Every private equity firm uses spreadsheets. That is not the problem.
Excel is flexible, familiar and useful. It is still one of the best places for financial modeling for PE, one-off analysis, scenario planning and partner questions that need a fast answer. Most investment teams do not need to be persuaded to stop using spreadsheets altogether.
The question is narrower and more important: should spreadsheets be the recurring system for private equity portfolio monitoring?
That is where the model starts to break. A spreadsheet can hold data. It can calculate. It can support a decision. But portfolio monitoring is not just calculation. It is the repeatable process of collecting information from portfolio companies, mapping it to consistent definitions, checking it, comparing it and making it usable for investment teams, operating partners, finance teams and management.
Once that process depends on spreadsheet files, the firm is no longer only using spreadsheets. It is using them as infrastructure.
The practical rule
Keep spreadsheets for analysis. Move recurring monitoring into a governed workflow that can connect systems, normalise data, preserve definitions and support portfolio-level comparison.
Why spreadsheets persist in private equity
Spreadsheets persist because they solve real problems. They let teams move quickly before a system exists. They let a deal team test assumptions without asking for a product change. They let finance build a first version of a board pack, operating model or KPI tracker without waiting for implementation.
For early monitoring, that can be enough. A small portfolio, a stable reporting cadence and a manageable number of stakeholders can often survive on a well-maintained spreadsheet process.
The difficulty is that successful funds rarely stay there. The portfolio grows. New companies arrive. Operating data comes from different source systems. KPI definitions become harder to compare. The board pack needs to be faster. LP questions get more specific. Value creation teams want a clearer operating view.
The spreadsheet that once gave the team flexibility starts creating dependency.
Where spreadsheet-based monitoring breaks
The first signs are usually operational, not strategic. Multiple versions circulate. One portfolio company changes the format. A metric definition is slightly different this quarter. A formula gets overwritten. A manual adjustment is understood by one person and invisible to everyone else.
Each issue can be fixed locally. The problem is that the fixes compound into a process nobody fully trusts.
| Spreadsheet symptom | Monitoring risk | What should replace it |
|---|---|---|
| Multiple files and tabs | The current version is unclear | Central workflow and audit history |
| Different KPI definitions | Comparison becomes caveated | Metric mapping and governance |
| Manual consolidation | Finance time moves into data plumbing | Automated ingestion and normalisation |
| Delayed board packs | The firm sees issues after the moment to act | Repeatable reporting cadence |
| Hidden spreadsheet logic | The process depends on individual memory | Documented transformation rules |
This is why replacing spreadsheets is not mainly a tooling decision. It is a governance decision. The firm is deciding which parts of portfolio monitoring should be flexible and which parts need to be standardised, repeatable and trusted.
What replacing spreadsheets actually means
Replacing spreadsheets does not mean banning Excel. That framing is too simplistic for private equity.
A better framing is this: spreadsheets should remain a workspace for analysis, but they should stop being the system of record for recurring monitoring.
In practice, that means the recurring workflow moves into software that can:
- connect to the source systems that matter inside each portfolio company
- normalise operational, financial and customer data into a consistent layer
- preserve metric definitions and transformation logic
- support permissions, submissions, approvals and auditability
- make comparison easier across time periods, business units and portfolio companies
- give investment teams a monitoring view that updates without rebuilding the model every month
That is the difference between a spreadsheet replacement project and a genuine private equity portfolio monitoring workflow. The goal is not a cleaner dashboard. It is a cleaner operating layer underneath the dashboard.
Where AI-driven analytics fit
HubSpot's recommendation for this article points toward AI-driven analytics. That direction is right, with one caveat: AI is only useful when the underlying data is clean enough to trust.
If a firm has inconsistent KPI definitions, disconnected source systems, manual adjustments and unclear permissions, AI will not solve the monitoring problem. It will simply sit on top of the same fragility. The better sequence is foundation first, analytics second.
Modern portfolio management tools and investment tracking software should therefore start with ingestion, mapping, normalisation and governance. Once that foundation exists, private equity analytics become more useful because the model can reason from a more reliable version of the portfolio picture.
For a deeper view on the metric layer, Planr has written separately about how portfolio KPI standardization works in private equity.
Proof point: Dominique Dawes Academy
The Dominique Dawes Academy case study shows the pattern at operating-company level.
After Trivest invested in Dominique Dawes Academy, Adam Zeitsiff came in as CEO to help lead the business through its next stage of growth. The issue was not that the business had no data. The data existed, but it lived across different systems: point-of-sale data, NetSuite financials and CRM data.
The harder part was comparison. Month over month. Year over year. Quarter over quarter. Gym versus gym.
Planr's role was to connect and normalise the data so it could become a trusted operating layer. In the signed-off case study, Adam describes the impact in practical terms: a clearer daily view of the business, better visibility for local managers and monthly reporting moving from two to three weeks to two to three days. The finance team saves around 60 days per year.
The lesson for private equity firms is broader than one operating company. Portfolio-level visibility starts with clean, comparable data inside the portfolio companies themselves. If every company is still doing the hard work of comparison manually, the GP cannot build a reliable portfolio view one level higher.
Read the Dominique Dawes Academy case study
See how a PE-backed operating company moved from fragmented systems and manual comparison toward one trusted data layer for reporting, operating cadence and portfolio visibility.
The end state
Replacing spreadsheets in PE monitoring is not a rejection of spreadsheets. It is a recognition of where they create value and where they create risk.
Use spreadsheets for financial modeling, analysis and scenario work. Use governed portfolio monitoring software for recurring submissions, data normalisation, metric definitions, permissions, reporting cadence and portfolio-wide comparison.
That distinction matters because the highest-value monitoring questions in private equity are rarely about a single number in isolation. They are about whether the firm can trust the data, compare it across the portfolio and act before the reporting cycle has already moved on.
When spreadsheets stop being the monitoring layer, investment teams get something more durable: a repeatable workflow that can scale with the portfolio.
