You closed the deal. The champagne is put away. Now you own a company whose data you evaluated during diligence but never had to operate.
The first 100 days after acquisition set the trajectory for the entire hold period. Get the data foundation right and every value creation initiative that follows moves faster. Get it wrong and you spend the next three years fighting the same reconciliation problems, asking the same questions, and getting different answers.
This playbook is for operating partners and portfolio company leaders who just closed a deal and need to know what to do with data in the first 100 days. Not a technology roadmap. Not a digital transformation strategy. A practical sequence of actions that builds the data foundation for everything that comes after.
Why the first 100 days matter for data
Three reasons.
Attention is highest. In the first 100 days, the new management team is paying attention to everything. They expect change. They expect questions. After 100 days, routines set in and resistance to change increases. Use the window.
Problems are still visible. During diligence, you identified data issues. Right after close, people still remember what those issues were. Six months later, those findings are in a binder nobody opens. Act while the context is fresh.
The value creation plan depends on it. Every PE value creation plan includes elements that require data. Revenue growth analytics, operational efficiency metrics, add-on acquisition integration, management reporting for the board. If the data foundation is weak, these initiatives stall.
Day 1 through 30. Assessment and triage
The goal for the first month is not to fix anything. It is to understand what you bought and what needs attention first.
Inventory the systems
Build a map of every system that touches financial or operational data. ERP, CRM, billing, HR, inventory, marketing automation, BI tools, spreadsheets. Yes, spreadsheets count. At many mid-market companies, the most critical business logic lives in Excel.
For each system, document: what data it holds, who owns it, how it connects to other systems, and when it was last updated or migrated.
This is not a technology audit. You are mapping the data supply chain. Where does data originate? How does it move? Where does it end up in the financial statements?
Identify key person dependencies
In the first two weeks, you will discover who the “data people” are. Not necessarily the ones with data in their title. The controller who builds the board deck. The operations manager who maintains the customer spreadsheet. The analyst who runs the monthly reconciliation.
Make a list. For each person, note what data processes they own exclusively. These are your single points of failure. You do not need to eliminate them in the first month, but you need to know where they are.
Assess data quality on the metrics that matter
You do not need to audit every data field. Focus on the metrics that drive the value creation plan.
If the plan depends on revenue growth, test revenue data quality. Can you segment revenue by customer, product, channel, and geography? Does it reconcile across systems?
If the plan depends on margin improvement, test cost data. Can you see costs at the unit level? Are allocations documented?
If the plan involves add-on acquisitions, test the integration readiness. Can the current systems absorb another company’s data? Is there a master data model?
Deliver the assessment
At the end of 30 days, you should have a one-page assessment that answers four questions:
- What is the current state of data infrastructure? (Scored against your own criteria, not an abstract maturity model)
- What are the top 5 risks? (Specific, with estimated impact)
- What are the top 5 quick wins? (Achievable in the next 30 days)
- What needs to be true about data for the value creation plan to work?
Present this to the deal team and the portfolio company CEO. Align on priorities before moving to execution.
Day 31 through 60. Foundation building
Now you fix things. But selectively. The goal is to build the minimum data foundation that supports the value creation plan and the quarterly reporting rhythm the PE firm expects.
Establish the management reporting package
The PE firm needs a monthly reporting package. Revenue, EBITDA, KPIs, cash flow. Define exactly what this package contains, where the data comes from, and who is responsible for producing it.
This is not optional. This is the operating system for the next three to five years. Get the definitions right now. Agree on the methodology. Document the calculations.
Common mistake: accepting whatever the company was producing before the acquisition. The pre-deal board deck was designed to tell a specific story to the previous owner. You need a package designed for value creation tracking.
Fix the top reconciliation issues
From your assessment, take the top two or three reconciliation issues and fix them. Not with a one-time manual fix. With a repeatable monthly process.
Revenue reconciliation between booking, billing, and GL is almost always number one. Customer count consistency between CRM and finance is usually number two.
The standard: at month end, these reconciliations should complete in less than one day with documented explanations for any remaining variance.
Cross-train on critical processes
For every key person dependency you identified, start cross-training. This does not mean replacing people. It means making sure at least one other person can perform each critical data process.
The minimum bar: if any one person is unavailable for two weeks, the monthly reporting package still gets produced on time.
