Why is inventory increasing
when sales aren’t?
A practical way to understand the real reasons behind inventory build-up — and how data, analytics and AI can help you take action.
The Enterprise AI Map
Five parts, one path from business questions to measurable value.
Business Before AI
Why understanding the business comes first.
Dimensions, Facts and Measures
How to structure the enterprise.
LLM vs TFM
Different models for different problems.
Maths Behind AI
A simple view of regression and prediction.
From Insight to Action
Turning intelligence into measurable value.
From Business Question to Action
The Business Question
Inventory is increasing, but sales are flat or declining. Why is this happening, and what can we do about it?
Understanding the Problem
Higher inventory is often a symptom, not the real problem. It can be driven by demand changes, planning gaps, supply disruptions, portfolio shifts, channel dynamics or commercial decisions.
PLM at the Heart of Everything
From idea to impact. A connected product and business lifecycle.
Consumer Insight
Turn shopper trends and preferences into winning style bets.
Range & Assortment
Plan the right styles, colours and sizes for every store and channel.
Plan & Buy
Make smarter buying decisions with real-time demand signals.
Source & Produce
Collaborate with vendors and bring collections to life on time.
Distribute & Allocate
Get the right stock to the right store, fast.
Sell (Omnichannel)
Deliver a seamless shopping experience across every channel.
Customer & Loyalty
Turn every purchase into a lasting relationship.
What the Data Typically Shows
Illustrative analysis (not from a specific customer).
Key dimensions to analyse
Common drivers
From Insight to Action
Example areas of action (will vary by business).
Improve planning accuracy
Use better demand signals and collaboration.
Optimise assortment and mix
Focus on high-velocity, profitable SKUs.
Align supply with demand
Adjust production, procurement and replenishment.
Review commercial policies
Check incentives, order patterns and channel dynamics.
Key Takeaways5 Points
Questions to Consider5 Questions
“Good questions create better data. Better data creates better decisions.
— Orane
Explore Other Enterprise Problems
Explore other enterprise problems.
Don’t Start With AI.
Start With a Business Problem.
Bring us a problem, a decision or an exception that matters. We’ll work backwards from the business outcome to the context, data and intelligence required.