Lost sales and markdowns cost retailers $1.4 trillion and remains one of the biggest challenges in retail today. To thrive in a hyper-competitive market, retailers are turning to AI and optimization to eliminate inventory guesswork so they can make better, more profitable merchandising, allocation and fulfillment decisions.
Miles Barger, VP of Merchandise Planning, Allocation, and Inventory Optimization at Lucky Brand, shares insights on how his team is embracing AI to optimize allocation and store fulfillment with Celect.
This webcast covers:
- Why previous allocation and fulfillment processes were inefficient
- How Lucky Brand was able to rethink style allocation and predict localized demand
- Ways Lucky Brand changed its fulfillment approach to pull inventory from slow-turning stores and speed up order delivery
- The operational impact of inventory optimization – avoiding markdowns, minimizing sellouts, increasing full-price sales and maximizing gross margins
- How Lucky Brand significantly increased sell-through and margin with Celect Allocation and Fulfillment Optimization
12. Inventory Management Challenges To Solve
Planning and Allocation
Ø All planning tools are excel
Ø Labor intensive and room for errors
Ø Automated system driven by analytics
Ø Facilitate end – to- end planning, utilizing one system
(approach)
Ø Pre-Season targets –> Style Planning -> allocation
-> fulfillment
Ø Reduce the total amount of inventory carrying costs,
especially in e-Commerce and Canada
Ø Dynamic denim replenishment (50% of the business) driven
by demand forecasting
Ø Utilize attributes to influence depth and assortment
allocation by store
Ø Store specific optimized assortments
14. Partnership with Celect
Ø Celect allocation new approach
Ø Shuffling the deck by looking at everything
available in the DC and matching it to store need
to provide optimized store specific assortments
Ø Concept of over-recommending stores – Celect
recommending more stores or different stores
than the original intent
Ø Allocation decision is being made real-
time and is product-specific
Ø Store tiers assigned at style level, not
department
Ø Enhanced store ecom fulfillment
Ø Water-fall based decisions – to an algorithm
Ø Multiple factors, including WOS &
customer proximity
16. Implementation Challenges
Ø Timeline – more thorough discovery prior to landing the timeline by module
Ø Fulfillment was on-time without much support needed
Ø Product Attributes
Ø Integration with a 3rd party OMS
Ø Integration with JDA Allocation
Ø Integration of master data from Netsuite and JDA into Celect
Ø JDA is the system of record for most store groups
Ø Netsuite for all product information
Ø GBB Stores
Ø Lack of reporting to monitor success
Ø Translating Retail language and terminology into engineering speak
17. Implementation Benefits
17
Ø Fulfillment prioritizing slower turning stores vs prior
to implementation
Ø On-track to hit $3.5M, which is a beat to the
initial YR1 projection from Celect of $2.7m in
sales upside.
Ø Allocation module for Fall 3 2018– Holiday 2018
fashion season codes generated $898K in sales
upside via better product flow to stores. This
equates to $2.9M in sales annual upside (including
denim replenishment)
Ø Stores providing extremely positive feedback
regarding replenishment
Ø Optimized size replenishment in denim
Ø “Every replenishment carton counts!
Previously, we would ‘sort’ through the
replenishment to find what we really needed
and get that to the floor first! Now all styles
matter!”
18. Implementation Lessons Learned
Ø Implementation team structured with a business lead from P&A, and an IT lead
Ø Key learning – identify one owner from the business who has IT knowledge
Ø The integration is 100% dependent on how easily data flows between systems
Ø Completely surprised by the adoption success with allocation
Ø The team loves the tool! No pushback around adoption – on-board from day 1!
Ø It’s making them smarter and working faster!
Ø The plan tool utilizes cost available as the metric to toggle, and all of the output is in regular
price
Ø we needed to update our planning tools to utilize Celect recommendations
Ø The department recommendations in plan are in line to what our teams planned
Ø The opportunity Celect identified was in style buy quantity and channel placement
19. Next Steps
Ø Working through enhancements
Ø Replenishment by size for
fashion goods
Ø Use of Celect as basics
management tool, and
optimizing the pre-pack
percent as well as the initial
commit %
Ø Finalizing reporting ROI metrics
Ø Upgrading to version 2 of plan and buy
Ø Reduce some of the constraints in the
system (e.g. store groups) and
potentially test a channel with fewer
constraints.