making ai real with size pack optimization
TRANSCRIPT
Making AI Real With
Size Pack OptimizationExcel Can’t Touch This!
Tim Carney – 9/18/2019
Dumbest Man Alive? or Do We Have a Tendency to Overlook Things?
Before 2014, Belk Used Excel To Write Orders by Size
Applying average size ratios across stores
• Increases stock outs / lost sales
• Causes overstocks by location
• Increases markdowns
• Lowers profitability
• Causes customer dissatisfaction
2
Upgraded Merchandising & Planning Systems
• Automated Processes that used Artificial Intelligence
• Used Machine Learning to synthesize data & make better decisions
• Integrated SAS Size Pack Optimization into order process
• Some brand margins grew as much as 230 basis points over 4 years
Project Smart 2012 – 2014 – Process Automation
3
Two Distinct SAS Solutions – Size Pack Optimization
Pack OptimizationDetermines best packs to satisfy need while
minimizing costs
Size ProfilingCreates library of size ratios by
product by door
1 2
50% / 26% / 24%
S M L
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How Belk uses SAS SPO?
Business Use SAS Pack Optimization Additional Benefit
Assortment Planning
(Initial Order
Placement)
• Optimized packs by
product / store /
time of placement
• Auto PO generation
Replenishment
Forecasting
Create An Optimized
Allocation
right sizes
right packs
right locations
right time
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6
How Belk is Using Artificial Intelligence
and Machine Learning to Capture Size
Demand By Store
Size Profiling
• Uses historical data to determine size ratio demand
based on :
– Merchandise
– Location (Brick & Mortar Stores vs. Ecom)
– Time boundaries
Size Profiling – Uses AI & Machine Learning to Capture Size Demand
S M L
S M L
S M L
Store 458
Crabtree
Store 452
Southpark
Store 678
Flowood
17% / 63% / 20%
37% / 45% / 18%
12% / 42% / 46%
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Size Profiling – Our Virtual Assistant Does The Heavy Lifting
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• Lowest Profile Level - defined by
user
• System creates profiles for every
level in the hierarchy for the specified
Dept. down to Lowest Profile Level
• User reviews exceptions from their
Virtual Assistant
S M L
S M L
S M L
Branded
Knits Wovens
Polo
S M L
Ven/Class
S M . L
Vendor
S M L
WovensKnits
Lowest Profiling Level
Dept. 387
Collections
S M L
S M L
Machine Learning – Imputation Process
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SouthPark ran out of
Medium Red Polos,
but sold 3 Smalls and
4 Larges
S M L
Sold 3Sold 0
due to 0
in stock
Sold 4
S M L
Sold
30%
Sold
30%
Sold
40%
Mediums represented
30% of sales for
similar stores over the
same time period
SouthPark could have
sold 3 Mediums if they
were “in stock”
S M L
3 4
Actual Sales
Actual Sales at
Similar Stores Imputed Sales
?3
Flowood CrabtreeSouthPark SouthPark
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How Belk is Using Artificial Intelligence
and Machine Learning to Satisfy Size
Demand By Store
Pack Optimization
• To convert assortment plans into optimized packs at the style/ color/ door
level
• Tool can also provide the exact quantity to order by size for vendors that
can ship and allocate by size (“eaches”)
SAS Pack Optimization – Objective
Store 458
Crabtree
Store 452
Southpark
Store 678
Flowood
S M L
S M L
S M L
17% / 63% / 20%
37% / 45% / 18%
12% / 42% / 46%
X
X
X
108 Pcs
120 Pcs
96 Pcs
Op
timal P
acks!
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Human Interaction – Choose from 3 Pack Options
• Before an order can be optimized, the user must define the type of pack:
1
Used for Private
Brands
System
recommended packs
Vendor
Predefined
packs
Selected – packs
2
ONLY includes a single
style / color / size
3Bulk packs
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• Use constrains pack creation with pack settings:
– Define number of units per pack
– Maximum number of packs to recommend – puts a cap
on the total number of packs
– Share pack configurations across products – forces
same configurations across all colors
– Recommend multi colors into a single pack, e. g.
“Rainbow packs” or “Fun Packs”
Example
Inner Pack Units 6, 12, 18
Max # of
Packs 3
Share Pack?
yes
Multi Style Color? No
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User Guides Virtual Assistant With Pack Settings
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SPO Uses Machine Learning, Optimzation And Automation To Determine
Best Pack Combinations While Minimizing Operational Costs
Pack Optimization logic will minimize the mismatch across an entire order
• Calculates Mismatch – difference between target (optimal units) & Actual units
ExampleSketchers Athletic
Shoe
Machine Learns - Minimizes the Mismatch
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Summary - Artificial Intelligence – Accenture Labs
“Explainable AI won’t replace
people, but will complement
and support them so they
can make better, faster, more
accurate and more
consistent decisions”
"The future of AI lies in
enabling people to
collaborate with machines to
solve complex problems.
Like any efficient
collaboration, this requires
good communication, trust
and understanding."
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APPENDIX
Class 1: Knits
S LM
Using Partitions based
on a Attribute Class
Partition
Dept. : Moderate Tops
Partition
Class 2: Sweaters
XLS LM S LMS LM XLXS
Van Heusen
S/S
Knit
Saddlebred
L/S
Knit
Van Heusen
Merino
Sweater
WH Belk
Cashmere
Sweater
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Key Concept - Profile Creation - Partitioning Using Attributes
1. Static Hierarchy 2. Attribute Partitioning
FOB
Demand Center
Dept
Vendor
Ven/Class
Class*
Label
Company
Style
Style/Color
shorts
Dept
jeans caprisskirts Attribute based
on CLASS
slim
Vendor
skinny relaxedboot Attribute based
on FIT
* Class is not in static hierarchy
Key Concept - Profile Creation Flexibility – Hierarchy vs. Attribute
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Advanced attribute partitioning (in FY15)
• Store Groups - Collection of stores that
have similar size distributions for a group of
products
• Considers three situations:
1. “Comp” stores have been open “long enough” to
have sufficient data
2. “Non-comp” stores have not been open “long
enough” to have sufficient data
3. “New” stores – have no data
• Systemic activities
1. “Comp” Stores are grouped together
2. “New” or “Non Comp” Store are classified into
the overall average store group
New
Non-Comp
Store Group # 0
All Stores
Key Concept - Store Groups
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Key Concept - Imputation With Sparse Data
Tool imputes the “lost sales” that were caused by a lack of inventory by analyzing the
demand of the same item across a group of stores during a similar time period
• When there is not enough data to impute sales, SAS will omit the entire week of
sales data for that Style / Color combination
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