This session is a continuation of “Apply MLOps at Scale” at Data+AI Summit Europe 2020 and “Automated Production Ready ML at Scale” at Spark AI Summit at Europe 2019. In this session you will learn how H&M is continuing to evolve and develop their AI platform in order to democratize and accelerate AI usage across the full H&M group, including speed to production, data abstraction, feature store, pipeline orchestration, etc. Our existing reference architecture has been adapted by multiple product teams managing 100’s of models across the entire H&M value chain and enables data scientists to develop model in a highly interactive environment, enabling engineers to manage large scale model training and model serving pipeline with full traceability. The current evolution aims to both reduce the time to introduce new features to the market as well as the learning feedback loop by democratizing AI in the organisation and persistent focus on sound MLOps principles.

1. Scaling AI @ H&M
Björn Hertzberg
Head of Data Science

2. General Information
Agenda
AI Journey @ H&M
Quick Facts and Current Use Cases
Fountainhead
A vision for Group-Wide AI Adoption
Content Personalization
The Customer AI Platform

3. General Information
H&M Group is a family of brands and businesses, driven by the
desire to make great design available to everyone, in a more
sustainable way. We offer fashion, design and services that
inspire and enable people to express their style while making it
easier to live more circular.
74 store markets
153,000 employees
4,950 stores
187 billion SEK (2020)
sales including VAT SEK
52 markets
more than
E-commerce in

4. General Information
Our Journey

5. General Information
Design / Buying Production Logistics Sales Customer
Assortment Quantification
(ASQ)
Fashion Forecast
In-price Negotiation
Supplier
Recommendation
Allocation (ALLO)
Warehouse Moves
(Movebox)
Markdown (MDO) Recommendations
Content Personalization
Customer Value
AI Foundation
Current Coverage of Value Chain
Technical Enablers
Kowledge Capture &
Best Practises
AI Exploration &
Research
AI Platforms

6. Fountainhead

7. General Information
People
Match Skills with Passion
Targeted Recruitments
Learning Culture
Process
AI Literacy
AI Platforms
Separation of Duties
Growth Enablers

8. General Information
'The Fountainhead' to accelerate democratization of AI in BT
Vision
8
Data
foundation
Capabilities Easily incubated AI use- cases
into AI foundation
Same capability for
multiple processes
Same output for
multiple analyses
Production &
deployment
PLM &
industrialization
Control tower/
measurement
IaC & common
standards
Documents &
cookbooks
AI literacy
Model
development
Data
ecosystem
Data architecture &
technology
Data
organization
Data
governance
Users
Scope of The
Fountainhead
Yggdrasil
Data
catalogue
Model lifecycle
management
Vision
Accelerate unlock of business value
across the value chain by democratizing
AI across Business Tech through an AI
platform 'The Fountainhead' and
automation to promote reusability,
integrated into the whole value chain –
enabling majority of teams and people
across H&M to unlock new value and
improve processes E2E, and to reduce
time-to-market by 50% for AI use-cases
PoC & dev.
support
Reusable
output
Visualization
Custom
er &
partners
End-users and
consumers
Business and
tech users
Product
teams in BT

9. Content Personalization
Part of our internal AI platform economy

10. General Information

11. General Information

12. General Information
Model serving – deployment strategy

13. General Information
Model Serving – Inference Graph

14. General Information
Content Personalization Engine

15. Content Personalization
Use-case: Start-page Teasers

16. General Information
Example - Teasers on Start Page

17. General Information
Contextual Bandits

18. General Information
Contextual Bandits

19. General Information
Contextual Bandits

20. Take away
▪ Scaling AI requires autonomy and alignment
▪ Allow structure to crystalize outward from the teams
▪ Unlock flow by standardizing and simplifying

21. General Information
Feedback
Your feedback is important to us.
Don’t forget to rate and review the sessions.