“Go to the cloud” has been a key building block in every global CIO’s digital strategy. However, as the CFO, do you find yourself getting into frequent arguments with them over the savings promised at the time of embarking on this journey?

Many of us have heard about promise of predictive analytics (PA) in machine learning (ML). Over 50% of organisations think that data science and ML are critical for success. At the same time, less than 20% of finance teams are deploying data science today. Why did this happen?

FP&A helps create sources of future value whilst being on top of how much value is being created at present. Neither of these two things is as easy to measure at any one point in time. So, how can we answer the question “is FP&A delivering what is expected of it”?

The way a company FP&A suite is organised (i.e. its setup) covers the way data are organised and analysed, the way the reporting and the forecasting are produced and performances are measured. What will qualify as the best FP&A set up? How will it be accepted by the company?

The role of FP&A is becoming more important than ever. FP&A is seen as instrumental in helping organisation formulate strategy and drive performance. However, how does FP&A function go about building its brand?

Without a doubt, the effects of AI on the global economy are jaw-dropping. But how does that affect the FP&A sector? Do we need to worry about the rise of artificial intelligence?