From data to decisions: How financial models drive scenario planning

In an increasingly data-driven world, businesses face immense pressure to make informed decisions that mitigate risk and maximise opportunity. 

Financial models act as powerful tools to navigate uncertainty, providing clarity through scenario planning. Tim Linke, National Financial Modelling Lead at RSM, discusses the value of financial models in planning, forecasting, and supporting better decision-making. 

The power of practice: Building financial modelling skills 

Becoming proficient in financial modelling takes time and practice. “It’s about learning by doing,” Tim explains. “Building models require scar tissue—those late nights and stubborn errors that teach you the hard way. That said, working with experienced teams and mentors accelerates that process (…and saves you some of the pain along the way…).” 

For those serious about developing their skills, Tim recommends exploring structured certifications like those offered by the Financial Modeling Institute (FMI). These globally recognised programs help professionals refine their abilities and build a solid foundation in best practices. 

How do you improve an existing financial model?

Financial models often start with the best intentions but can become overly complex. “Step back and assess the critical path and associated logic flow,” Tim advises. “Map out the structure on paper or a whiteboard and identify pain points or unnecessary complexity.” 

Models must be transparent and user-friendly. Collaborating with stakeholders during development—breaking it into digestible parts and sharing digestible components regularly — helps ensure the final product aligns with business needs and is easy to navigate. “Anyone in my team will tell you how much I love a whiteboard. It’s about creating clarity, not clutter,” Tim adds. 

From planning to forecasting: Building scenarios that matter 

Financial models serve as the bridge between planning and forecasting. Tim explains, “Planning sets the business goals, whereas forecasting quantifies what achieving those goals looks like. The two processes are interdependent.” 

Scenario planning allows businesses to test assumptions and explore outcomes. For example: 

• What happens if sales decrease by 10%?
• How does an interest rate change impact cash flow?
• What additional funding is needed if costs rise unexpectedly? 

The ability to adjust inputs quickly and reflect changes in real-time is crucial. “Models need to be dynamic, enabling businesses to stress-test plans and identify risks before they arise,” Tim says. 

Simplicity and transparency in modelling 

A major challenge in financial modelling lies in striking the balance between detail and usability. “A model shouldn’t try to do everything,” Tim notes. “Understand the purpose and create a tool that answers specific business questions without becoming a black box of complexity.” 

Transparent models provide confidence. Key practices include: 

• Using clear, simple formulas.
• Separating inputs, calculations, and outputs for better traceability.
• Avoiding unnecessary complexity or hidden hard-coded values.
• When stakeholders can understand and trust the logic, they’re more likely to rely on the insights for decision-making.

Combining data analytics with financial knowledge

Financial modelling and data analytics often overlap, requiring professionals to bridge technical analysis with strategic storytelling. “The challenge is taking complex data and transforming it into actionable insights,” Tim explains. 

Good financial modellers not only build robust tools but also communicate findings effectively. “It’s about presenting the financial data in a way that tells a compelling story and informs decision-makers. A great model is only valuable if the insights it provides can be understood and acted upon.” 

Analysing models you didn’t build: Navigating the unknown

Reviewing a financial model built by someone else can be daunting. Tim recommends a methodical approach: 

• Trace the logic: Follow outputs back to calculations and source inputs.
• Check formula consistency: Use tools to identify inconsistencies or hard-coded values.
• Test assumptions: Adjust key variables to ensure the model behaves as expected. 

“Treat it like a scientific experiment,” Tim advises. “Craft a hypothesis, test it, and use that as a way to verify that the model reflects the business logic accurately.” 

Financial modelling: A tool for problem-solving 

Financial modelling is more than crunching numbers—it’s about solving problems. “Every business needs a model, whether simple or complex, to plan for the future and assess risks,” Tim says. From infrastructure projects to cash flow forecasting, financial models help businesses make confident decisions in uncertain environments. 

Drive better decisions with scenario planning 

At RSM, we specialise in creating tailored financial models that help businesses plan, forecast, and explore multiple scenarios effectively. Learn more about our financial modelling services and discover how we can help your business turn data into decisions. 

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Contact your local RSM office to find out more about financial models.