Start with the Monday meeting
Write down the decisions your partners and operating team make in a normal week. A new opportunity may need a screening decision. A portfolio company may need a reporting follow-up. A workstream may need an approval. Each requires a different view of the same firm.
Build the first dashboard around those decisions. The firm view should connect companies, funds, active opportunities and assigned work. Company reporting belongs in a company view; diligence belongs with the deal. Mixing everything into one enormous table makes the apparent completeness hard to use.
- Partner: exceptions, decisions due and the person responsible.
- Deal team: stage, open diligence questions and the next decision.
- Operating partner: company reporting, operating priorities and evidence of progress.
- Finance team: reporting completeness, approved periods and unresolved differences.
Make missing and stale data visible
The most important dashboard state is often an empty cell. Missing revenue is not zero revenue. A report uploaded today can still describe an old period. A number extracted from a document can be readable without being approved.
For every company-period, keep the reporting period, currency, source document, reporting owner and review status together. Show the date of the latest complete reporting package separately from the upload date. The team should be able to identify companies that have not reported without opening every folder.
| Field | What it tells the team |
|---|---|
| Reporting period | The period the figures actually describe |
| Source reference | Where the number can be checked |
| Review status | Whether a person has approved it |
| Missing fields | What still needs to be collected |
| Owner and due date | Who can close the reporting gap |
Agree on definitions before comparing companies
Revenue, EBITDA and cash are useful labels, but they do not settle the definition. One company may report adjusted EBITDA while another supplies an unadjusted figure. One may use a month while another uses a quarter. Adding these numbers produces a tidy total with an unclear meaning.
Keep reported figures and normalization adjustments separate. Define the reporting period, unit and calculation for each comparable measure. When a metric cannot yet be compared, show the reason. A visibly incomplete comparison is more useful than a precise-looking total that combines unlike measures.
Connect exceptions to an accountable next move
A red indicator is an observation. The useful workflow starts when the team gives it an owner, a due date and a decision. For example, an incomplete monthly report can create a request to the company finance lead. An unresolved diligence question can hold a stage transition for review.
Keep the observation, proposed action, approval and result distinct. That distinction becomes more valuable as automation increases: the system can help organize and prepare work while the firm retains responsibility for consequential decisions.
- Observation: what changed and which source supports it.
- Hypothesis: what the team thinks caused the change.
- Action: a defined task with an accountable owner.
- Outcome: a measured result, including no improvement or an uncertain result.
Test the dashboard with an intentionally imperfect pack
Before choosing software, try one complete company report, one missing report and one document with a corrected figure. Ask a new team member to find the source, identify the gap and assign the follow-up. Then revise the source and check whether the review state remains clear.
The downloadable worksheet turns these questions into acceptance criteria. It is a proposed working framework, not a benchmark of how every PE firm operates. Use it to define your own pilot and compare demonstrated behavior rather than feature labels.
Download the dashboard requirements worksheetHow this becomes an Agentic Equity layer
The first layer is a reliable operating picture. The next is coordination: source collection, reporting review, diligence tasks and decisions that share a common record. The longer-term opportunity is to learn which actions improve businesses, and under which conditions.
Learning needs a record of the baseline, the intervention and the result. It also needs evidence that the improvement can transfer to another company. Agentic Equity begins with a working firm workspace and manual evidence review; broader AI analysis and external connections depend on configuration and authorized access. The ambition is to make improvement repeatable, with claims that can be checked.