Turn transformation into financial impact.
Transformation is often launched to solve a performance problem — yet the organization can emerge from it with another project completed, without having fundamentally increased its ability to transform.
The starting point is therefore not technology, methodology or a transformation program. It is an economic objective: unlock trapped cash, protect EBIT, improve revenue performance or remove structural inefficiency. The question is then how to bring the right capabilities together around that objective and solve the problem from inside the business.
In practice, the obstacles rarely sit within one function. Cash can be trapped between Sales, Operations, Finance and Technology. Different functions describe the same reality through different data, processes, priorities and professional languages. Transformation becomes slow when these interfaces become translation problems.
This is where AI changes the economics of transformation. Generative AI can help reconstruct processes from fragmented information, structure conversations and expert knowledge, connect different representations of the same reality, and accelerate analysis. The objective is not to replace expertise, but to reduce the friction between experts so that a small cross-functional team can work from a shared understanding and iterate faster.
The approach is deliberately lean: create executive gravity around one measurable economic outcome; bring the right people together around the business problem; use AI to remove unnecessary analytical and coordination friction; and establish a small operating model that owns, improves and scales the solution.
Three examples illustrate the model.
In Order-to-Cash, a cross-functional team across Sales, Commercial, Operations, Finance and Technology addressed a €15m cash opportunity and reduced DSO by three days in two months in a pilot region. The breakthrough was not a new system, but a different way of working across the existing system.
In Intercompany, a fragmented process involving more than 20–30 FTE was redesigned around a lean core team of five, generating more than €300k of recurring annual efficiency gains while creating a foundation for more granular pricing and faster adaptation.
In Revenue Insights, more than 40 experts had been reconciling Excel-based views between Sales and Finance. A small mixed team established one trusted revenue view, reducing the recurring expert effort to around six people and creating more than €200k of annual efficiency potential. Adoption only happened when Sales became part of the ownership model.
The strategic question is therefore not simply whether an organization can execute its next transformation.
It is: what capability will this transformation leave behind?
Because the ultimate objective is not to make transformation a recurring dependency — but to make the organization increasingly capable of transforming itself.