The financial planning and analysis (FP&A) storyteller has emerged as one of the five critical roles within the FP&A function. In a data-driven world, the volume of data that exists is exponentially increasing. Equally, the time available for managers to process insights from this data is decreasing. Therefore, the requirement that these insights be taken and used to drive leadership decisions has never been greater.
To bring some perspective to this position of AI within the context of FP&A activities, the FP&A Trends Group recently conducted research examining how artificial intelligence (AI) and machine learning (ML) were being used within the profession. They carried out interviews with thought leaders and academic professionals and examined case studies of organizations that were using AI and ML successfully.
This paper is a result of that research, looking specifically at how, when combined with human intelligence, AI can transform the role of FP&A.
There has never been greater uncertainty and a faster pace of change than over the past months.
And yet, at a time that requires speed and agility, and in a function that needs these qualities more than others, we cleave to our traditional management accounting methods and adhere to our longstanding processes.
The financial numbers only show one side of the story. When FP&A professionals are presenting the complete story behind the numbers, soft data needs to be collected and incorporated. The big question is, what data and where is it?
Many Finance professionals have an incorrect perception of the word “insight” but here is a simple way to validate if you provide insight or “just” data. Ask yourself, what decision a business can make based on the data you have provided? Insight is something valuable and not yet known by the business, but when known the business uses it to make decisions that are data-driven.
The quality of a decision is a question about what data or lack of data the decisions are made on. So, let’s discuss what is a Data-Driven Decision and what is not, but also how do we make Fair Decisions.