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.

The New Normal means that planning is no longer an extrapolation of the past. Similarly, business drivers that worked last year may no longer be relevant for the future. The reality is that organizations face multiple possible futures. Each one can be triggered by a crisis or an unforeseen event that will require the company to adjust or even change course.

So how should FP&A adapt to this New Normal?

Today’s uncertain times mean that it is no longer good enough for organizations to have one fixed plan and forecast. Historic data by itself cannot help predict the future, nor can classical planning methods and standard variance analysis provide sufficient information to manage a business. It is time to change and adopt a fact-based mindset towards business decisions.

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.

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