Start the data dictionary
Begin documenting the definitions of every metric the company reports. Revenue, ARR, MRR, retention, churn, CAC, LTV, whatever the business tracks. For each metric: the definition, the formula, the source system, and any known issues or exceptions.
This dictionary will grow over time. Start with the 15 to 20 metrics in the management reporting package. Add to it as new questions arise.
Day 61 through 100. Value creation sprint
The foundation is in place. The reporting package works. The critical reconciliation issues are fixed. Now you build the analytical capability that drives value creation.
Build the customer analytics the deal thesis requires
Every deal thesis has assumptions about customers. Growth rate, retention, expansion, cross-sell, geographic expansion. Build the analytics that test these assumptions against actual data.
Customer cohort analysis is the starting point. How do customers acquired in different periods behave over time? Is retention improving or declining? Is expansion revenue growing?
If the deal thesis depends on improving retention from 85% to 92%, you need to see the current trajectory by cohort, by segment, and by reason for churn. Without this, the value creation plan is guessing.
Establish operational KPIs with targets
Move beyond financial reporting to operational metrics that predict financial outcomes. These vary by business type but typically include: sales pipeline velocity, customer onboarding time, support ticket resolution, product usage, employee productivity.
Set baseline measurements from the data you have. Establish targets for 12 months out. Build the reporting to track progress monthly.
Prepare for add-on integration (if applicable)
If the value creation plan includes add-on acquisitions, build the integration playbook now. What systems will the acquired company use? How will data be migrated? What is the timeline from close to integrated reporting?
Having a documented integration playbook before you need it reduces the cost and timeline of every subsequent acquisition. The first integration is the hardest. The playbook makes each one faster.
Deliver the 100-day report
At day 100, present a report that covers:
- What was done (systems mapped, reconciliations fixed, reporting established)
- What the data shows (baseline metrics, early trends, surprises)
- What still needs attention (remaining gaps, resource requirements)
- Recommended data initiatives for the next 12 months (tied to value creation plan)
This report is the bridge between the triage phase and the steady-state operating rhythm. It should feel like a handoff from “we are getting our arms around this” to “we know where we stand and we have a plan.”
The 5 mistakes every new owner makes
1. Starting a technology project instead of a data project
The instinct is to buy a new BI tool, implement a data warehouse, or migrate to a cloud platform. These are technology projects. They take months, cost real money, and do not solve the underlying data quality and process problems.
Fix the data first. Document the definitions. Reconcile the systems. Then, if a technology investment makes sense, you will know exactly what it needs to do.
2. Trusting the diligence report as a complete picture
Diligence reports identify issues at a point in time with limited access. Once you own the company, you have full access. You will find things the diligence team missed. Expect it. Budget time and resources for it.
3. Keeping the pre-deal reporting unchanged
The previous owner had different priorities, different time horizons, and different definitions of success. Your reporting package should reflect your value creation plan, not theirs. Update it in the first 60 days.
4. Underinvesting in people
Data readiness at a mid-market company is fundamentally a people problem. The systems are usually adequate. The issue is that nobody owns data quality, nobody documents processes, and the finance team is too small to do both their day job and data improvement work. Budget for at least a part-time resource dedicated to data operations.
5. Ignoring data until the exit
The same data issues that complicated your acquisition diligence will complicate your exit diligence. Start fixing them now, while you have time. The companies that invest in data readiness during the hold period exit faster and at higher multiples.
For more on how data issues affect exit valuation, see How Data Problems Cost One Company Half a Turn.
What good looks like at day 100
You do not need a perfect data infrastructure at day 100. You need:
- A management reporting package that the PE firm trusts and the company can produce reliably
- Revenue reconciliation that works monthly without heroic effort
- Documented definitions for every metric the company reports
- At least one backup person for every critical data process
- A clear view of the customer analytics that drive the deal thesis
- A prioritized roadmap for the data work that still needs to happen
This is not glamorous work. It does not make LinkedIn posts. But it is the difference between a portfolio company that creates value and one that explains why the numbers this quarter “need some context.”
For the exit readiness perspective, see PE Exit Readiness: The Data Checklist Most Teams Miss.
For a weekly brief on portfolio company data operations and value creation, subscribe to Inside the Data Room.