End-to-end, decision-grade analytics platforms — Microsoft Fabric and Power BI, built by people who've used the reports. Plus interim finance leadership for PE-backed businesses. Both, from one team.
IT firms build the platform. Finance teams struggle to use it. Dashboards go stale, reports get rebuilt in Excel, the investment doesn't land. We've sat in both chairs — so the handoff doesn't break, because there isn't one.
A consultancy drops in Microsoft Fabric or Power BI, hits the implementation milestones, and hands over the keys. Finance teams are left to translate the architecture into the actual numbers the board asks for — a job they're not equipped for and shouldn't have to do.
We've been the FP&A leads who needed answers at 11pm the night before board. We're now the ones architecting the Fabric semantic models and building the Power BI reports. The platform is designed around the decision it supports — not the deployment milestone it was budgeted against.
Transformation and interim leadership, delivered by the same person who's done both as the employee and now does both as the specialist. Productised scopes, clear durations, defined deliverables.
Microsoft Fabric · Power BI · semantic modelling · governance · adoption
Audit, architecture, and the first use case.
A full data-maturity audit, a Fabric reference architecture designed around how finance actually consumes the numbers, and a working first use case live in Power BI. The foundation every subsequent build sits on.
The full build, end-to-end.
A complete Fabric + Power BI implementation aligned to board, lender, and operational decisions. Semantic models, DAX, dashboards, governance, and the team upskilled to maintain it when we leave.
Pick up where IT left off.
For stalled or underperforming Fabric and Power BI implementations. Diagnose the gap between architecture and adoption, rebuild where needed, retrofit governance, and get finance using the platform the business already paid for.
For PE-backed businesses · post-deal, pre-exit, CFO transitions
Post-deal finance stabilisation.
Day-one reporting baseline, board-ready management accounts, and a monthly close process that works. For platforms and bolt-ons where the finance function inherited from the deal isn't fit for the VCP.
Pre-sale finance clean-up.
QoE-grade data, a clean audit trail, and a KPI pack that holds up under diligence. Begun 12–18 months before process — because buyers price uncertainty with a discount.
CFO-transition cover.
Continuity during CFO or Head of FP&A gaps. Running the function end-to-end while the permanent hire search is underway — with a handover plan that protects the team through the switch.
The building blocks deployed inside every engagement — platform and function, under one roof.
Transformation and interim engagements both land in the same vocabulary — the one Finance Operating Partners actually use in monthly reviews and investment committees. No translation layer between you and the work.
Anonymised vignettes from recent engagements. Different sectors, different scales, the same signature — reporting you can trust, on a timetable you can hold.
A specialist lender with £820m AuM was reporting to the board and to senior lenders on a five-working-day close. The cycle was manual, spreadsheet-driven, and a bottleneck heading into the deal.
Directed the FP&A function through the transaction. Re-engineered the reporting stack — Amazon Redshift warehouse, Tableau front end — so the loan book and AuM numbers landed at WD1. Rebuilt the monthly pack (P&L, balance sheet, cash flow, borrowing base, distressed-borrower analysis) around the new source of truth. Partnered the CFO on financial due diligence and IM preparation.
Close cycle compressed from WD5 to WD1. Lender-grade reporting delivered on time through the transaction. PE investment completed; three analysts developed and a permanent Head of FP&A hired.
Three-plus years into the hold, and the sponsor needed sharper commercial decision-making to support an extended value creation plan. Operationally complex economics — seasonal, yield-driven, multi-site — and the in-house model didn't reflect how the business actually ran. Commercial sensitivity analysis was taking five days to run and landing too late to be useful.
Built the group's financial model from operational drivers up, working directly with the FD and operational heads to integrate site-level metrics into planning. Engineered SQL extraction from the data warehouse so the finance team could reach datasets previously beyond their technical capability. Embedded modelling and data-analysis practices through structured upskilling, so the capability held after the engagement ended.
Commercial sensitivity analysis compressed from five days to sixty minutes. Finance team self-sufficient on the new model and the underlying data by handover. Operational and financial planning joined up on a single source of truth.
Reporting credibility lost following a global finance systems transformation. The month-end pack was late, inconsistent across platforms, and the C-suite had stopped trusting the numbers — net profit, fee income, production, recovery, utilisation, debtors, WIP, cash.
Led month-end production and reconciliation across all metrics, driving a single version of the truth. Rebuilt the budget net profit reporting with new templates and macros for speed and accuracy. Resolved VBA and Excel errors carried over from the transformation. Established a robust reporting timetable and held it. Managed two management accountants, rolled out Power BI training to the wider team, and built the dashboards that replaced the spreadsheet layer.
Reconciliation variances resolved to zero. C-suite credibility in the numbers restored. Reporting delivered reliably to timetable on a single source of truth.
When you hire through a recruiter or a Big 4 interim desk, a significant share of the day rate pays for account managers, sales overhead, and bench marketing — not for the operator doing the work.
Working direct means a cleaner commercial relationship, faster onboarding, and a material cost difference on engagements that run longer than a few weeks. No sales layer, no change-of-consultant risk, one accountable operator.
Specifics discussed in scoping conversations — every engagement is priced to its actual scope.
Indicative · Industry benchmarks · UK mid-market
A free 30-minute call to map your current finance data landscape against what a decision-grade platform looks like. If it's useful, we'll send a tailored Fabric Readiness Audit PDF afterwards. No pitch deck, no pipeline follow-up.