Planning that survives contact with the deal.
Driver-based forecasting, rolling forecasts, and variance analysis rebuilt from the ground up around how PE-owned businesses actually operate - deal to deal, add-on to add-on, covenant to covenant.
Most FP&A models weren't built for PE ownership - or PE speed.
A budget built for a steady-state business breaks the moment a bolt-on acquisition, a new cost line, or a shift in the deal thesis hits it. Most portfolio finance teams are patching last year's spreadsheet rather than planning.
Forecasts don't survive the first re-forecast
Static, hard-coded budgets can't absorb a bolt-on, a new site, or a change in trading conditions without days of rebuild - so forecasts quietly stop being used.
Variance analysis raises questions, not answers
Actual-vs-budget packs show that numbers moved, but not the driver-level "why" a CFO needs to defend the number at the board table.
No scenario view for the deal thesis
When the sponsor asks "what does the model say if we pull that lever," the honest answer is often a week of analyst time, not an afternoon.
One person holds the model in their head
Forecasting logic lives in one spreadsheet, understood by one person - a single point of failure the sponsor doesn't know they're carrying.
A planning function built around drivers, not last year's tab.
Every engagement is scoped to the business - typically drawing on the three areas below, sequenced by what will move the needle on the value creation plan first.
Driver-based budgeting & rolling forecasts
Budgets and forecasts rebuilt around the operational drivers that actually move the P&L - volume, price, mix, headcount, capacity - so a re-forecast is a input change, not a rebuild.
- Driver library mapped to your operating model
- Rolling 12-18 month forecast cadence
- Built to flex for bolt-on acquisitions
Variance & bridge analysis the board can read
Actual-vs-budget and actual-vs-prior-year bridges that isolate volume, price, mix, FX and one-off effects - so a variance tells you what to do next, not just what happened.
- Automated bridge builds each close cycle
- Driver-level commentary, not just numbers
- Consistent format from FP&A to board pack
Scenario & sensitivity modelling for deal theses
Flexible scenario models that let you stress-test the deal thesis, price a bolt-on, or answer a sponsor's "what if" in an afternoon, not a week.
- Live sensitivity toggles on key drivers
- Bolt-on / add-on modelling templates
- Downside & covenant-headroom scenarios
13-week cash forecasting
A rolling short-term cash forecast tied back to the same driver logic, so covenant headroom is visible weeks before it becomes a board-meeting surprise.
- Weekly cash forecast, reconciled to actuals
- Covenant headroom tracked automatically
- Early warning, not late discovery
Diagnostic-led. No lengthy discovery decks, no theory.
Every engagement starts with a short, fixed-scope diagnostic - so you know exactly what's broken in the planning process and what it takes to fix it before committing to a full programme.
Diagnose
A focused review of the current budget, forecast and variance process - benchmarked against what PE ownership actually demands.
~3 weeksDesign
A driver-based model design and a prioritised roadmap - what to rebuild first, and the business case for each step.
Fixed-scopeDeliver
Hands-on build of the model, forecast cadence and reporting - with a founder-led team accountable to the outcome, not billable hours.
Outcome-basedFP&A outcomes from the field
Building a Group FP&A function from the ground up
Led the transformation of the group FP&A function and reporting for a Tier 1 aerospace supplier, replacing fragmented site-level processes with a single group standard.
Making branch profitability visible for the first time
Overhauled FP&A capability across a major UK insurance broking group's branch network, driving best practice and transparency into every branch's numbers.
Ready to see what a diagnostic would find in your planning process?
A fixed-scope, three-week review - with a clear view of what to fix first.