Private Equity Data Guy

Graeme Crawford
  • 5.0 (3)
  • BUSINESS

Private equity meets data. Conversations with deal teams, operating partners, and portfolio company leaders about the data problems that kill deals, slow exits, and destroy value. Hosted by Graeme Crawford, founder of Crawford McMillan. 20 years leading data programs at Fortune 100 companies. Now helping PE-backed companies fix data before exits so the numbers hold up under scrutiny. New episodes cover diligence red flags, value creation playbooks, and the real stories behind successful (and failed) transactions.

  1. APR 30

    Why PE Firms Are Asking the Wrong Question About AI

    Elon Salfati joined me this week to break down what most PE-backed companies are getting wrong about AI. Not the surface-level stuff, not the board slide version. The real operational gap between clicking a button and actually changing how a business runs. Elon advises PE firms, enterprise operators, and has consulted the UK House of Lords on AI policy alongside leaders from Microsoft and Palantir. His firm, Safari Group, works with businesses to replace manual, people-dependent processes with governed AI systems that scale without adding headcount. What stood out most in this conversation was the idea of decision sovereignty. When a company hands all its strategic thinking to an LLM, it loses its competitive edge. An LLM echoes the past. It will not discover gravity if an apple falls on its server. The real opportunity is flipping the model so the company reaches out to the human for creative judgment, not the other way around. Elon walked through a real case study with Key Loop where they reduced churn by rethinking the entire process workflow before touching the technology. [00:06:43] Wrong question vs right question [00:08:42] Point solutions on broken processes [00:10:39] Political resistance to change [00:16:08] Why AI initiatives stall [00:29:09] Decision sovereignty explained [00:36:09] Human with an army of agents [00:41:19] Turning service companies into software [00:47:01] Personal AI at work and home Guest Information Elon Salfati is the founder of Safari Group, a Zurich-based AI consultancy. His background spans cybersecurity, scalable systems, and applied AI research. He is currently completing his PhD at Imperial College London focused on building secure AI systems and organizational AI culture. Companies Mentioned Safari Group Key Loop IBM Capital One PepsiCo Blackrock NewsCorp Palantir Microsoft Anthropic Websites Mentioned https://www.safari-group.ai Takeaways AI without process redesign adds chaos, not speed. The companies winning are the ones asking what the operating model looks like when AI runs the operational layer, not just what AI tool to add. Decision sovereignty keeps your competitive edge intact. The shift worth building toward is an army of agents that surfaces decisions to the human, not humans triggering every automation manually.

    51 min
  2. This Is How He Turned Agency Ownership Into a Video Game

    APR 23

    This Is How He Turned Agency Ownership Into a Video Game

    Peter Kang built Barrel into a cash-flowing agency over fifteen years before he ever touched a deal. That patient foundation is what separates Barrel Holdings from a traditional PE firm. No fund, no management fees, no forced exit timeline. Just cash flows reinvested into acquiring good businesses at fair prices, with SBA financing doing the heavy lifting until the flywheel grows strong enough to need less leverage. We talk through what Peter looks for beyond the obvious numbers, including client retention, average tenure, concentration risk, and whether there is real leadership depth below the founder. We get into the Bolster story, the design agency he incubated, loved, and had to walk away from when he realized he was the only reason it had any business at all. And we get into how AI is changing what agencies can deliver, what clients are willing to pay, and how the hourly model is holding on by a thread in a world that rewards output over time. TIMESTAMPS [0:00] Peter Kang and Barrel Holdings [2:02] Holdco Tycoon game origin [5:18] Holdco structure vs PE fund [8:31] Price, leverage, sourcing lessons [16:18] AI reshaping agency work [21:05] What data matters in acquisitions [23:01] Culture risk and Bolster story [30:26] Documenting failures publicly KEY TAKEAWAYS Buying discipline matters more than deal flow. Overpaying is one of the fastest ways to get into trouble, and time pressure only makes it worse. Client retention and average tenure tell you more about an agency than revenue growth. Concentration risk is a red flag worth walking away from. Culture is not a feeling. It is the standards a leadership team enforces and models every day. When those standards clash post-acquisition, good people leave. Publishing failures is a sourcing strategy. Trust is built through transparency, and founders looking to exit remember who showed up honestly. AI is not replacing agencies. It is raising the standard for speed and output, and the pricing models that survive will be the ones tied to value, not hours. COMPANIES MENTIONED Barrel Barrel Holdings Agency Habits Bolster WEBSITES MENTIONED peterkang.com barrel-holdings.com https://www.linkedin.com/in/peterkang34/ GUEST INFORMATION Peter Kang co-founded Barrel in 2006 and spent two decades building it into the foundation for Barrel Holdings, a portfolio of digital agencies across e-commerce, Amazon, B2B marketing, and home services. He published The Holdco Guide and created the Holdco Tycoon game to share the capital allocation lessons he learned the hard way. Peter writes openly about wins and failures and runs Barrel Holdings with a decentralized, operator-led model.

