Exit readiness is built, not declared: A recap of our CFO roundtable in London

Today’s CFO goes well beyond control and compliance. They act as the architect of value: sequencing investment, quantifying return, and ensuring that the data substantiates the equity story. This requires establishing a transformation engine distinct from business-as-usual – a small, focused team working on the business rather than in it, supported by a regular “value council” to review trade-offs and progress.

This often includes:

• A finance function assessment (close, consolidation, FP&A, OTC/PTP, tax/treasury, technology/controls, people/operating model).
• A roadmap with defined owners, milestones, and benefits.
• A recurring readiness review to test evidence against likely buyer questions.

CFOs aligned around a shared goal: moving from spreadsheet-led reporting to governed, automated, and reconcilable data platforms – what many refer to as “industrialising the cube.” That typically means:

• A single source of truth across finance, CRM, projects, and HRIS.
• Auditability from board KPIs to transactional detail.
• A data dictionary with clear, consistent definitions: margin, project duration, ARR/NRR, SaaS mix, working capital.

The goal isn’t perfection, but credibility:  data that is reliable, reconcilable, and ready for scrutiny. In practice, that means automated ingestion, daily refreshes, reconciliation dashboards, and board materials drawn directly from governed models rather than bespoke spreadsheets.

Across the discussion, both sponsors and CFOs emphasised the importance of pragmatism: focusing investment where it creates genuine value rather than where it simply improves optics. When considering an initiative, teams should ask:

• Will it influence valuation?
• Will it make diligence easier?
• Will it enable a clearer storyline?
• Can an MVP be achieved within 90 days?

Many find a phased approach most effective – starting with Excel for speed, introducing structure and templates, then progressing to governed data models and targeted EPM tools where control matters most.

And buyer alignment is equally important as data quality. Strategic acquirers value synergies; secondary PE buyers seek repeatability. The right narrative must fit the right buyer. Data alone cannot sell the story.

Participants viewed AI through a pragmatic lens. It’s less about headcount reduction and more about scaling without additional overhead. The most meaningful use cases include:

• Close acceleration: automated reconciliations, anomaly detection, subledger tie-outs.
• Cash conversion: intelligent invoice matching, dispute classification, payment forecasting.
• Forecasting: machine learning enhancements to driver-based models for bookings, churn, and pricing elasticity.

Buyers increasingly expect visible, well-governed, AI-first signals: a use case pipeline, measured outcomes (e.g., shorter close, improved DSO, FTE redeployment), transparent data contracts and lineage, and clear governance around model accuracy and ethics.

CFOs strengthen their credibility by demonstrating measurable value creation through finance-led initiatives. That means establishing baselines, targets, and measurement methods across four core value areas:

• Efficiency: FTE leverage, outsourcing ROI, automation benefits.
• Working capital: DSO/DPO/DIO improvement, dispute resolution, cash conversion.
• Margin: price/mix optimisation, utilisation, procurement savings.
• Systems ROI: cycle-time reductions, control enhancements, opex avoidance.

Leading CFOs maintain a benefits ledger with 12-, 24-, and 36-month views – linked to the roadmap and reported with the same cadence as operational performance.

Exits are, in essence, stories supported by proof. The most effective CFOs prepare several data-backed narratives in advance (trade sale, secondary PE, IPO), each underpinned by a comprehensive data book: retention cohorts, revenue and margin bridges, CAC/LTV, pricing evolution, and working capital cadence.

That said, two common challenges frequently arise:

1. Revenue categorisation: Hybrid or tech-enabled models must clearly define what qualifies as “software.” Using consistent criteria – recurrence, delivery mechanism, margin profile, upgrade cadence, dependency on hardware – helps ensure transparency.
2. Organic vs. inorganic growth: In acquisitive businesses, definitions should be locked early, every transaction tagged, and pro forma restatements prepared well ahead of time.

Recent updates to UK GAAP (IFRS-style) lease accounting can introduce volatility into EBITDA and balance-sheet presentation – particularly for asset- or fleet-heavy businesses. Many CFOs now prepare a “frozen GAAP” view for comparability and include buyer-side bridges to current standards. The best advice: define the policy early, quantify impacts, and provide a clear, diligence-ready appendix with covenant and cash implications.

For PE-backed groups, integrating smaller, founder-led businesses, building a consistent finance and data culture can be as challenging as the technology itself. The most successful CFOs:

• Centralise policy, controls, and platforms – but federate planning inputs.
• Build a cross-functional “triad” of Data Engineering Lead, Finance Product Owner, and FP&A Architect.
• Invest in upskilling – SQL, Power BI, and data quality ownership.
• Maintain engagement through office hours, release notes, and OKR-linked adoption goals.

Above all, they seek advisers and partners who have practical experience with the journey, who can guide them with realism rather than theory.

By the time a process actually begins, the most exit-ready finance teams will have:

• Consistent trading performance and cash discipline.
• A transformation capability that doesn’t disrupt BAU.
• Reliable, reconcilable, and drill-through data.
• Buyer-specific narratives underpinned by data books.
• Quantified value creation with clear tracking.
• The ability to execute 90-day sprints to close final gaps.