The Financial Planning and Analysis (FP&A) function plays a crucial role in companies by performing budgeting, forecasting, and analysis to support major business decisions. According to Gartner, FP&A is a set of four activities that support an organisation's financial health: planning and budgeting, integrated financial planning, management, and performance reporting, and forecasting and modelling [Gartner, 2021]. The FP&A solutions enhance the finance department's ability to manage performance by linking strategy to execution; by assessing the budget and forecast against the actual financial performance. In other words, FP&A helps to effectively manage cash flow, makes the best use of capital, and facilitates planning and controlling of budgets to ensure the organisation's strategic goals are accomplished.
However, we are today in the digital world where organisations in every industry sector are looking to leverage their enterprise data to enhance business performance. In this backdrop, how can the FP&A teams adopt relevant solutions to improve the accuracy and reliability of plans and forecasts and speed up decision-making? While a reliable FP&A function relies on a solid business strategy and a sound financial acumen, at the execution level, the future of FP&A depends on three key building blocks: Digital, Data and Analytics. What are these building blocks and why do they matter from the FP&A perspectives?
Today, every organisation aspires to be a digital enterprise. But what is digital? According to Mckinsey consulting, digital is re-examining the way of doing business and understanding where the new frontiers of value are. For some companies, digital is capturing new frontiers and developing new business models in adjacent categories; for others, digital is identifying and going after new value pools in existing sectors [Mckinsey, 2015]. Specifically, digital is the convergence of internet technologies such as IoT (Internet of Things), social media, mobile, cloud, Artificial Intelligence (AI) and more to create a personalised and connected enterprise. Commonly associated with Enterprise 4.0 i.e., the new stage in industrialisation, Digital FP&A is about managing businesses in a secure, flexible, fast, consistent and reusable format. This digital format helps to increase the efficiency of both discrete and time-sensitive based business processes and activities.
Advancement in digital capture technologies and reduced cost in data storage and processing has enabled companies to efficiently capture both structured data (in Excel files or SQL databases.) and unstructured data (like text, audio, video, and images). However, just capturing and storing data doesn’t make the FP&A function data-driven. Specifically, the FP&A data that is captured should:
- Be aligned to the business purpose i.e., business data should be captured for operations, compliance, and decision making;
- Be structured by aligning to the right data type (nominal, ordinal and numeric). Structured data adhere to a pre-defined data model and is, therefore, easier to process and analyse;
- Have low variation or spread in the data. Low variance means the data set is tightly clustered together.
With quality data, the FP&A team can perform the right analytics and derive insights continuously and dynamically. Traditionally the FP&A team has focused on the analysis of historical performance such as cash flow, variance analysis, ratio analysis to name a few. They have not leveraged advanced analytics techniques such as predictive analytics, machine learning, prescriptive analytics, cognitive analytics, text mining, sentiment analysis, neural networks, cluster analysis and more. Making decisions only with historical performance is like driving a car using just the rear-view mirror. To prepare the organisation for the future, FP&A should be based on predictive analytics (analyst based and machine learning) and prescriptive analytics (optimisation and sensitivity analysis) [Southekal, 2020].
So, how does the new Digital FP&A look? What are the Digital FP&A use cases? Traditional FP&A models are often based on static, historical, and fragmented data that do not support high-quality insights, unlike rolling forecasting which predicts the performance continuously over a time period. Another use case is to move away from traditional manual compliance to regulations to automated rules-based compliance leveraging tools such as RPA (Robotic Process Automation).
Being relevant in today’s digital age is making decisions, based on insights from data and analytics. In today’s fast-paced business environment, the role of FP&A is evolving quickly, and many organisations are investing significantly in the FP&A function to derive business value. Today Digital, Data and Analytics in FP&A is an important enabler in achieving process and regulatory transparency with insights, fostering better decisions, and ultimately unlocking the business value.
- Gartner, “Financial Planning and Analysis (FP&A)”, 2021
- Mckinsey, “What ‘digital’ really means”, Mckinsey Digital, 2015
- Southekal, Prashanth, “Analytics Best Practices”, Technics, 2020