{"version":1,"type":"rich","provider_name":"Libsyn","provider_url":"https:\/\/www.libsyn.com","height":90,"width":600,"title":"How to Build a Deal Model That Beats PE on Price","description":" Jeremy Segal, Executive Vice President of Corporate Development, Progress (NASDAQ: PRGS) Buyers who mistake a high LOI bid for a winning strategy are easy prey for sellers who know the growth equity playbook. Jeremy Segal's position: precision at the LOI stage is a stronger differentiator than price. Jeremy Segal is EVP of Corporate Development at Progress (NASDAQ: PRGS), a publicly traded software company that has nearly doubled revenue through M&A, from under $400 million to nearly $1 billion. He has closed roughly 50 acquisitions across his career at Progress, LogMeIn, and Akamai. How do you build a cost-optimization model before LOI for lines you know you can execute? How do you win a competitive process against PE without the highest headline number? When a seller restricts access during the announce-to-close window, how do you decide whether to escalate or walk? And how do you handle a workforce that expected an IPO and got an acquisition instead? Jeremy answers each one. What You'll Learn Building a pre-LOI cost optimization model on what you can actually execute How to use existing infrastructure to outbid PE on price Escalating diligence friction before it kills a deal Why a no-retrade commitment builds trust with sellers Structuring retention pools when a target's IPO falls through What target profile actually fits a disciplined buyer Why private valuations haven't caught up to public markets If you're building deal models before LOI and want a framework for translating those assumptions into an operational plan you can actually execute, DealPilot, powered by M&A Science, has Buyer-Led M&A\u2122 frameworks to help you close the gap between what you modeled and what you deliver. ____________________ This episode of M&A Science is presented by DealRoom. DealRoom just launched the only MCP server built for Buyer-Led M&A\u2122 \u2014 so your AI and your deal data finally work together. Connect Claude, ChatGPT, or Copilot directly to DealRoom and let your AI read your pipeline, analyze due diligence documents, and automatically write findings back.  See for yourself: dealroom.net\/mcp ____________________ Episode Chapters [00:00] Intro [05:07] Why M&A has to be the growth engine [07:36] Deal cadence and financial discipline [09:42] Pipeline strategy and the five-year roadmap [12:46] How the synergy model works before LOI [17:15] The no-retrade commitment [17:48] Chef: beating PE on a competitive deal [24:56] ShareFile: carve-out from Cloud Software Group [28:07] What to look for in a carve-out diligence [33:48] MarkLogic: when the seller restricts access [38:48] When seller motivation becomes an orange flag [40:09] What counts as a material change warranting a retrade [41:12] How public market cycles affect the deal pipeline [48:09] Advice for a first-time acquirer [49:46] The craziest thing in M&A [53:02] Early Warning Signs in Diligence ","author_name":"M&A Science","author_url":"http:\/\/www.mascience.com","html":"