Day one of an acquisition is exciting. Day thirty is when the operating partner calls and asks why there's still no consolidated view of the combined entity. The deal model assumed $2M in synergies. Nobody can quantify whether you're on track because the two companies report their numbers in completely different ways.
This is the post-M&A data problem, and it's far more common than anyone admits during due diligence.
The Day-One Data Reality
Every acquisition inherits a data mess. The acquired company has its own:
- Accounting system with its own chart of accounts
- CRM with its own pipeline definitions and stages
- Operational tools that may overlap, conflict with, or have no equivalent in the acquiring company
- Reporting definitions that use the same words to mean different things (“revenue” includes or excludes certain items depending on who built the report)
Before you can answer any meaningful question about the combined entity, you need to normalize all of this. In most companies, this normalization happens manually — someone in finance builds a massive Excel workbook that maps the acquired company's data into the parent's reporting framework.
That workbook becomes the most critical and most fragile piece of infrastructure in the organization.
The 30-Day Playbook
Getting to unified reporting in 30 days requires a deliberate, repeatable approach. Here's what it looks like:
Week 1: Connect everything. Identify every data source in the acquired entity — accounting, CRM, operations, HR, payroll. Stand up automated ingestion pipelines for each one. The goal is to get raw data flowing into a central warehouse without manual intervention. With 500+ pre-built connectors and a team that's done this before, this takes days, not weeks.
Week 2: Map and normalize. This is the hard intellectual work. How does the acquired company's chart of accounts map to the parent's? What's the equivalent of their “gross margin” in your reporting framework? Where do the definitions diverge, and what's the right reconciliation approach? This requires business context, not just technical skill.
Week 3: Build the models. With the mapping defined, build the transformation logic that turns raw data from both entities into a unified set of metrics. Revenue, COGS, gross margin, headcount, operational KPIs — all calculated the same way regardless of which entity the data came from. Everything version-controlled so you can audit any number back to its source.
Week 4: Deliver and validate. Stand up the dashboards and reports. Walk leadership through the numbers. Validate against known figures. Adjust where necessary. By the end of week four, the board has a single view across the combined entity.
Why Speed Matters
The typical alternative — hiring consultants to do a “data integration assessment,” followed by a 6-month implementation project — fails for two reasons.
First, speed-to-insight directly impacts value creation. Every month without unified reporting is a month where synergy opportunities go unidentified. If the deal model says you should consolidate two warehouses, reduce duplicate vendor contracts, or standardize pricing — you can't act on any of that until you can see across both entities.
Second, the longer the data integration takes, the more entrenched the manual workarounds become. Once someone builds that master Excel workbook, it takes on a life of its own. Six months later, ripping it out is harder than building the automated solution would have been on day one.
Making It Repeatable
For platform companies doing serial acquisitions, the real value isn't just integrating one entity. It's building a repeatable playbook that makes each subsequent acquisition faster.
When you've already defined the standard chart of accounts, the canonical set of KPIs, and the transformation logic for normalizing data from common source systems — the second acquisition integrates in two weeks instead of four. The third takes a week.
This is where the managed model shines. Your data partner carries the institutional knowledge from every previous integration. They've seen the edge cases. They know which source systems have API quirks. They've already built the connectors. Each new bolt-on plugs into existing infrastructure instead of starting from scratch.
The Bottom Line
Post-M&A data integration doesn't have to be a six-month project. With the right approach and the right partner, you can go from close to consolidated reporting in 30 days. The deal thesis depends on it.