Context

A board was evaluating a technology-enabled services target where much of the growth case depended on the quality of data, reporting, and the underlying digital operating model. The commercial narrative was compelling, but it was unclear whether the target’s AI/data capability and management information were strong enough to support the expected scaling and synergy case.

Role

The assignment was to provide board-level challenge on commercial diligence, AI/data maturity, and integration readiness. The objective was to help the board judge whether the digital capability was truly an asset, whether reporting was decision-grade, and how much execution risk sat behind the growth story.

Actions

Reviewed the target’s data discipline, reporting quality, operational visibility, and AI-readiness in conjunction with the commercial case. Tested whether the management information could support scalable decision-making, whether the digital architecture would help or hinder post-close integration, and what level of upgrade would be needed to deliver the forecast value. Helped the board connect commercial assumptions to operational reality and shape the first priorities for post-close governance.

Results

The board came away with a more realistic picture of execution risk and a clearer separation between proven digital capability and aspirational claims. This improved decision quality, reduced the risk of over-paying for immature capability, and gave leadership a more practical view of the investment and governance needed after completion to convert the growth thesis into measurable results.

Governance learnings

When digital capability is central to the deal case, boards should treat AI/data maturity as a core diligence issue, not a side topic. Stronger outcomes come when the board tests whether reporting, systems, and decision-quality are truly fit for scale before they are priced in as upside.