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Mitzera's CEO argues that his team's ability to explain the fundamental reasoning behind every experiment, rather than just following a standard checklist, built immense confidence with acquirers during diligence. This approach demonstrates a deeper command of the science and accelerates trust in a high-stakes process.
To overcome skepticism around complex products like AI, leverage internal networks for social proof. Have your CTO ask their engineering contact at the target company to send a note to the economic buyer (e.g., the CRO) vouching for your company's technical credibility. This cross-functional validation builds immense trust.
Shifting the conversation from "moving faster" to "investing wisely" helps get stakeholder buy-in. It highlights that experiments prevent wasting significant time and money on suboptimal or failing ideas, making it a powerful risk management tool.
Turbine's pharma partners consistently praised the deep biological competence of its science team. This ability to engage as scientific peers, not just data scientists, built essential trust for early deals when the AI platform was still largely unvalidated.
Instead of seeking validation, leaders should test their strategy like a scientist. Formulate a specific hypothesis about customer value, commit to a clear test and a decision rule beforehand, and be prepared to pivot if the data proves the hypothesis wrong. This avoids confirmation bias.
During diligence, an investable founder is transparent about current risks (e.g., a major customer account is in jeopardy) and presents a mitigation plan. This candor is more valuable and trust-building to an investor than a founder who projects a flawless, risk-free business.
Centana Growth uses its deep diligence process to uncover operational insights for founders. In one case, they collaboratively identified a flaw in a company's core matching algorithm during a diligence session, leading to immediate improvements before the deal even closed. This reframes diligence as a value-add activity.
To build credibility for a new safety device without industry access, the founder hired a senior NASA engineer as a consultant. Leveraging expertise and simulation tools from an industry with even higher safety standards, like aerospace, provides powerful third-party validation that can overcome skepticism from incumbents.
Instead of a bloated checklist, Milliken focused its diligence for its largest acquisition on four critical questions tied directly to the investment thesis. This allowed a team of 100+ to prioritize efforts, "fail fast," and avoid analysis paralysis on the path to a go/no-go decision.
Instead of only the buyer investigating the target, successful M&A involves "reverse due diligence," where the target is educated about the buyer's company. This transparency helps the target team understand how they will fit, fostering excitement and alignment for the post-close journey.
To get Google's TPU team to adopt their AI, the AlphaChip founders overcame deep skepticism through a relentless two-year process of weekly data reviews, proving their AI was superior on every single metric before engineers would risk their careers on the unconventional designs.