Demystifying intelligent forecasting

Tangible steps to get started on the road to more dynamic and valuable forecasts

Enterprise planning initiatives often feel like the business world’s version of a New Year’s fitness resolution: You know you want to get your forecasts in better shape, but you don’t know where to start.

AI, machine learning, better algorithms, predictive analysis, more automation, and data—lots of data. It all sounds great, but it also sounds like a pretty massive workout for the whole enterprise…eh, maybe next year (sound familiar?).

The truth is, implementing intelligent forecasting is much more accessible than many business leaders realize, especially when you cut through the jargon and understand rapid, sustainable results can be obtained with a step-by-step approach.

And, with every journey—whether it be fitness or intelligent forecasting, it begins with that first step—one that can produce real results quickly and have long-term staying power. What other workout can say that?

Data and technology: Our step-by-step approach

We take a look at these categories and help your company determine where to start and where you can go to succeed.


01. Predictive models


02. Data and signals


03. Visualizations and user interface


04. Data integrations

Learn how to take the first step to implementing and using intelligent forecasting.

Contact us

Brett Benner

Brett Benner

Partner, Finance Transformation, KPMG US

+1 267-256-2959
Peter Irwin

Peter Irwin

Principal, Lighthouse Data Analytics & AI, KPMG US

+1 212-872-7805
Upendra Kendurkar

Upendra Kendurkar

Director, Analytics Consultant, KPMG US

+1 469-288-6186
Colleen Schohl

Colleen Schohl

Director, Finance Transformation, KPMG US

+1 440-655-6258
Shehtaaz Zaman

Shehtaaz Zaman

Managing Director, Advisory, Finance Transformation, KPMG US

+1 212 954 6295