FP&Ai Podcast: Ep 4 : Driver Base Planning Part 2
Driver based planning only works when it is built on the few levers that truly move results. In Episode 4, Roger Knocker and Anthony Wilson continue the series on budgeting, forecasting and planning with practical examples you can apply now.
What we cover:
- Subscription revenue drivers: additions, cancellations, cohorts and churn
- Scenario analysis that links revenue, labour, materials and overheads to gross margin
- Event based cash flow planning that ties invoices, terms and timing to bank movements
- How to pick the right drivers and keep the model simple enough to use every month
If you want a plan that adapts as fast as the market changes, this episode is for you.
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Conversation Highlights:
[00:01] Anthony Wilson demonstrates practical examples of driver-based planning across business types, starting with subscription-based revenue. He explains that tracking new contract additions and cancellations helps forecast revenue, calculate churn, and monitor customer retention.
[00:20] By modeling these drivers, businesses can adjust assumptions such as price or volume and immediately see the impact on revenue projections.
[00:36] Anthony introduces scenario analysis as an extension of driver-based planning. Using key variables—revenue, direct labor, materials, and manufacturing overhead—he shows how different growth or cost scenarios can be tested to measure their effect on gross margin.
[00:57] He emphasizes that driver-based models allow rapid reforecasting when business conditions change, making them suitable for dynamic planning rather than static annual budgets.
[01:15] Anthony highlights how cash flow forecasting benefits from a driver-based approach. By tracking payment timings, customer terms, and invoice schedules, companies can better project liquidity.
[01:38] Implementing this in a system rather than spreadsheets allows aggregation across divisions, supports multi-region or multinational operations, and improves treasury management through automation.
[02:00] The conversation shifts to identifying the most impactful business drivers. Anthony explains that analyzing historical data and cause-and-effect relationships reveals how sales, costs, and operational activities correlate.
[02:27] He recommends frameworks such as a balanced scorecard to align financial and operational metrics, identifying both financial drivers (e.g., gross profit percentage, net margin) and operational drivers (e.g., volume, machine hours).
[02:55] Roger Knocker reinforces the importance of historical data, advising against including too many variables. Focus should be on a few material drivers that truly influence profitability, simplifying modeling and improving accuracy.
[03:15] Anthony stresses cross-functional workshops between FP&A teams and business units to ensure models reflect real-world operations and show how actions in one area affect financial outcomes.
[03:38] Roger adds that FP&A professionals must confidently represent efficiency, profitability, and cash flow, complementing operational teams focused on quality and service.
[03:58] Before using a new model, Anthony advises validating it by running retrospective scenarios—forecasting past months using driver-based assumptions and comparing to actual results—to refine accuracy and build confidence.
[04:18] Finally, Anthony emphasizes the importance of business intelligence tools for aggregating and analyzing data, as well as AI and machine learning to detect patterns in large datasets.
[04:40] He notes that as data volumes grow, these tools are essential for modern FP&A functions to deliver real-time, insight-driven decision support.