    48 min

  3. APR 17

    What PE Buyers Find When They Actually Look at Your Data

    In this episode, I sat down with Derek Sather, CRO at KKR-backed Education Perfect, to talk about what actually happens when someone with deep systems thinking and revenue architecture experience steps inside a PE portfolio company. Derek breaks down what it means to move from managing a pipeline to underwriting revenue, and why that shift matters more now than ever before. We get into the real cost of messy data during diligence, what buyers are actually looking for when they dig into your revenue numbers, and why AI will amplify your chaos just as fast as it amplifies your clarity. If you are building toward an exit or trying to make your revenue engine defensible, this one is worth your full attention. [00:01:42] - Derek's background and career path [00:06:16] - What the data looked like going in [00:13:31] - Revenue numbers and diligence breakdowns [00:17:19] - Building credibility one metric at a time [00:22:23] - Demand architecture and the new CRO role [00:29:44] - What buyers look for before an exit [00:34:22] - Retention vs acquisition and compounding growth [00:39:38] - AI, clean data, and the new PE playbook Guest Information Derek Sather is an MIT-educated systems thinker and current CRO at Education Perfect, a KKR-backed edtech platform based in Sydney, Australia. He spent six years at Winning by Design helping over 600 software companies engineer predictable revenue. Find him on LinkedIn. Companies Mentioned Education Perfect KKR Winning by Design Capital One IBM Uber Websites Mentioned https://www.linkedin.com/in/dereksather Key Takeaways One metric, one owner, one logic chain. That is how credibility gets built. A messy revenue engine does not get fixed by AI. It gets scaled into more confusion. Revenue quality is the asset. Not just revenue growth.

    44 min
  4. Is your Data telling you the right story?

    APR 9

    Is your Data telling you the right story?

    Holli Moeini spent 35 years as a CFO scaling companies through acquisitions before leaving corporate to help founders protect their value when going up against PE buyers. Her book, Find the Missing Millions in M&A, breaks down the five moments in every deal where money moves toward you or away from you. In this episode, she maps out each one and explains what sellers can do before they ever get to the table. The conversation gets into the financial story, working capital, diligence, earn outs, and integration. Each one is a place where the unprepared seller loses. The ones who walk away with the most are the ones who treat their data and accounting as front office functions, not back office overhead. [00:00| You cannot go it alone [04:55| Five crime scenes in every deal [07:15| Cleaner data, better multiple [11:41| Working capital costs millions [20:57| Earn out clarity control cadence [25:29| Integration starts before close [29:02| Data as a front office function [41:49| Run it like you will sell Guest Information Holli Moeini is a CPA and M&A advisor with over 35 years in finance. She spent her career as a CFO scaling companies from $30M to $200M through acquisitions. She now works with founders and sellers preparing for PE transactions. Companies Mentioned IBM Capital One Barnes and Noble Amazon Websites Mentioned https://hollimoeini.com/

