Value Creation Blueprint: Building the Data Flywheel

1. Infrastructure: Build the Refinery

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The Challenge

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Most PE-backed firms are sitting on fragmented data. Systems don’t talk to each other. Reporting is manual. Time is wasted stitching spreadsheets while decisions lag.

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The Opportunity

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Unifying infrastructure gives you control, speed, and a foundation for every other layer.

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It’s not about building a "data lake" for its own sake. It’s about creating platforms that help teams ask and answer better commercial questions, faster.

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Key Moves

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• Move from departmental silos to shared cloud platforms (e.g. AWS, Databricks, Snowflake)
  
  
• Standardise data models across the org so that ops, sales, and finance speak the same language
  
  
• Build APIs and access layers early to avoid rework down the line
  
  

Case Story

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One manufacturing PortCo had five ERPs across six markets. It took three weeks to reconcile inventory data. After moving to a central cloud data lake and aligning the model, weekly dashboards were automated, saving 50% of analyst time and reducing stockouts by 18%.

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“Before, we had data. Now we have answers.” – CFO, PortCo

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Stats That Matter

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• 80% of execs say data silos hurt transformation. Accenture
  
  

• Unified data platforms reduce time-to-market by 55%. McKinsey

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2. Insight: Catalyse Action with AI and Analytics

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The Challenge

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Data warehouses alone don’t change performance. Insight needs to be relevant, timely, and embedded in decisions. Too many dashboards are built after the fact and nobody uses them.

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The Opportunity

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Modern AI and ML tools help you move from lagging reports to leading indicators such as predicting churn, forecasting pricing elasticity, or personalising outreach.

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But AI isn’t magic. It’s a multiplier for what you already understand. Junk in, junk out.

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Key Moves

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• Build use-case-led models, not vanity projects
  
  
• Focus on frontline value: will this model help someone do something better?
  
  
• Invest in “reverse ETL” and push predictions into CRM, ERP, or workflow tools
  
  

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Stats That Matter

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• AI adopters see 30% more efficiency and 90% improved decision-making. MIT Sloan / BCG
  
  

• Only 10% of firms say their analytics are truly embedded into operations. McKinsey Global Survey

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“The goal isn't insight. It's better decisions.”

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3. Governance: Control Without Paralysis

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The Challenge

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Many PE leaders worry about compliance, risk, and data quality and rightly so. GDPR, HIPAA, and other regulatory regimes create real liability. Poor governance leads to distrust, fines, and failed initiatives.

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Yet many firms respond by locking everything down, or worse, building nothing at all.

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The Opportunity

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The best-performing companies don’t choose between speed and control. They bake governance into the foundation, treating it as a strategic enabler, not a blocker.

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Key Moves

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• Automate data quality checks, don’t rely on manual review
  
  
• Build audit trails and access logs as standard
  
  
• Create policies that scale across PortCos but remain flexible to individual business needs
  
  
• Stand up lightweight Data Steward roles in business functions, not just IT
  
  

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Stats That Matter

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• Poor data quality costs companies $3.1T globally each year. IBM
  
  
• Firms with strong data governance are 2.5x more likely to outperform peers. Harvard Business Review
  
  

“Good governance isn't red tape—it's what makes trust and scale possible.”

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4. Culture: Distribute the Fuel

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The Challenge

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Even with clean data and good models, many firms stall at the last mile. Insights don’t reach the people making decisions. Dashboards sit untouched. Teams revert to gut feel.

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The Opportunity

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Build a data culture. Not by training everyone to code in Python, but by creating habits, rituals, and workflows that use data every day.

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Key Moves

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• Integrate metrics into weekly business meetings and not just monthly reviews
  
  
• Assign data ownership in ops, not just IT
  
  
• Build feedback loops: does this report actually help someone do their job?
  
  
• Treat “data as a product” and consider packaging insights for partners, regulators, or even monetisation
  
  

“We stopped asking what reports to build. We asked what decisions we needed to make.”

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Stats That Matter

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• Only 26.5% of companies say they have a data-driven culture. NewVantage Partners

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• Firms with strong data cultures are 3x more likely to execute on digital strategy. McKinsey

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The Flywheel: Compounding Returns

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The real magic isn’t in any one layer, it’s in the compounding effect.

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• Infrastructure makes insight possible
  
  
• Insight drives action
  
  
• Action builds culture
  
  
• Culture improves data
  
  
• Better data strengthens infrastructure

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Like Rockefeller reinvesting pipeline savings into refining capacity, every round of the flywheel accelerates the next.

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This is how value creation scales.

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“If you don’t build your own flywheel, you’ll end up fuelling someone else’s.”

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Final Word: From Resource to Platform

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Drake found oil. Rockefeller built the system.

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Today, most PortCos have data but not many have systems that turn it into growth.

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The winners won’t be the ones who collect the most data. They’ll be the ones who refine it best, distribute it fastest, and act on it daily.

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So, the question for your next board meeting:

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Are we building another well or a refinery?

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