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© Ingka Holding B.V. 2022
Leveraging data and AI
to optimize fulfilment
operations planning at IKEA
Picture by Pixabay
14 September 2022
© Ingka Holding B.V. 2022
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Loek Gerrits
Machine Learning Engineer
BigData Republic
Alexander Backus
Data & Analytics Leader
IKEA Retail (Ingka Group)
BILLY
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“Creating a better everyday life for the many people”
Group
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465
IKEA stores, shops and
planning studios in 32
countries
174,225
co-workers
EUR 39.8 billion
total revenue
Figures from Ingka Group Annual Summary FY21
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Towards omnichannel retail
Physical store Multichannel Omnichannel
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The need for a centralized planning capability
Planning
system
Business
objectives
World state
information
Demand plan
Supply plan
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Three opportunities to improve planning
Data-driven Optimisation
Automation
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Inter IKEA Systems
(franchiser)
Group Digital
Retail
Cross-functional
product teams
A digital product organisation
Engineering
Data & Analytics
Product
Xperience & Design
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We empower co-workers to make
informed planning decisions and
positively impact IKEA's future
Support the co-worker
journey with automation
and best-in-class analytics
Provide user-friendly and
high-performant planning
tools for all co-workers
Enable co-workers to collaborate
with the end-end perspective of
an omnichannel environment
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Towards human-centred AI-assisted planning
[1] The starting point
Business
objectives
World state
information
Plans
Human-centred
planning system
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Towards human-centred AI-assisted planning
[2] A step forward
Business
objectives
World state
information
Plans
Forecasts
AI
Data
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Data Machine
learning
model
Forecast
𝑓 𝑥 = 𝑦
Generating forecasts using
three components
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Historical demand Events
T
T - 30
T - 2
T
T - 2
T - 1
T + 365
𝑓 𝑥 = 𝑦
Data
Our model uses different
types of inputs
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Expressive
Non-linear relationships
Scalable & flexible
Future iterations
Generalizable
Minimize subroutines
Tailormade
IKEA Knowledge
𝑓 𝑥 = 𝑦
Model
Design considerations for
our machine learning model
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Uncertainty
Orders
Order lines
Weight
Volume
Quantity
𝑓 𝑥 = 𝑦
Forecast
Multiple forecasts to
support specific plans
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Dashboard
Model registry
Model code
Train job
Scheduler
Predict job Evaluate job
App
Cloud-based MLOps platform for
forecasting and optimisation
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Towards human-centred AI-assisted planning
[2] A step forward
Business
objectives
World state
information
Plans
Forecasts
AI
Data
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© Ingka Holding B.V. 2022
Towards human-centred AI-assisted planning
[3] The future
Plans
AI
Reviewing
Adding
Steering
Data
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Key take-aways
Empower cross-
functional product
teams to deliver planning
solutions end-to-end
1
Have a long-term strategy
to guide your machine
learning algorithm and
system design choices
2 3
Together with users,
evolve stepwise to
human-centred AI-
assisted planning
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Tack!
Picture by Pixabay
Find us at booth
53
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