Arguably, the ability of FP&A professionals to make enhanced contributions is substantially impacted by the quality of tools provided to them.
It’s all Business Information
Rather than getting hung up on semantic debates, business intelligence (BI) can be defined as the use of business information (processed data) and business analyses to support business decisions in the context of core business processes that drive profit and performance. Typical BI applications – all of which leverage business data – include:
- Reports: Standard, pre-formatted information for backward-looking analysis of business trends, events and performance results.
- Multi-dimensional analyses: Applications that leverage a common database of trusted business information and fully automate information ‘slicing and dicing’, for analysis of the underlying drivers of business events, trends and performance results.
- Scorecards and dashboards: Convenient forms of multi-dimensional analyses that are common across an organisation, enabling rapid evaluation of business trends, events, and performance results and facilitating use of a common management framework and vocabulary for measuring, monitoring, and improving business performance.
- Advanced analytics: Automated applications that distil historical business information so that past business trends, events, and results can be summarised and described via well-known and long-used statistical methods.
- Predictive analytics: Automated applications that leverage historical business information, descriptive statistics, and/or stated business assumptions to predict or simulate future business outcomes.
- Alerts: Automated process control applications that analyse performance variables, compare results to a standard, and report variances outside defined performance thresholds.
Ultimately, all of these forms of BI deliver business information for decision-makers to use to understand past performance and its root causes, model various courses of actions, predict future results, and make decisions that are informed by underlying data. Simply put, BI is about leveraging business information to drive business results.
BI for FP&A
The role of the FP&A professional encompasses such activities as planning, forecasting, budgeting, controlling, variance analysis, scenario analysis, communicating goals and results, and decision support. These activities are tools that support the broader FP&A role, which is increasingly focused on the reduction of resource waste in business processes and creation of business value through effective resource utilisation.
What this translates to is that FP&A professionals need to provide relevant information to the executives and managers who make the decisions that have the highest impact on business results. This is consistent with the traditional role of management accountants, whose efficacy has been hampered to a meaningful degree by the lack of fully-automated access to high quality business information and the lack of advanced tools for analysing such information.
While spreadsheets have been a huge advance and will continue to be a mainstay tool in the FP&A toolkit, modern BI and analytics represent the next generation of FP&A tools. Below are two high-level examples of how BI can augment and accelerate the FP&A contribution to business results:
- Common, standardised business information for planning, forecasting, budgeting, modelling, and scenario analysis: Done well, BI is based on an underlying data warehouse and/or data mart, and thus it delivers common multi-dimensional views of business trends, events, and performance. Planning, forecasting, and budgeting almost always start by looking at what has happened in the past to derive assumptions about the future. BI eliminates much of the arduous data discovery work needed to develop and justify those assumptions. The same underlying data is also an input to models and scenario analyses, which basically predict and evaluate what might happen in the future under various assumed conditions.
- Standard scorecards and dashboards for variance analysis, performance control, and communicating strategic and operational results: Companies today often spend considerable manual effort to generate monthly scorecards and dashboards by extracting bits of information a piece at a time from standard reports or report data files, dropping the information into spreadsheets, and then copying the spreadsheets into presentation decks for upper management. One study revealed than many companies invest over US$100,000 per year in labour costs to produce such manual scorecards and dashboards. BI automates such work, and it provides a robust platform for drilling down to root causes of variances.
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