hierarchy and linked to the order management tool
• The Forecasting module reduces forecast error by continuously comparing multiple
historical demand patterns to the current actual performance of an SKU

7. Advanced : Seasonal Factor x ARS
Seasonal Factor
• Seasonality: Repetitious behavior in demand for products driven by casual
factors like weather or holidays
• Drives the shape of the profile
• Seasonal Factor: Weekly index of “seasonality” that represents a week’s
relative strength in the year
• Used to forecast demand for that particular week
ARS
• The current week’s sales are divided by the Seasonal Factor for the current
period in order to arrive at the De-seasonalized Average Rate of Sale
ARS = (Current Sales)/(Seasonal Factors for the Current Period)
• Calculates the ARS for each Method (3, 6, 12, 26, 52 week) and closest to
previous week sale is chosen as the best ARS

8. Basic Vs Advanced : People
Factors Basic Advanced
Buyer involvement High especially during
promotion cycles
Less as the dynamic
forecast help planning in
advance
Subject matter
expertise
Less as it’s a simple and
basic model
Need experts to train other
users
Documentation Need to be created as and
when used
Existing documentation
provided by software
provider
Ownership with
SCM team
Low as Multiple teams
involved
High as the organization
trusts the system

9. Basic Vs Advanced : Process
Factor Basic Advanced
Pricing and
Promotions
Manual intervention with buying
team to build inventory
Seasonal factor captures the
peak on a weekly basis
Demand
Fluctuation
Need to re-adjust the min max
parameters or raise manual
purchase orders
Functionalities like promo
factor and planned sales days
can help build additional stock
cover
Order
management
Manual intervention is required Completely automated unless
otherwise required
New Product
Introduction
(NPI)
NPIs need to be planned with
buyer instincts and brand inputs
Functionalities like Parent Child
Relationship can help link new
item with existing item as per
requirements
Key Performance
Indicator(KPI)
Vendor Fill rate and In-stock % Forecast Accuracy and Service
Level

10. Basic Vs Advanced : Technology
Factor Basic Advanced
Suitability Feasible so far for only FMCG
products with smaller lead times
Feasible for all types of products
Scalability The model is feasible to limited
number of stores
Addition and closing of stores
can be easily taken care off
Implementation Easy to implement as its people
driven
Tough to implement as it would
need capital and infrastructure
investment
Integration with
business chain
Low as systems are not linked
with each other leading to silos
High as the tool is integrated
with multiple functions like
Vendor order manager through
EDI
Maintenance down
time
Few hours on Monday morning High with weekly batches

11. Summary
Choosing a suitable model depends on the following
Long term planning
• Investment on the model needs to looked as a long term benefit than immediate gains
Cost
• The Return on Investment ROI needs to be considered while choosing a tool
Size of Operations
• A retailer with 50 stores will need extremely opposite systems to one with 500 stores
People Execution
• Technology is only good as the people who use it hence the end users of the tool determines its effectiveness

12. References
• https://www.lokad.com/min-max-inventory-planning-
definition#:~:text=The%20%E2%80%9CMin%E2%80%9D%20value%20r
epresents%20a,EOQ%20(Economic%20Order%20Quantity)
• http://assets.teradata.com/resourceCenter/downloads/Brochures/DCM_O
verview_final.pdf
• https://docs.oracle.com/cd/E12440_01/rpm/pdf/150/html/merch_impg/
RMS.htm

13. THANK YOU