We are excited to share with you the results of the third annual FP&A Trends Survey! The research is based on insights from 338 finance professionals across a diverse set of industries around the globe. We focused our attention on the changing role of FP&A into a strategic partner and how technology can support this evolution.
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By deploying integrated FP&A organisations see greater performance improvements compared with traditional FP&A processes. This is enabled by combining strategic planning, business planning and forecasting and operations planning and forecasting.
FP&A is going to thrive and evolve if it continues to enhance the decision-making process in an uncertain business environment. This is why we need to see a huge shift in the FP&A skill set.
What is systems thinking and how can it be applied in a real-life finance business partnering scenario? A modern finance business partner requires a shift in mindset away from linear to more of interconnectedness.
The modern Financial Planning and Analysis (FP&A) function has an important role to play in enhancing decisions through the power of predictive analytics and driver-based modelling.
Currently artificial intelligence (AI) and machine learning (ML) is havi. In terms of accounting and finance, is AI & ML a gift or curse for us? The answer largely depends on two key variables.
How can we plan and forecast in the uncertain environment? One of the current challenges for FP&A professionals is that traditional planning methods are no longer sufficient for this turbulent period. This is where FP&A Scenario Planning comes into play.
With the help of modern technology, we will try to make this digital meeting as interactive as possible by incorporating panel discussion, polling questions, Q&A sessions, and a survey.
A proper financial model that provides quick answers to different changes will help you make your life in planning more successful.
There have been not many details about how to get started with a machine learning (ML) project in FP&A. This article will cover the financial forecasting process in companies and how ML can help with it.
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