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Today’s Rundown

• Building a career through the search fund model

• Mathematical analysis of value-creation attribution in search funds

• Search fund pre-LOI investment analysis

• 3 deal / launch announcements

Weekly Highlights

• auilium shared a new podcast episode with Henrik Buehler on building a career through the search fund model:

  • Emotions drive M&A outcomes more than most buyers admit: ~50% of B2B buying decisions and ~95% of consumer decisions as emotion-driven, and argues the same dynamics apply in succession deals - often making continuity/culture decisive even when price is competitive

  • Europe search funds are scaling fast, with measurable momentum: ~1,000 search funds raised globally, with ~650 in North America and ~350 outside, and “most” of the non-NA activity in Europe

  • Germany is still early but building infrastructure: the discussion estimates ~20–30 active searchers/duos (mostly traditional model; self-funded harder to track) and notes ~50 chambers of commerce each now having a succession-focused person, reflecting how central succession has become

  • Deal size expectations are drifting upward due to capital supply: typical targets are ~€1–4m EBITDA, but an example is given of a German searcher acquiring ~€8–10m EBITDA using a large syndicate - linked to broader “dry powder” pressure

  • Target “quality” is defined with guardrails that reduce early-operator risk: prioritizing recurring/repeat B2B revenue, EBITDA margins ideally ≥15%, and room for mistakes + reinvestment; SaaS is potentially attractive on revenue quality but often challenging on entry valuation and multiple arbitrage

  • Search execution is run like a sales funnel with cadence math: top-down thesis → database filtering → ~200-target lists → outreach via email/letters with 4 follow-ups over ~1 month (about every 7 days) because response rates rise with follow-ups

  • Co-founder risk is explicitly managed with process: ~65% of ventures fail due to co-founder conflict, and outlines mitigants: shared values/vision, clear role division, “hard feedback” culture, and a disagreement framework (surface perspectives → active listen → evaluate neutrally → seek consensus → post-mortem learning)

  • Key seller insight: many founders (especially €1–4m EBITDA) are first-time sellers; “process” can be disruptive and leak rumors; searchers win by offering stewardship (employees, culture, local reputation) and by plugging into the seller’s first advisor - often the tax advisor - before an auction process starts

• Yale, in partnership with search fund Skyline Crest Partners, published a mathematical analysis of value-creation attribution in search fund projects:

  • Across 59 exited search fund investments representing roughly 35% of known exits, about 80% of enterprise value creation came from EBITDA multiple expansion while only 20% came from EBITDA dollar growth

  • EBITDA grew by roughly 60% on average, driven by revenue growth of more than 100 percent, but this was partially offset by EBITDA margins falling from about 25% at entry to 19% at exit

  • Nearly 90% of companies experienced EBITDA multiple expansion and more than half at least doubled their exit multiple, while only about 30% achieved any EBITDA margin expansion

  • Statistical analysis shows EBITDA multiple expansion is positively associated with revenue growth and firm size but negatively associated with margin expansion, suggesting that reinvestment and margin compression often correlate with higher exit valuations

  • The findings imply that search fund returns rely heavily on market timing, buyer demand, and exit process quality, making terminal multiple risk a dominant driver of IRR rather than operational margin improvement

• Fontics launched a search fund pre-LOI investment analysis:

  • A structured Pre-LOI quantitative review that normally takes 5–10 hours can be compressed to under 60 minutes by standardizing the LBO build and automating scenario, sensitivity, and driver analysis, effectively cutting build and analysis time by about 90%

  • A disciplined one-hour workflow allocates roughly 30 minutes to extracting teaser inputs, 10 minutes to updating a pre-built LBO, and the remaining 20 minutes to identifying key value drivers, running scenarios, stress-testing structures, and reaching a go or no-go decision

  • Empirical experience from QoE providers suggests more than 90% of QoE reports adjust EBITDA downward, implying Pre-LOI EBITDA should be treated as an optimistic ceiling and reinforcing the need for fast downside-focused screening

  • In most deals, a small set of variables drives outcomes, with roughly 3–5 inputs explaining over 90% of MOIC or IRR movement, allowing searchers to focus scenario analysis and negotiations on a narrow set of high-impact levers

  • Small simultaneous changes across core drivers can materially shift returns, with examples showing that moving IRR from roughly 26% to 30% may require less than a 5% combined adjustment across revenue growth, leverage, margins, or structure rather than heroic single-variable assumptions

Deal / Launch Announcements

• 🇪🇸 Ignacio Jimenez de Laiglesia and Gonzalo Tomé Aróstegui launched Virrey Capital, a sector-agnostic search fund (link)

• 🇪🇸 Javier Sánchez Cordero and Aitor Grandes Gajate launched Scrum Capital, a sector-agnostic search fund (link)

• 🇩🇪 Frank Forster launched AQUEDUCT, a search fund and SME investor (link)

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