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How Lucky Brand Eliminates Inventory Guesswork with AI-Driven Allocation & Fulfillment

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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

Published in: Retail
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How Lucky Brand Eliminates Inventory Guesswork with AI-Driven Allocation & Fulfillment

  1. 1. How Lucky Brand Eliminates Inventory Guesswork with Celect Through AI-Driven Allocation & Fulfillment
  2. 2. Welcome! © 2019 Celect, Inc. All Rights Reserved.2 Miles Barger VP Merchandise Planning, Allocation, and Inventory Optimization Andrea Morgan-Vandome Chief Marketing Officer
  3. 3. Celect Overview © 2019 Celect, Inc. All Rights Reserved.3 Celect helps retailers optimize inventory decisions on what and how much to buy, where to place inventory, and where to fulfill from. +7 Patents / Patents Pending MIT AI Lab Top 50 Innovations, Groundbreaking New Technology AWARDS Gartner 2017 MQ for Merchandise Assortment Management Featured as Gartner 2017 Cool Vendor for Retail Merchandising Finalist for Daniel H. Wagner Prize for Excellence in Operations Research Practice FULFILLMENT OPTIMIZATION PLAN & BUY OPTIMIZATION ALLOCATION OPTIMIZATION
  4. 4. Retail Is Changing, Inventory Decision-Making Has Not © 2019 Celect, Inc. All Rights Reserved.4 Customer Expectations Have Changed Retail Operations & Execution Have Changed Inventory Decision-Making Has Not Changed
  5. 5. What we’ll cover today 1. Lucky Brand Background 2. Inventory Challenges 3. Partnership with Celect 4. Implementation Challenges, ROI & Lessons Learned 5. Questions © 2019 Celect, Inc. All Rights Reserved.5
  6. 6. Lucky Brand Business Overview
  7. 7. The Point, El Segundo, CA
  8. 8. The Point, El Segundo, CA
  9. 9. The Point, El Segundo, CA
  10. 10. The Point, El Segundo, CA
  11. 11. The Point, El Segundo, CA
  12. 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
  13. 13. Big Data
  14. 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
  15. 15. © 2019 Celect, Inc. All Rights Reserved.15 FULFILLMENT OPTIMIZATION PLAN & BUY OPTIMIZATION ALOCATION OPTIMIZATION
  16. 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. 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. 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. 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.
  20. 20. NOW WHAT? © 2019 Celect, Inc. All Rights Reserved.20 Learn more about Allocation Optimization https://www.celect.com/allocation-optimization Learn more about Fulfillment Optimization https://www.celect.com/fulfillment-optimization Book a 15-minute evaluation with a specialist: https://drift.me/evanc

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