Combining strategy, M&A, and integration under a single leader provides a full lifecycle, enterprise-wide view. This structure breaks down silos and creates a "closed-loop system" where post-deal integration performance and lessons learned directly feed back into future strategy and deal theses, refining success metrics beyond financials.

To avoid a broken handoff, embed key business and integration experts into the core deal team from the start. These members view diligence through an integration lens, validating synergy assumptions and timelines in real-time. This prevents post-signing surprises and ensures the deal model is operationally achievable, creating a seamless transition from deal-making to execution.

Deals fail post-close when teams confuse systems integration (IT, HR processes) with value creation (hitting business case targets). The integration plan must be explicitly driven by the value creation thesis—like hiring 10 reps to drive cross-sell—not a generic checklist.

An M&A lead's role isn't to be an expert in tax or IT, but to assemble specialists. Like a general contractor, they must know enough to spot issues ('wires sticking out of the wall') and deploy the right expert, synthesizing findings to assess valuation and integration hurdles.

Effective multi-threading isn't just about engaging multiple customer stakeholders. It also means strategically deploying your own team members—like founders, product experts, or engineers—at key moments. This "team sport" approach builds buyer confidence and de-risks complex enterprise deals.

To avoid post-close surprises and knowledge loss, marry diligence and integration leads before an LOI is even signed. This ensures real-world operational experience informs diligence from the start. The goal is to have a drafted integration thesis by LOI and a near-complete plan by signing, not after closing.

The key technical skill for an AI PM is not deep knowledge of model architecture but a higher-level understanding of how to orchestrate AI components. Knowing what AI can do and how systems connect is more valuable than knowing the specifics of fine-tuning or RAG implementation.

To prevent knowledge gaps between deal execution and integration, IFS makes the same internal expert responsible for a specific workstream (e.g., product, GTM) during commercial diligence and the subsequent integration phase, creating end-to-end accountability.

A process where the deal team hands off a signed transaction to a separate integration team is flawed. State Street integrates business and integration experts into the deal team from the start. This ensures diligence is informed by integration realities, timelines are realistic, and synergy assumptions in the deal model are achievable.