In this blog I take a broader view of new products and talk about how best to monitor progress post-launch when information is still a little sketchy, volumes are still very low and reporting mechanisms may not yet be fully in place.

Scenario analysis, sensitivity analysis and what-if analysis are very similar concepts and are really only slight variations of the same thing. All are very important components of financial modelling – in fact, being able to run sensitivities, scenarios and what-if analysis is often the whole reason the model was built in the first place.

Is your most fancied FP&A RPA initiative not delivering the anticipated benefits? You are not alone. So, what are the most common pitfalls? And more importantly, how can you sidestep them and increase your odds of a successful RPA implementation?

Ask anyone working in the finance field now, how much time you consume in some manual tasks; such as data entry, accumulation & validation of data, accounts reconciliation & preparing some basic statements or reports. Unfortunately, statistics say that more than 35% from Accounting & Finance Teams spent from 50 to 70% from their time on manual processes & data entry on ERP systems!

Digital transformation has created new opportunities. It's possible to generate insight from more sources of data, faster than ever before. But technological advances have also increased competitive pressure. How can FP&A teams adapt to these challenges and redefine their role in modern business? How can FP&A remain relevant in an organisation where everyone is an analyst?

The crux of the analytics movement is making better decisions and more organizations are moving towards a data-driven culture, but only about a third of organizations surveyed said they would describe their current culture as data-driven. So, where is the disconnect?