Whoever bought the most got the best purchase price. Whoever had the largest headcount in the back office could afford to reprice more often. Price advantage was therefore largely a matter of scale: large players won, smaller ones followed with a delay. That mechanism comes under pressure as soon as the work behind a price — calculating, repricing, guarding margin per order — is partly done by AI instead of by a team doing it by hand.
A price a customer sees is the outcome of work the customer does not see: checking cost price build-up, tracking competitor prices, recalculating margin when purchase costs change, assessing exceptions for large or unusual orders. For the largest part of that work, a distinction can be made:
Where this already works this way, a quote can be ready within hours instead of days, and a price change by a competitor is processed within a day instead of at the next pricing round. Where it does not yet work this way, that is not down to company size but to whether the pricing data and rules have already been recorded in a way a system can use. A large company with scattered, informal pricing arrangements lags behind a smaller company with a clean pricing structure here.
The difference is not in the level of the price itself, but in the speed and consistency with which it comes about. A customer requesting three quotes notices it when one responds within a day with a substantiated price and the other needs a week because someone has to manually recalculate. On repeat purchases, the customer notices it when the price moves along with market conditions without a separate negotiation being needed for that. That is not a matter of being cheaper; it is a matter of less friction in the process that leads to the price.
The party that first hands over the computational work behind pricing to a system does not automatically win on price itself — that can remain the same or even be higher. The advantage lies in the number of cycles an organization can run per period: repricing more often, responding faster to purchasing fluctuations, processing more quotes without adding extra capacity. For a peer group, this means that the comparison on price is no longer just about list prices, but about the speed with which those prices stay accurate.
This touches on staff deployment in the back office, and the question of what an employer does with that falls outside what can be answered here: separate statutory requirements apply to that, and that decision lies with the employer. What can be answered here: which part of the pricing work in a specific company is already transferable at this moment, and which part continues to require oversight.
Price advantage is often viewed in isolation, but in practice it competes with other factors where the same shift is occurring. A lower price does not win if a competitor's delivery time is now shorter than yours, and a price advantage weighs differently if the competitor's quality perception has meanwhile risen. Whether a competitor actually delivers on its price advantage cannot always be deduced from official figures either; for that it is relevant to know how you obtain information about competitors who do not publish figures. Compare that with the way marketing texts formulate price claims, where it regularly happens that competitors' wording is barely distinguishable from one another, something related to why competitors all sound the same in their promises.
A suspicion that you are cheaper or more sharply priced than a competitor is not the same as a position you can substantiate to a customer or internally to a board. The underlying question — which work in your own organization can already be taken over by AI at this moment and which work continues to require oversight — is answered per task with the werkscan from FTE TO AI.
Name the claim you would make today about your price position relative to your peer group. Then check whether that claim can currently be substantiated with evidence, or whether it is mainly an assumption that has been carried along for some time. The free dimensiecheck is the starting point for that: you name where you believe you win, and see which of those claims can currently be defended with evidence. The full benchmark, with the comparison across all dimensions, is under construction.