The short answer
Companies in a group end up running on separate spreadsheets because each entity brings its own systems, chart of accounts and definitions, and nothing connects them. The fix usually isn’t forcing one ERP on everyone. It’s agreeing on shared definitions, mapping each company to them, and building a data layer that feeds one set of dashboards everyone trusts.
Key takeaways
- Spreadsheet sprawl is a structure problem that builds up through acquisitions and local workarounds.
- The hidden costs are stale decisions, hidden problems and endless debates about whose number is right.
- Standardizing on one ERP is sometimes right, but it’s often slow, expensive and disruptive.
- A shared data layer on top of existing systems usually delivers one version of the truth faster.
- It starts with agreeing what revenue, a completed job and margin mean across the group.
Ask the leadership team of a holding company or multi-entity business a simple question, like “what was our margin by service line last month?”, and watch what happens. Someone emails each company. Each company sends back a spreadsheet. The numbers don’t quite match. A week later, after a lot of reconciling, you get an answer that’s already out of date.
This isn’t a people problem. It’s a structure problem, and one of the most common bottlenecks in growing organizations.
Why do multi-entity companies run on spreadsheets?
Nobody designs a five-spreadsheet operation on purpose. It accumulates:
- Acquisitions. Each company you add brings its own accounting system, field software and habits.
- Local workarounds. When a system doesn’t do what a team needs, someone builds a spreadsheet. It works, so it stays.
- Different definitions. One company counts a job as complete when the crew leaves, another when it’s invoiced. Both are reasonable. Together they’re unreconcilable.
- No shared data layer. Even when each system is decent on its own, nothing pulls them into one consistent view.
What does spreadsheet reporting cost a holding company?
The obvious cost is time: finance and operations people spend days every month collecting, cleaning and reconciling instead of analyzing. The bigger costs are harder to see:
- Decisions get made on numbers that are weeks old, or on gut feel because the numbers aren’t ready
- Problems at one company hide inside consolidated totals until they’re expensive
- Every report becomes a debate about whose number is right
- Integrating the next acquisition is slower, because there’s no standard to integrate into
Running on too many spreadsheets? In a working session we’ll map where your numbers break down and the first fix that pays off. Book a working session ›
Should every company move to the same ERP?
Sometimes. But it’s often expensive, slow and disruptive to businesses that run fine on their own tools. Compare the two common paths:
| One ERP for every entity | Shared data layer on existing systems | |
|---|---|---|
| Best when | Entities run similar operations and current systems are failing | Entities differ, or current systems work well locally |
| Time to one view | Long: every company must migrate first | Shorter: connect sources and build dashboards |
| Disruption | High for every entity | Low: day-to-day tools stay the same |
| Future acquisitions | Migrate each one onto the ERP | Map each one to the shared definitions |
If a full move does make sense, it’s an ERP implementation and integration project. For most groups, the data layer comes first. For PE-backed platforms adding companies through add-ons, we walk through the full playbook in how to report across portfolio companies on different ERPs.
How do you get one version of the truth across companies?
- Agree on definitions. Decide, once, what revenue, a completed job, utilization and margin mean across the group.
- Map each company to the standard. Translate each entity’s chart of accounts and job codes into the shared definitions.
- Connect the sources. Pull data automatically from each system into one place on a schedule, instead of emailing spreadsheets.
- Build the views people need. Dashboards for leadership, each company and each function, all reading from the same numbers.
- Retire the spreadsheets. Once people trust the dashboards, the side spreadsheets stop being necessary.
This is the core of our data, analytics and BI work, and it follows the same five steps we use on every engagement (see how we work).
What changes when it’s working?
The monthly close gets shorter, leadership sees performance across every company without waiting, and conversations shift from “whose number is right” to “what do we do about it.” New acquisitions plug into a standard instead of becoming another island. For operators running many sites, the same standards are what make a shared back office possible, covered in centralizing back-office work across locations. The same pattern shows up in field-heavy groups, too: if your companies include storm or utility contractors, the data you connect also speeds up post-storm closeout.
Frequently asked questions
What is a data layer?
A data layer is a central place, often a data warehouse, where data from each company’s systems is pulled in automatically, translated into shared definitions and used to feed reports and dashboards. The day-to-day systems stay the same.
Do we need the same accounting system at every company?
Not necessarily. Many groups get consolidated reporting by mapping each company’s chart of accounts to a shared standard and connecting the systems, instead of migrating everyone to one platform.
How long does it take to get consolidated dashboards?
It depends on the number of entities and systems, but connecting existing systems to a data layer is usually much faster than migrating every company to a new ERP, because operations don’t have to change first.
What tools are used for multi-entity reporting?
Common pieces include a data warehouse or SQL database, integrations or APIs to each source system, and a BI tool such as Microsoft Power BI for dashboards. The right mix depends on what you already run.
Where should a holding company start?
Start with definitions. Agree on how the group measures revenue, completed work, utilization and margin, then connect the one or two systems that hold most of that data.
