Cube vs. Mosaic for a PE Portfolio Company's Board Reporting

Most PE sponsors have a specific reporting template, sometimes a spreadsheet they've used across their whole portfolio, that the portfolio company is expected to fill in on a fixed schedule. If that template is itself a spreadsheet, Cube's approach of building your model to feed that exact template directly can save real time versus manually re-keying numbers every reporting period.

If the sponsor is more flexible about format and mainly wants a consistent set of metrics delivered reliably, a dashboard-based tool has more room to add value beyond just filling in a fixed template. Ask the sponsor's own portfolio operations team directly what format they actually prefer before assuming either answer, since some sponsors have a strong opinion here and others genuinely don't mind as long as the numbers are accurate and arrive reliably on schedule.

Covenant calculations, debt-to-EBITDA ratios, fixed charge coverage, often have specific definitions negotiated into the credit agreement that don't match a standard EBITDA calculation off the shelf. Whichever tool you use needs to carry the exact covenant definition from your specific credit agreement, not a generic debt ratio, since a mismatch here isn't just an inconvenience, it can create a false covenant breach or false comfort depending on which direction the calculation is off.

Get your credit agreement's precise covenant language in front of whoever configures the model before the first reporting period runs, rather than discovering a definitional gap the month a covenant is actually close to being tested.

Check each covenant calculation against these points:

• Pull the exact covenant definitions from your credit agreement instead of using a generic EBITDA or debt ratio.
• Confirm the tool can carry your negotiated add-back definitions exactly as written.
• Test debt-to-EBITDA and fixed charge coverage in the model against a period you have already reported to the lender.
• Check covenants at least as often as the agreement requires, and consider checking more often to catch a potential breach early.
• Make sure every reported number can be traced back to its source, since the sponsor's team may want to audit it.

If your finance team already builds the EBITDA bridge, add-backs, and covenant calculation in a spreadsheet that ties out correctly, Cube's approach of syncing that model against your accounting data keeps the logic exactly where it's understood and auditable, which matters when a sponsor's own team may want to trace a number back to its source.

This auditability is worth real weight at a PE-backed company, since a sponsor's deal team or a lender's credit team reviewing your numbers will often ask to see exactly how a figure was derived, and a transparent spreadsheet formula is easier to walk someone through than a black-box dashboard calculation.

Some sponsors prefer a live dashboard they can check between formal reporting periods rather than waiting for a monthly package; if that's your sponsor's preference, Mosaic's dashboard-first approach may fit better. Confirm in a demo that it can carry your specific EBITDA add-back definitions and covenant calculations exactly as negotiated, not a generic template, since sponsors and lenders will notice a discrepancy quickly.

Ask your sponsor directly whether they'd actually use self-serve dashboard access or whether they prefer receiving a formal package on schedule, since building for a preference the sponsor doesn't actually have is wasted effort either way.

Sponsors typically want to see actual results against the original deal model's projections, not just against a rolling internal budget, since the deal model is what they underwrote the investment against. Keep the original deal model as a fixed reference point in your forecasting tool, separate from your current operating budget, so a variance walk can show both how you're doing against this year's plan and how the investment thesis is tracking against what was originally underwritten at close.

Jirav's driver-based modeling is useful when a portco is evaluating an add-on acquisition and needs to model the combined entity's headcount, cost structure, and integration timeline, since a sponsor evaluating an add-on will want to see realistic integration assumptions, not just the acquired company's standalone numbers layered on top.

A driver-based model also makes it easier to show the sponsor a range of integration scenarios, faster versus slower headcount consolidation, for instance, rather than presenting a single fixed outcome that leaves no room for the deal team's own questions about timing and risk.