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. What PE Gets Right That Corporate America Never Will

    2D AGO

    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
  2. 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
  3. 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
  4. Why Your PE AI Program Is Already Failing

    FEB 27

    Why Your PE AI Program Is Already Failing

    Shawn Olds spent two decades building AI companies and advising PE firms on what actually produces returns from the technology. He went from the 82nd Airborne to West Point computer science to co-founding Boodle Box, and along the way he has worked with over 200 companies on AI adoption. The number that should make every operating partner stop: over 80% of AI programs in portfolio companies fail. Not because the technology breaks. Because of decisions made before a single tool is ever deployed. Shawn and I covered why context engineering has replaced prompt engineering, why CEO backing is the one variable that separates companies getting real ROI from those just gaining productivity, and how PE firms can use data scientists during due diligence to surface hidden EBITDA before they close a deal. He also walked through real examples from the security industry that show how unstructured data already sitting inside a company can be turned into millions in annual savings without purchasing a single new tool. Chapters: 00:07 - The Role of AI in Prompt Creation02:04 - The Journey into AI Consulting11:08 - Empowering Innovation in AI Adoption24:14 - Harnessing AI in Business: Practical Applications29:39 - The Role of AI in Enhancing Business Processes37:41 - Starting with AI: Understanding the Journey Guest Information Shawn Olds is an AI strategist and co-founder of Boodle Box, a platform that brings multiple AI models into one collaborative workspace. He studied computer science at West Point and served in the U.S. Army's 82nd Airborne before spending two decades building technology companies across the United States, the Middle East, and Africa. He now advises PE firms and portfolio company CEOs on practical AI adoption that produces measurable business results. Companies Mentioned Boodle BoxMcKinseyBainBCGPwCMIT7-ElevenHire AlignedZero Prostate Cancer Foundation Websites Mentioned NotebookLMChatGPTClaudeGeminiPerplexityLinkedIn

    41 min
  5. Private Equity Is 20 Years Behind and Running Out of Time

    FEB 20

    Private Equity Is 20 Years Behind and Running Out of Time

    Lee McCabe joined me to talk about why private equity value creation keeps running into the same problem. The problem is messy systems, unclear metrics, and leaders making decisions without clean reporting. Lee shared how that shows up inside portfolio companies, and why the operating partner model often depends on influence, not authority. We also got into what it takes to fix the foundation. Lee laid out where digitization pays off fastest across consumer services and B2B, plus what breaks attribution in longer sales cycles. We closed on PE firms building real brands, the role of content, and what “media plus investing” can look like in a space that usually avoids having a point of view. Chapters: 00:00 - The Challenge of Digitizing Businesses02:38 - The Opportunity for Digital Transformation in Private Equity10:04 - The Opportunities in B2B and Consumer Services19:36 - The Changing Landscape of Private Equity28:07 - The Changing Landscape of Private Equity and Media34:29 - The Evolving Landscape of Private Equity Marketing37:30 - The Need for a New Model in Private Equity Conferences Companies MentionedeBay: Example of a highly instrumented digital environment.Expedia: Reference point from Lee’s travel background.Facebook: Example of a scaled platform where measurement is built-in.Alibaba: Example of global expansion and operating at scale.Nike: Used to frame the idea of companies built around media and narrative.Google: Example of a company that could offer real product thinking on stage.KKR: Example of a well-known large PE brand.Carlyle: Example of a well-known large PE brand.Apollo: Example of a well-known large PE brand.Blackstone: Example of a well-known large PE brand. Websites Mentionedequity.compartners.com Guest InformationLee McCabe runs Claymore Partners and advises private equity firms on digital value creation. Lee publishes the newsletter Not Very Private Equity and shares opinions publicly, with a focus on what operating partners and portfolio leaders see day to day.

