This world of “unknown unknowns” has greatly challenged forecasting models for all sorts of organisations — especially when predicting how the situation will evolve and what action is required to reach an acceptable state. 

Understanding new KPIs and drivers, their impact and how we can influence them has been a key priority for leading organisations. This, however, requires a good understanding and implementation of Driver Based Planning, coupled with key business strategies.

The Digital Central European FP&A Board examined why Driver Based Planning is key for the future of organisations.

FP&A Evolution: From Traditional to Digital

To introduce the subject, I took the members through the differences between Traditional Budgeting, Driver Based Planning models, and Driver Based Planning models with Predictive capability.

The Predictive Planning Maturity Model below shows the evolution of organisations. It spans from the very “basic” stage, where drivers are user-defined; to the stage where time series and other analyses are used to define drivers; to using Machine Learning and predictions; and finally, to the leading state, where drivers are user- and Machine Learning-defined using predictive analyses, and operational and financial plans are all linked and driver-based. 

Figure 1

Swarovski case study on Driver Based Planning

One such leading organisation in the field of Predictive Driver Based Planning is Swarovski. With an annual turnover of more than Euro 2.5bn and three very complicated business segments, Swarovski adopted Driver Based Planning as a key tool to stay ahead of the curve — especially in uncertain environments like nowadays.

Michael Nudelmann, Director of Controlling & Head of FP&A, took us through the complexities of Swarovski’s business and how their processes evolved. They moved from quarterly forecast to monthly two years Rolling Forecast, from bottom-up build to driver-based modelling using prediction and validation, and output at the store and consolidated level. The benefits were immense:

• Agility — ability to anticipate changes in trends

• Short-term focus but gaining a medium-term view

• Faster decision-making because of improved insights

• Deeper business understanding

• Considerably reduced manual effort in forecast build
• Precise steer and implication analysis
• Simple process ensuring enough granularity for decision-making and operational steering

The figure below demonstrates the details of their Net Sales Driver Based Predictive model:

Figure 2

For Michael, “Predictive Driver Based Planning matters for FP&A because it provides exponentially more insights with significantly lower time and effort.”

Connecting Stakeholder Management to Driver Based Planning

Rudie Van Dijk, Global Director FP&A at Tip Trailer Services, emphasised the importance of connecting Stakeholder Management to Driver Based Planning.

He explained what his organisation is doing to ensure they have the basic right to deal with uncertain environments. They have embarked on a finance digitisation roadmap where they are looking at standardisation, data, change, and integration of planning processes in their quest for world-class FP&A. There is a very high focus on enhanced IT capabilities in each step of their transformation.

Rudie stressed the importance of understanding your stakeholders and the KPIs that are used to track performance and stress testing. We need to ensure they are all linked from the very top with the strategic plans, through target setting, operational and financial plans to budget and forecast, and finally, to how they are reported and what actions are taken if there are any deviations to plans. Below are the key KPIs the organisation uses and how they track them all through.
 

Figure 3

Understand your stakeholders and the key drivers used to manage their expectations. Utilise this right from the beginning - from the strategic plan to target-setting to all plans and reporting. Remember that this is a continuous process whereby drivers must be reviewed on a timescale.

Mindset Change for better Driver Based Planning

So, what are the key skill sets to ensure we, as FP&A, are on top of this? Ronald Huaman Hilario, Head of Controlling at Minsur S.A. FP&A, needs a whole new mindset change, especially when it comes to dealing with uncertain environments and working with Driver-Based Planning models.

Over and above functional skills like accounting, controlling, statistics, IT, tax, and corporate finance, softer skills like curiosity, communication and strategic thinking are key!

During the pandemic, it was essential to think of impact and messages to the city of reducing KPIs and expectations. Instead, they promoted flexibility with “how might we” questions to ideate the right problem.

They levelled up their FPA professionals’ hunger for learning by presenting them with problems and encouraging them to work through solutions together. 

The key was also to ensure excellent communication and storytelling throughout the organisation.

For Michael Lengenfelder, Head of PF&A Product Management at Unit4, Strategic FP&A should be the starting point.
 

Figure 4

Think about these key actions:

1. Define your most important areas for planning/forecasting

2. Decide on the approach: value drivers vs AI vs both

3. Model the value drivers with business experts

4. Monitor the value drivers’ accuracy over time

5. Be prepared to adapt them over time

6. Link your value drivers back to your strategy 

7. Make use of the rich functionality that FP&A software brings to support your planning with value drivers

Summary 

This article and the case studies discussed show the importance of Predictive Driver Based Planning for FP&A and how organisations should implement it. It is of utmost importance that FP&A drives this agenda to ensure that, whatever happens in the future, we are prepared to run our models on an almost real-time basis and examine how our plans change and what actions we can take to mitigate the impact. This is achieved by having a real-time Predictive Driver-Based model with drivers that are reviewed and understood and derived via Machine Learning and external sources.
 

We would like to thank our global sponsor, Unit4, for their great support with this Digital FP&A Board.