Automotive supply chain

optimising dealer-level inventory THROUGH demand prediction

Trusted Data were tasked by a global automotive brand to overcome legacy forecasting issues, which had negatively impacted bottom line performance

How we unlocked $57 mn of working capital in one year

Trusted Data were called to support a regional distribution partner for a global automotive brand with a network of 55 dealerships.

Having the right end-customer configuration in stock would substantially boost sales but unattractive configurations placed a substantial burden on working capital and profitability, with unsold stock quickly depreciating and eventually being sold on with heavy discounting.

Trusted Data were engaged to navigate the client to a solution by which the Planning & Procurement function could best identify the correct product mix and volume on each order cycle from Global HQ.

Leveraging Machine Learning to improve forecast accuracy


Quarterly sales forecasting error was 41%, and this led to redundant inventory tying up capital.

Lost sales opportunities caused from incorrect vehicle allocation (model & volume) to dealers.

The clients’ net profit margins were 5%. Overstocking or having the wrong vehicle models in stock was equally a supply chain and sales dilemma, placing a huge strain on the Clients’ commercial efforts in the region.


Trusted Data modelled 5 years of sales data to identify:

  • What type of vehicle would sell in the next 6 months?
  • Where and what quantity / type to move across to regional depots based on dealer demand?
  • The quantity of vehicles predicted to sell in a given time period?

Trusted Data then created a dynamic model, interpreting sales data and generating updated forecasts at each ordering interval.

By aligning the fitted sales forecast model by vehicle type (engine, colour, interior) and combining this with procurement cycles, the client benefitted from ordering vehciles in tune with local customer demand and taste profile.

Annualised Savings in year one

$57 mn

quarterly Forecasting error reduced below


YOY Vehicle (unit) Sales Increase


Planning cycle time reduction