Collection planning:
Fewer SKUs, more margin
How a cannibalism network identifies the 400 SKUs out of 1,800 as candidates for the assortment review - with only 3% revenue loss, but up to 18% less overstock and €0.78M margin improvement.
This module is part of a six-part model calculation about a fictional mid-sized fashion company (1,800 SKUs, 18 markets). All figures, datasets, model metrics and euro amounts are entirely fictional - they illustrate the methodology and the kind of effect achievable. They are not results of real clients and not a performance promise. What values are achievable on your real data is established only in a pilot project.
01 The problem - planning 1,800 SKUs when 400 are unnecessary
Why a wide assortment does not automatically mean more revenue
More SKUs = more choice = more revenue? Our analysis shows: 22% of SKUs generate 78% of revenue. The remaining 78% cannibalise one another, tie up warehouse capacity and generate overstock. The model identifies which SKUs your assortment needs - and which are candidates for review in the next assortment round.
02 Model - assortment optimisation with a cannibalisation network
The model identifies 400 SKUs as removal candidates - together they generate only 3% of revenue but cause 18% of overstock. If approved in the assortment round, overstock drops by up to 18% - at around 3% revenue decline. The €0.78M margin improvement is a net figure: saved production, warehousing and markdown costs minus foregone contribution margin - an assumption of the model calculation, anchored in the Pareto norm (around 20% of SKUs carry around 80% of revenue). The model does not replace the assortment decision - it provides the data foundation for an informed discussion in the buying and design team. The final decision additionally considers brand positioning, supplier relationships and range width.
03 Next steps for your brand
All 1,800 SKUs through the cannibalisation network. Report: top performers, cannibalisers, candidates for removal.
Next season: optimised assortment in 3 pilot markets vs. standard assortment. A/B at market level.
Data-driven recommendations for your design team: which silhouettes, colours and price points are missing from the assortment?