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Good Enough for Now: The Data Maturity Trap Every PE Portfolio Company Faces
January 27, 2026
The Mid-Market 2026 Playbook
This is Part 1 of our three-part series on transforming your mid-market PE-backed business for 2026. In this piece, we explore the data foundation that makes everything else possible. Parts 2 & 3: Coming SoonGood Enough for Now: The Data Maturity Trap Every PE Portfolio Company Faces
Private equity portfolio companies face a fundamental tension between speed and sustainability. On one side, there’s pressure to demonstrate rapid operational improvements and revenue growth. On the other, there’s the reality that most mid-market acquisitions come with fragmented data systems—QuickBooks instances, Excel-based processes, and disparate ERPs that were never designed to support investor-level visibility expectations.The question isn’t whether to invest in data infrastructure. The question is when, and how much is enough at each stage of the growth journey. Companies that get this timing wrong either bog down their acquisition velocity with premature standardization, or find themselves unable to answer basic questions about company performance to their investors when it matters most.
The Case for Staged Data Maturity
In the early stages of a roll-up strategy—particularly when acquiring companies every few months—perfect data integration is neither achievable nor necessary. What matters at that point is establishing baseline visibility across a limited set of high-impact metrics: cash flow, customer retention, and working capital efficiency.This often means implementing a scalable cloud ERP platform that can serve as the foundation for the entire portfolio. Platforms like NetSuite provide the flexibility to consolidate financial data across multiple entities while maintaining the agility needed during rapid acquisition periods. The goal is establishing common chart of accounts structures and investor-level reporting that aggregates performance across all entities – creating the visibility needed to drive investment decisions without slowing acquisition velocity.
This approach does create some technical debt as you prioritize speed, and at that point in your trajectory, that’s an acceptable trade-off. The alternative – pausing acquisitions to perfect data architecture – creates a different kind of debt you likely don’t want: lost market opportunities and delayed revenue synergies.
The Complexity of Enterprise Data
Enterprise data has evolved into a complex, fast‑moving ecosystem, and that complexity is now hitting mid‑market operators just as hard as the Fortune 500. For CEOs and CFOs leading PE‑backed companies, the challenge isn’t just managing more data—it’s turning fragmented systems and inconsistent reporting into the kind of clarity that accelerates value creation. In a world where every quarter counts, the ability to harness data effectively has become a strategic lever for growth, operational discipline, and investor confidence.To look at this challenge in a specific context, let’s consider the challenge of customer master data. A single customer record may be touched by sales (initial entry), marketing (segmentation and campaign attribution), operations (service delivery details), IT (system integration and format standardization), and finance (billing and revenue recognition). Each touchpoint introduces the potential for inconsistency: divergent naming conventions, duplicate records, incomplete fields, or misaligned customer hierarchies.
When you scale this across eight acquired entities over 24 months, each with different CRM platforms, customer data models, and business processes, the result is predictable: leadership cannot definitively answer questions about customer concentration, segment profitability, or retention trends across the entire base.
This is the inflection point where “good enough” data infrastructure becomes a strategic liability rather than a pragmatic trade-off.
Recognizing the Inflection Point
The pattern that takes place is remarkably consistent across most mid-market companies. Year one is characterized by speed: acquisitions close rapidly, basic reporting mechanisms are established, and the focus is on integrating operations and capturing immediate synergies. This is rational behavior given capital deployment timelines and the need to demonstrate momentum.Moving on, year two typically involves continued acquisition activity with the assumption that data consolidation can be deferred. “We’ll address this after we complete the next few transactions” becomes the operating assumption. This is where strategic risk starts to accumulate.
By year three, the organization faces a materially different set of challenges. The company includes ten or more acquired groups still often running disparate systems. This begins to lead to things like monthly close cycles extending beyond 20 days due to manual consolidation requirements, or performance metrics being defined inconsistently across the group, making meaningful comparison difficult. Most critically, as the organization begins to approach the potential exit period, the lack of clean, integrated data becomes a valuation issue. Buyers expect—and underwrite more favorably for—companies that can demonstrate clear visibility into performance drivers, customer economics, and operational efficiency.
