CFO’s guide to sustainable Financial Planning and Analytics FP&A

The CFO’s Guide to Sustainable (Cloud) Financial Planning & Analytics (FP&A)

Isn’t the world a strange place at the moment?

I recently received a message from a mid-tier ERP vendor suggesting that finance teams adopt their new ERP platform with a bit of AI bolted to the side to improve FP&A reporting !

Yes—just reporting.

No mention of the key steps required to develop FP&A maturity.

No acknowledgement of the pain points finance faces during month-end close or forecasting.

No clarity on the drivers for change, operating model evolution, or the scale of the investment.

No conversation about the real business outcomes FP&A should support.

Let’s be clear:

❌ Moving ERP systems won’t fix broken FP&A, neither will AI alone
❌ ERP +AI alone won’t enable “green line” analytics
❌ ERP migrations without a strategy often delay—not accelerate—FP&A value

Most ERP programs fail to deliver transformative outcomes (80%). Many fall short on finance analytics, leaving frustrated finance teams resorting to Excel—again—as the de facto FP&A tool.

Cloud Isn’t the Silver Bullet for FP&A—But AI Might Be

While cloud ERP promises flexibility, agility, and scale, it rarely delivers enterprise-grade FP&A without targeted investment in data, operating model reform, and decision intelligence.

This is where AI-enabled FP&A comes in.

By embedding AI into forecasting, scenario modeling, and driver-based planning, CFOs can unlock agility, accuracy, and automation. But it requires intent—not just tech.

Top Tips: Build the FP&A Model Your Business Actually Needs

Here’s a structured and sustainable approach to reshaping FP&A in the age of cloud and AI.

1. Define Your Required Outcomes

Start with the business value:

• What decisions do we need to support?

• What planning cadence is right—quarterly, monthly, rolling?

• What data really helps us run the business?

💡 AI Tip: Use AI copilots to rapidly prototype forecasts, sensitivity models, and visualizations based on historical data and emerging patterns.

2. What Does “Good” Look Like?

Don’t reinvent the wheel. Tap into real-world FP&A experiences:

• Join the UK&I SAP User Group, #GenerationCFO, or CIMA communities

• Learn what works and what doesn’t

• Borrow proven templates and tools

These peer networks offer faster, cheaper insights than hiring a Big 4 for every pain point.

3. Diagnose What’s Broken in Your FP&A Operating Model

Before you build new, snag what’s broken:

• Are forecasts owned or delegated?

• Are processes understood or tribal?

• Is data trusted or transformed in spreadsheets?

Document issues across people, process, tech, and data. Most FP&A pain traces back to an immature or poorly designed finance operating model.

4. Understand the Business Operations Behind the Numbers

Most finance teams don’t fully understand the cadence and upstream processes that generate their data.

Spend time with ops, sales, HR, and supply chain teams. Map the real-world processes behind each forecast variable.

💡 AI Tip: Use AI-driven process mining to expose bottlenecks, lag times, and data quality gaps that impact forecast accuracy.

5. The FP&A Playbook: Define the Target Operating Model

Use this equation:

FP&A Success = (Required Outcomes × Best Practices) ÷ Legacy Lessons × Tangible Business Benefits / TCO

Build a Day in the Life of FP&A playbook that:

• Maps each step in the planning cycle

• Clarifies business roles, service levels, and value outcomes

• Quantifies costs, cadence, and technology enablers

This becomes a core tool for business engagement and change management.

6. Embrace Kaizen: Small, Sustainable Change Beats Big Bang Projects

Big-bang transformations often stall. Instead:

• Go #Agile

• Go #Kaizen

• Deliver change in bite-sized sprints

This lets finance refine models, fix data, and test new analytics while continuing business as usual.

💡 AI Tip: AI tools can simulate different sprint outcomes and even recommend backlog prioritization based on effort and impact.

7. Be Smart with Analytics Tools—Avoid Tech Bloat

Don’t rush to buy a new BI platform or data lake because a salesperson says you need one.

Instead:

• Sweat your existing reporting and data tech stack

• Use Digital Upcycling to extend what’s already working

• Fix the data model first, not the reporting layer

💡 AI Tip: AI-enhanced tools can now automate anomaly detection, suggest data enrichments, and reduce the need for manual data transformations.

8. Build a Sustainable Superuser / Citizen Developer Model

Good FP&A must scale. Create a super user network and COE model so that:

• Finance teams can build their own scenarios

• Tools are templated and governed

• Training is internal, not outsourced

This cuts costs, increases adoption, and ensures business ownership.

9. Digital CFOs Must Own the FP&A Transformation

Today’s CFO is more than a finance lead—they're the enterprise orchestrator.

“£2 out of every £3 invested in digital and AI transformation is wasted.” – World Economic Forum

The FP&A transformation is a test case for how to do digital right.

The CFO must own:

• Requirement gathering

• Benefit mining

• Design–build–test cycles

• Governance, documentation, and training

Show the organisation what great transformation looks like—starting with FP&A.

Conclusion: Keep FP&A Simple, Outcome-Focused, and Agile

Great FP&A isn’t about flashy dashboards or shiny new tools. It’s about:

✅ Clear outcomes
✅ Clean, trusted data
✅ A fit-for-purpose operating model
✅ Continuous, AI-enhanced improvement

Deliver it in sprints. Show value early. Then scale.

Let’s Talk—No Buzzwords, Just Coffee

If you’re considering a reboot of your FP&A function or finance operating model, I’d love to help you explore the options.

No sales pitch. Just practical advice over a coffee and a chat.

Alisdair
alisdairbach@dragonerp.co.uk