Eighteen slides on data readiness, AI adoption and the connected vehicle. Every figure is sourced and the sources are named on the slide. Free, and we do not ask for your email.
No form, no email, no follow up sequence. If it is useful, use it. If you want to talk afterwards, the door is there.
Demand is not the constraint. Data is.
Vehicles on the road are older, more numerous and more electronically complex than at any point in the industry's history. The parts exist. The margin exists. What is missing is the ability to find, forecast, price and fit the right part the first time, at the speed a connected vehicle now expects.
These are the ones worth knowing even if you never open the PDF. Each is attributed to its source, as published.
The compliance runway is already live, and the dates are fixed rather than forecast.
In the United States, the REPAIR Act remains in committee, so the independent channel is still waiting on statute.
Data foundations take 18 to 36 months to lay. On that arithmetic, 2030 readiness is a decision made in 2026.
McKinsey's base case puts the global aftermarket near €1.2 trillion by 2030. Its accelerated-technology scenario compresses the same pool to €588 billion.
That is not a forecasting range. It is two different industries, and which one you land in is a function of readiness rather than of luck.
Not a technology wish list. These are the clusters where operators can point to a measured result.
Slide 7 of the report states that 86% of automotive e-commerce returns are attributable to inaccurate fitment data, citing industry analyses.
We have since tried to trace that figure to a primary study and could not. Every source we followed leads back to a company selling fitment software, with no published methodology behind it. We no longer use it, and we have removed it from the rest of this site.
The underlying mechanism is real and well documented: parts are returned because the vehicle did not match, not because the box was damaged. The specific percentage is not something we can stand behind, and we would rather say so here than quietly leave it in a PDF people cite.
Everything else in the report is attributed on the slide it appears on. If you find another figure you cannot trace, tell us and we will either source it or withdraw it.
The gap between reading this and doing something about it is usually a catalogue nobody has measured. We will measure it: send a catalogue extract and we will return the audit scored, with your gaps ranked by vehicles in operation.