How far can you go with improving your FP&A practices? This article reveals relationship between three...
Data-driven FP&A: the tip of the iceberg
In Part 1 of the series ‘FP&A and the three-headed serpent‘, you got acquainted with the ‘data – business planning – tools & techniques’ model, which is the basis for FP&A practices. The combination of words ‘data-driven’ seems to imply that you should start with data, and to some extent this is true.
As an FP&A professional, you deal with data that is being delivered to you by various business stakeholders. Your data travels a long way from its source through applications to your reporting system.
The data you deal with is the tip of the iceberg. The major part of data processing is the part that is hidden beneath the water. And this is also the place of origin of all the data quality issues.
You do not have much influence on this hidden part. This part of the iceberg is out of your area of accountability. Unfortunately, this is the most important part of making a business data-driven. This dilemma is similar to the ‘chicken or the egg’ dilemma: which one was there first, and where do you start? You want to make data manageable and should become a sponsor of this idea within your company, but you know it cannot happen overnight. There is a long way to go before your company can achieve this goal.
Define who really needs which data
As an FP&A professional, you have probably built a strong business partnership with top and operational management.
Insight 2 from the global FP&A research stipulates that FP&A Teams aspire to be more strategic, quote: ‘Companies are wasting valuable analytical talent on low-value adding activities such as data reconciliation, data cleansing, reporting reconciliation etc.’.
Very often, FP&A staff simply delivers standard reports to their main stakeholders with a certain frequency. The first step for you is simply checking whether all reports you deliver are really necessary. Reports themselves are simply containers of information. The second step is specifying the data needs and requirements of your main stakeholders. These requirements may include critical information needed for decision making, the frequency of report delivery, or how they are to be delivered.