How a Modern Data Platform Supports Buy-and-Build in Private Equity
Understanding PE Buy-and-Build Success Factors
Reliable buy-and-build strategies in private equity require focused, intentional plans built around multiple acquisitions of smaller, often underperforming, companies. While many factors determine success over the course of the buy-and-build cycle, the potential to realize multiple arbitrage begins with the underlying strength of the platform company and the leverage this gives general partners when pursuing lower-multiple deals. If the platform company has systems that support efficient integration, GPs can more confidently acquire underperforming targets at reduced multiples, securing a key component of the arbitrage strategy.
With efficient integration, the performance of acquired bolt-ons can rise more quickly to the level of the platform company. Inefficient integration not only prolongs underperformance and suppresses bolt-on valuations, but can also drag down the performance and value of the platform company itself.
The Value and Role of Data in Private Equity
One of the most critical and perennially frustrating elements of integration is data, specifically the ability to clearly assess performance in aggregate and in comparison across business units. Cobbling together reports from disparate systems, or waiting for full software integrations, increases risk when acquiring underperforming assets.
Flying blind leads to reactive decisions, unintended consequences, and management turnover. Strong private equity data intelligence allows bolt-ons to operate effectively from day one, without disruption. Boston Consulting Group has noted that companies failing to use data to create value risk losing competitive advantage or hastening their own obsolescence, a warning that applies directly to PE firms executing integration-dependent strategies.
Integrating data from acquisitions may feel overwhelming, but it does not have to be. As outlined in prior data intelligence insights, investors need near real-time access to portfolio-wide performance data to identify and overcome barriers to growth. The CoolSys case study illustrates this directly: by building a unified data layer across 18 acquired companies before full system integration was complete, the business achieved a 4 to 5% improvement in operating margins and a 52% reduction in employee turnover.
The Modern Data Platform
Microsoft Fabric brings together familiar tools including lakehouses, data lakes, and Power BI to store, model, and report on data from a single platform. Now generally available, Fabric has become the practical foundation for PE-backed companies looking to unify portfolio data without waiting for full system consolidation across acquired entities.
This approach supports efficient bolt-on integration by providing private equity firms with data sources that can be incorporated quickly with minimal disruption to existing processes. To understand how mid-market companies are accelerating that integration, this overview of fast-tracking data integration with data lakes covers the mechanics in detail. The flexible platform adapts as reporting requirements evolve across the hold period, delivers near-term ROI through agile implementation that surfaces actionable insights early, and provides a strong foundation for generative AI and natural language querying as those capabilities become operational priorities.
PE Buy-and-Build Success Factors: Takeaway
A modern data platform gives general partners a meaningful advantage in competitive markets. By enabling strong platform companies to efficiently integrate underperforming bolt-ons, firms can pursue lower-multiple acquisitions and lay the groundwork for successful arbitrage. The data foundation that supports this does not require waiting for full system integration across every acquired entity. It requires building at the data layer first, which is precisely what makes it possible to move quickly after each acquisition closes.
Blue Margin can handle the heavy lifting of consolidating portfolio data into a centralized data lake, or partner with your team as a fractional data team to turn that data into value-driving insights. Contact us to get started.