    48 min

  5. APR 2

    Private Equity Is a Talent Business, Not a Finance Business

    Tim Schulte leads value creation at Council Capital, a healthcare-focused PE firm in Nashville. He spent years at Vista Equity Partners before building something different at Counsel. In this conversation, we get into why the playbook model breaks down across a diverse portfolio, what a toolkit approach actually looks like in practice, and what AI is doing to the work of value creation right now. We get specific on data infrastructure, change management, and why the people question determines whether any of this works. Tim's view on AI is one I share: the tools are getting better fast, the value still sits in implementation and adoption. We cover the state of PE returns, what the industry has to do to justify its position going forward, and how Council Capital is building real operational capability at the lower middle market level. [00:01:53] Tim's path into private equity [00:06:01] What Vista Equity got right [00:10:08] Toolkits vs playbooks explained [00:14:06] Data infrastructure across diverse portfolios [00:19:44] AI and the toolkit build process [00:26:14] Recommending AI across portfolio companies [00:32:47] PE history and what comes next [00:39:37] Where the industry is heading Key Takeaways The playbook model breaks down when portfolio companies are diverse. Toolkits that operators choose to use work better than mandated processes. Data strategy has to serve the operating team first. If the PE firm pulls data that operators don't use, the problem is alignment, not data. AI saves time on framework creation. The value is still in getting people to change how they work. Companies Mentioned Council CapitalVista Equity PartnersRampAnthropicOpenAIBrookdale Senior LivingCignaKrogerUniversity of Chicago Websites Mentioned https://councilcapital.com/ Guest Information Please provide details about the guest who will be featured in the episode. Guest's Full Name Tim Schulte Company / Organization Council Capital Website or Main Page Empty Guest Social Media Links https://councilcapital.com/

    41 min
  6. What PE Gets Right That Corporate America Never Will

    MAR 26

    What PE Gets Right That Corporate America Never Will

    Ryan Krook has spent his career at the intersection of data and operations, working inside companies like Uber, Shopify, and McKinsey before founding Pareto Apps. In this episode, we get into what it actually looks like to walk into a mid-market PE portfolio company that has never taken data seriously, and what to do about it. Ryan brings a perspective I don't hear often: he has sat on the LP side, worked as an outside consultant, and now operates hands-on inside the companies fixing the problems that matter most at exit. What stood out to me most was Ryan's take on starting small. Not small as in unambitious, but small as in disciplined. Get one reliable metric. Build from there. That approach, rooted in the Pareto principle, is how you create real operational leverage without pulling people away from the work that actually drives the business. We also got into the risks that come with vibe-coded apps, AI without data governance, and the version control nightmare that happens when everyone builds their own tool. Timestamps [00:02:09] - Ryan's path into data [00:07:49] - Working inside PE at McKinsey [00:15:53] - Mid-market companies and data gaps [00:21:52] - Data governance and why it matters [00:25:09] - Where to start with data investment [00:30:51] - Iterative builds and fast delivery [00:38:00] - Vibe coding risks in enterprise [00:42:04] - AI capabilities, a 1 to 10 take Guest Information Ryan Krook is the founder of Pareto Apps, a firm that builds bespoke data and AI solutions for PE-backed portfolio companies and early-stage startups. He previously held roles at Ontario Teachers' Pension Plan, McKinsey, Uber, and Shopify. Ryan is based in Canada and focuses on getting companies to a place where their data is reliable enough to actually use. Companies Mentioned Pareto AppsOntario Teachers' Pension PlanMcKinseyUberShopifyBowellSnowflakeBolt Websites Mentioned paretoaps.coLinkedIn Key Takeaways Start with one reliable metric before building anything largerData governance is what makes AI outputs trustworthyPE-backed companies move faster because everyone is aligned around the same exit timelineVibe-coded apps carry the same version control risks as unmanaged spreadsheetsThe barrier to standing up solid data infrastructure has dropped significantly in the last few years

