Driver-Based Planning is a powerful approach that helps companies plan better by focusing on key business drivers, or in other words, key performance indicators (KPIs) that can impact the business.

While companies usually use high-level assumptions for their strategic plan, they can use more specific KPIs for Driver-Based Planning in their operational plans.

There are already a lot of articles and studies on how to implement a driver-based plan. This article focuses on the post-planning stages and the challenges that arise at this point. More specifically, the difficulty experienced in identifying key business drivers after company functions have started to build the initiatives that support the business plan.

Another challenging area that has often been overlooked is how the driver-based approach can effectively extend into actual operations after the planning is done. Once the company has identified the KPIs it will use for planning, it goes into an elaborate planning cycle. The cycle includes aligning assumptions, analysing data, and creating a good plan using those inputs. While many companies can track and compare the drivers versus the plan within dashboards and reporting tools, the challenge is translating the impact of business activities or initiatives devised after the planning cycle.

The Main Challenge with Linking Functional Initiatives to a Driver-Based Plan 

To illustrate the problem, let us take a consumer goods company’s revenue line and apply a Driver-Based Planning approach. 

The immediate drivers at the most simplistic level of revenue are the average selling price and the number of customers. If we focus on the number of customers in this example, we can further identify the quantity drivers as: 

• Number of customers = New customers acquired + Existing customers

Normally, during the initial planning, the company identifies new customers and existing customers as two main drivers but does not dive further into this detail. However, as the company operationalises the plan, the different functions start programs and initiatives to drive results. The marketing team, for example, may want to define these categories further when working on the initiatives. As an illustration, the marketing team may break new customers down further. 

• New customers acquired = Social media sourced + traditional media sourced + walk-in

The management team then look at the business as usual (BAU) activities, choose to continue activities that will improve the new customer acquisition metric and create various dashboards to measure the effort versus plan.

However, the teams may come up with new initiatives that are not BAU for the business. For example, seasonal drives or one-off investments. The reporting then becomes more ad-hoc, and in many cases, data is captured through manual reports like spreadsheets, making the overall reporting cycle more tedious and prone to errors.

This situation is further complicated when different functions start to individually identify BAU and initiatives that are unique to their operations. For example, marketing can focus on social media while deploying tools like online marketing banners, keyword optimisation and SEO. In contrast, the sales team may drive new customers through channel expansion. 

One single driver may expand out to multiple sub-drivers, and different functions may end up being responsible for various sub-drivers. It means that reports may miss some of these activities or fail to consolidate all the applicable ones.

As part of the feedback loop, the FP&A team can play an important part in helping the business identify, analyse, and report all these activities. This will provide management with an accurate and comprehensive view. 

To do this, FP&A need to work with the various functions and implement a three-step approach.

1. Qualify the activities. Once the business identifies the drivers to focus on, FP&A can start identifying and categorising the relevant BAU activities that can help improve the business drivers. As the functions come up with different ad-hoc initiatives, the FP&A team must be involved in determining whether those ad-hoc initiatives qualify as legitimate initiatives that will improve a particular KPI. The work includes a review of the initiative, identification of the parameters, and a definition of the measurements involved. By engaging FP&A early on in this process, the business or function can avoid later disagreements on the effectiveness of each initiative.
2. Track and proactively review the activities. While most BAU activities are more established, ad-hoc activities may require the business function to tweak and review initiatives in order to work out if they are performing. The FP&A team can proactively help with this, as they can provide data and analysis to support the team.
3. Consolidate and report. As mentioned above, FP&A plays an important part in any initiatives’ consolidation and reporting process since different functions will work in isolation on their respective initiatives. At the same time, FP&A will present a high-level view to management in order to advise them on the overall effectiveness of each activity and determine whether the driver focus is improving results.

The Role of Technology: Ways to Improve the Driver-Based Planning Process

As the Driver-Based Planning process moves from strategic to operational, the amount and diversity of data required for analysis and reporting increase significantly. 

From a practitioner’s standpoint, implementing the framework to identify and track ad-hoc initiatives may be easier said than done. Especially when it comes to identifying parameters and their relationship to the drivers. However, FP&A can leverage technologies in three areas.

1. Data warehouse and finance system. Improving this system will make it easier for FP&A professionals to collect and categorise data. FP&A professionals today need to work with multiple data sources, not limited to only financial data. The FP&A team can now provide a more comprehensive analysis by leveraging different data sources, such as customer and marketing data from their respective channels.
2. Artificial Intelligence (AI)/Machine Learning (ML). FP&A can take advantage of the latest improvements in AI/ML. It is important to use AI/ML tools to help identify the related data sets and apply them to the required analysis. 
3. Dashboards. There are ways to improve dashboards to include relevant analysis and collate and present data in more user-friendly reports for the whole organisation. This can reduce reliance on spreadsheets and save time in report preparation.

Conclusion

In conclusion, the Driver-Based Planning approach effectively allows companies to identify their most important areas. However, challenges in the post-planning part of the cycle can be mitigated with the FP&A team’s involvement. This includes helping identify specific business activities in the data that will help measure them.

While this may have been difficult in the past when data and analysis were less accessible, the latest improvements in technology now provide companies with much better insight. AI/ML and better data handling technologies, data warehouses, improved financial systems, and dashboards make this process much simpler.

This article was first published in the SAP blog.