    41 min
  6. Data Doesn't Win Wars—This Does

    FEB 16

    Data Doesn't Win Wars—This Does

    I sat down with Paul Evangelista, Chief Data Officer at the United States Military Academy at West Point, to talk about what happens when decisions carry real weight. Paul spent 30 years in the Army, from engineer officer to operations research analyst, and now leads data strategy where leadership is forged under pressure. We talked about why decision literacy matters more than data literacy, how mission command principles translate to private equity portfolio companies, and why trust is the foundation of high-performing organizations. Behind every value creation plan is a data problem. Paul breaks down how PE firms can build decision systems that work under stress, why fuzzy strategy is more dangerous than messy data, and what the private sector can learn from military command structures. If you care about building organizations that make better decisions faster, this conversation is for you. Chapters: 00:10 - The Importance of Real-Time Decision Making01:07 - The Role of Data in Military Decision Making16:25 - Understanding Mission Command in Military and Business28:21 - The Impact of Strategy on Business Resilience36:22 - Transitioning from Military to Private Sector Companies mentioned in this episode: United States Military AcademyMicrosoftAzureDatabricksCapital One Guest Information Paul Evangelista is the Chief Data Officer at the United States Military Academy at West Point, where he leads the Office of Data and Analytics. He spent 30 years as an Army officer, including combat deployments to Iraq and Afghanistan, and holds expertise in operations research, systems engineering, and decision science. Paul is transitioning from military service this spring to bring his experience in high-stakes decision-making to private sector leadership.

    40 min
  7. How To Stop Wasting Six Figures On Hires Who Look Perfect On Paper

    JAN 22

    How To Stop Wasting Six Figures On Hires Who Look Perfect On Paper

    I've spent 20 years watching brilliant people build companies on gut instinct and prayer when it comes to hiring. After losing a million dollars on a single bad hire who tanked an entire engineering team for six months, I wanted to understand if there was actually a way to measure the thing everyone claims is unmeasurable: culture fit. Jacob Crockett built Higher Aligned after nearly getting fired at one company for the exact same behaviors that made him a star at the next. That personal disaster led him to ask a question most people assume is impossible: can you actually quantify whether someone will thrive in your environment before they walk through the door? We talked about what happens when you stop guessing and start measuring the human side of business decisions. Jacob walked me through how his AI platform scores alignment before the hire, the invisible costs that never show up on any P&L, and why the recruitment industry has devolved into an automated mess where both sides are gaming broken systems. If you've ever hired someone who looked perfect and crashed spectacularly, this conversation will explain exactly why that happened and what you can do differently. Chapters: 00:09 - Navigating Workplace Challenges01:34 - Understanding Culture in Organizations: A Data Perspective21:21 - Understanding Workplace Culture and Individual Fit28:06 - The Impact of Culture on Business Success45:12 - The Evolution of Work: From Loyalty to Portfolio Careers Companies Mentioned Higher Aligned UnitedHealth Group LinkedIn Tesla Indeed Websites Mentioned aligned.com Guest Information Jacob Crockett is the founder of Higher Aligned, a company that uses AI to measure cultural alignment and team fit in hiring. He has a background in data science and has worked at UnitedHealth Group and several other organizations before starting Higher Aligned.

    51 min
  8. Why Your AI Projects Fail (You Can't Fire AI)

    12/05/2025

    Why Your AI Projects Fail (You Can't Fire AI)

    I sat down with Scott Golder, Senior Director of Data Science at Home Depot, to talk about what actually works when you're building data teams. Scott has spent 20+ years fixing what others couldn't, from Capital One to running algorithms behind one of the top five e-commerce platforms in the world. He breaks down why deeper academic backgrounds don't always make better data scientists, how to make AI trustworthy at scale, and what happens when you fall in love with your methodology instead of the problem you're supposed to solve. This conversation gets into the messy reality of deploying machine learning in the real world. Scott shares how Home Depot uses recommendations differently than selling sweatpants, why human accountability can't be replaced by 10,000 AI coworkers, and which AI tools he actually uses when his kids go to bed. If you're building data products or trying to figure out where AI fits in your business, this one's for you. Chapters: 00:00 - The Importance of Seasonality01:43 - Connecting Data Science with Real-World Challenges10:17 - Understanding Customer Empathy in Product Design16:15 - Transitioning to AI and Machine Learning21:41 - Navigating Accountability in AI Decision-Making25:00 - AI in Everyday Life: Personal Experiences and Insights33:10 - The Future of Software Engineering and AI38:14 - The Importance of Data Governance in AI Companies Mentioned Home Depot Capital One IBM Google Duolingo Guest Information Scott Golder is Senior Director of Data Science at Home Depot, where his team powers the algorithms behind one of the world's top five e-commerce platforms. He previously helped scale data science at Capital One and has a background in sociology, linguistics, and computer science. Scott specializes in building data teams that blend academic depth with real-world implementation in hostile corporate environments. Key Takeaways Academic credentials don't predict data scientist performance. Fall in love with the problem, not your methodology. AI works best for summarization when you fence the data. Human accountability can't be replaced by software. Speed and cost of AI models dictate where they're feasible. Your data foundation must be solid before AI can help.

    40 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
    30
  • Rating
    Clean
  • Copyright
    © Copyright 2026 Graeme Crawford
  • Show Website
    Private Equity Data Guy