    52 min
  7. How this company lost $2.8M due to three mismatched numbers

    MAR 12

    How this company lost $2.8M due to three mismatched numbers

    Greg Hood has spent over 20 years as a finance executive inside Canadian and US fintechs and financial services firms. He built Sky Site Analytics to help PE firms, sell-side M&A advisors, and high-growth companies fix the data layer before buyers find it first. We cover the dirty data discount, what actually breaks during exit, and why the back office is always the last to get the budget it needs. If you have ever sat across from a buy-side team watching trust drain out of a room because three reports show three different revenue numbers, this conversation is for you. Greg and I have worked in the same trenches long enough to know that the data problem is almost never a technology problem. It is a process problem wearing a technology disguise. TimestampsChapters: 00:04 - Challenges in Product Management03:37 - The Evolution of Data in Finance09:12 - The Importance of Data Quality in Finance23:16 - The Importance of Accurate Financial Data Reporting29:23 - The Impact of AI on Business Practices36:33 - The Value of Data in Business43:49 - The Valuation of Data as an Intangible Asset GuestGreg Hood is a CPA and CMA who held one of the first Chief Data Officer roles earned by a CPA. He founded Sky Site Analytics, a Toronto-based consultancy that works with PE firms and high-growth companies on finance data infrastructure and exit readiness. His team won Most Innovative Finance Department while at Q Trade, an online brokerage, where they cut a two-and-a-half-day close process down to under two hours. Companies MentionedSky Site AnalyticsQ TradeKunaiParamount CommerceCampfire (AI-first ERP)QuickBooksNetSuiteSnowflakeDatabricksAnthropic (Claude) Websites MentionedSky Site AnalyticsGreg Hood on LinkedIn Key TakeawaysInconsistent revenue numbers across reports can cost millions in exit valuation, not because the business is bad but because trust is gone.The data layer is routinely skipped during due diligence, and that gap is getting more expensive as data rooms grow from 30 documents to over 300.First-party data can be a monetizable asset, but quality and uniqueness determine value. If your data looks like everyone else's, it is not worth what you think.

    49 min
  8. The Data Problem That Kills PE Exit Multiples

    MAR 6

    The Data Problem That Kills PE Exit Multiples

    Shota Ishii joined me on The PE Data Guy to talk about what happens when PE-backed manufacturers cannot answer a basic question: which products are actually making money? He has spent two decades building systems that give companies a clear picture of where their cash goes, and we got into why that gap exists and what it takes to close it. We covered working capital, data architecture, and what mid-market companies need to do right now to get their data in order before AI can do anything useful for them. Shota shared an example of a $400 million metal company that found $80 million in working capital improvements once they had the right transaction-level visibility. Chapters: 00:00 - Understanding Capital Efficiency06:42 - The Journey to Becoming a Robo CFO20:55 - Amazonifying Legacy Industries: The Need for Real-Time Data31:51 - The Importance of Data Strategy in Mid-Market Companies35:18 - The Future of AI in Mid-Market Companies Guest InformationShota Ishii is the founder of Proximo Tech, where he works with PE-backed manufacturers on capital efficiency and working capital. He studied applied physics and AI and has a background in quantitative finance, hedge funds, and corporate innovation. He is based in Japan and can be found on LinkedIn. Companies MentionedProximo TechMoody'sBlackstone CreditAmazonSnowflakeDatabricksAWSGoogle CloudSalesforceOpenAI Websites MentionedProximo TechLinkedInSnowflakeDatabricksAWSGoogle Cloud Key TakeawaysClean, granular data at the transaction level is the foundation for improving working capital.The cost of not building a data platform grows over time as competitors who do build one move faster.Data is a company asset. Without structure and governance around it, AI cannot make use of it.Mid-market companies often underestimate how affordable modern data tools actually are.

    45 min
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About

Private equity meets data. Conversations with deal teams, operating partners, and portfolio company leaders about the data problems that kill deals, slow exits, and destroy value. Hosted by Graeme Crawford, founder of Crawford McMillan. 20 years leading data programs at Fortune 100 companies. Now helping PE-backed companies fix data before exits so the numbers hold up under scrutiny. New episodes cover diligence red flags, value creation playbooks, and the real stories behind successful (and failed) transactions.

Information

  • Creator
    Graeme Crawford
  • Years Active
    2025 - 2026
  • Episodes
    35
  • Rating
    Clean
  • Copyright
    © Copyright 2026 Graeme Crawford
  • Show Website
    Private Equity Data Guy