In the first FP&A Board Connect, Takeshi Murakami, Business Manager to CEO/President at Microsoft Japan, a speaker of the second Tokyo FP&A Board, explains how Microsoft achieved remarkable results by using predictive analytics and machine learning in FP&A.

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?

At the fifth Committee meeting, Kevin McConnell, Intelligent Technologies Solution Strategy at SAP, shared an interesting presentation about using Machine Learning for better results in FP&A. In the video, Kevin talks about the evolution of Machine Learning and how machine learning automation works.

At the third meeting of the AI/ML FP&A Committee, Xena Ugrinsky, Principal and Founder at GenreX, talked about the future of FP&A and some ways of incorporating AI into the financial forecasting process. Also, Xena provided an example explaining how Stanley Black & Decker improved financial forecasting by 60%.

In this video, Stefan Spiegel, CFO at Swiss Railway Freight Logistics (SBB Cargo AG), talks about the program that they used in SBB Cargo to replace management accounting. Instead of using a classical cost-accounting system, SBB Cargo switched to Intelligent business simulation engine.

At the fifth AI/ML FP&A Committee meeting, Igor Panivko, FD & MD at Konica Minolta, talked about dynamic and interactive Sales Planning based on the algorithmic model. He shared his experience in harnessing data in FP&A and how the company tried to solve some of the challenges which are typical for the finance function.