Building Infrastructure in Parallel with Growth
Leading mid-market leaders must integrate data strategy into their M&A approach from the initial acquisition point. This doesn’t mean perfect systems from day one – it means establishing a clear roadmap with defined decision points and milestones.The optimal approach follows a three-phase evolution: In phase one, you want to establish foundational standards while maintaining acquisition velocity. Aim to define the five to seven metrics that matter most for the investment thesis, require minimum data standards from each acquired entity, and then begin researching the target technology platform that will serve as the consolidation point for the joint company.
Phase two begins to focus on systematic migration. First priority will be to actually select the cloud-native ERP platform that will serve as your consolidation point—NetSuite and Sage Intacct are particularly well-suited for mid-market companies growing through acquisition due to their multi-entity capabilities and scalability. You should define and document what “good” looks like for data across the joint company. Then focus on migrating all the acquired companies into the platform, starting with those that have the least technical debt. The focus in this phase is on building repeatable integration processes that can be applied to future acquisitions.
By phase three, the organization should begin operating with the newly defined discipline: new acquisitions move to the standard platform within 90 days. Older acquisitions should also be migrated based on strategic priority and complexity. The emerging pattern should become consistent – those companies that establish this roadmap by acquisition three or four achieve materially better outcomes than those that defer consolidation until they’ve assembled ten or more disparate entities.
The Mid-Market Advantage
Mid-market companies have a structural advantage that’s often underappreciated. While enterprise organizations spend 18 to 24 months and significant capital migrating legacy on-premise infrastructure to cloud platforms, mid-market companies have more agility and can implement cloud-native solutions from the outset.This advantage is particularly pronounced in roll-up strategies. A deliberate platform selection by acquisition three or four, followed by systematic migration of existing entities and rapid onboarding of new acquisitions, creates both operational efficiency and strategic optionality. The alternative – allowing the new joint company to continue fragmented across multiple systems – makes the eventual consolidation exponentially more complex and expensive.
Practical Implementation
The roadmap for growing companies is straightforward in concept, though demanding in execution. Here are some key points to consider when looking at practical implementation of this approach:- Begin with a current-state assessment: document the systems landscape across the acquired groups, the data being tracked, and the gaps that constrain decision-making. This creates your baseline for prioritization.
- Define the few critical key metrics: choose five to seven that directly support the investment thesis and operational strategy. Ensure every entity can report these metrics consistently. This is not about comprehensive dashboards; it’s about answering the questions that matter for company management and value creation.
- Select the right cloud-based platform: Make your decision based on scalability, implementation speed, and total cost of ownership. For fast growing mid-market companies, platforms like NetSuite offer particular advantages: multi-entity consolidation, real-time reporting across all entities, and the ability to onboard new acquisitions rapidly. Focus on developing a standard 90-day integration playbook for newly acquired companies. This playbook should address data migration, process standardization, and user enablement.
- Recognize where partnership makes strategic sense: Building data warehouse expertise and platform implementation capabilities internally is rarely the highest-value use of management bandwidth. Partnering with specialists who have navigated similar transformations – particularly those with deep expertise in multi-entity ERP implementations for PE-based mid-market companies – allows leadership to focus on running the business rather than managing technical complexity.
The Strategic Imperative
All in all, “good enough” data infrastructure is an acceptable starting position. It becomes a strategic vulnerability when it persists beyond the point where company complexity demands integration.Companies that successfully scale through acquisitions while building data infrastructure in parallel create two forms of value. Operationally, they can identify synergies, optimize capital allocation, and respond to market dynamics with confidence. At exit, they command premium valuations because buyers can clearly see performance drivers, growth opportunities, and the infrastructure to sustain momentum under new ownership.
The companies that defer data infrastructure investment until it becomes urgent find themselves in a different position: scrambling to answer investor questions, unable to demonstrate consolidated company trends, and leaving value on the table because the data doesn’t support the narrative.
The decision point is clear: organizations early in their acquisition strategy should establish the foundation now. Organizations deeper into their growth should treat data consolidation as a strategic priority, not an operational project to be deferred. The cost of action is material, but the cost of inaction compounds exponentially.
Building a growing PE-backed company through acquisitions? Schedule a consultation to discuss how data strategy can support your acquisition velocity while positioning the company for optimal exit outcomes.
Continue the Series
You’ve built the data foundation. Now what? In Part 2, we explore how your finance function should use that data to drive growth—not just report on what already happened.
→ Part 2: Your Finance Function in 2026 (Stay Tuned) Discover why 50% of your “top clients” might not be profitable, and what strategic finance actually looks like in 2026.
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