The concepts of artificial intelligence (AI) and machine learning (ML) are not new. They are relatively new to Finance and FP&A leaders, and that means many may have an aversion to leaning more about and leveraging them in delivering value from FP&A.
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Spreadsheets are a great tool to build and maintain ad-hoc calculations, quickly draft a business plan and create good-looking reports. But when it comes to planning and budgeting in a complex business environment the flexibility of spreadsheets is often quick to become an obstacle instead of an asset in your planning process.
The Global Artificial Intelligence / Machine Learning FP&A Committee was created in March 2018 with the aim to see how the latest developments in those technologies can influence modern Financial Planning and Analytics. On the 14th of November, the Committee held its third meeting.
The 18th London FP&A Board gathered on 21 November 2017 to discuss FP&A Transformation through Organisational Structure.
On the 26th of June 2018, the London FP&A Board held its 20th meeting with an interesting debate on FP&A Team Building.
Disclaimer: Financial Modelling has no strict “right” or “wrong” method of application. It does, however, have forms of best practice and this what this article attempts to highlight
The fourth Zurich FP&A Board gathered on 5 October 2017 to discuss Rolling Forecast Philosophy.
The second Zurich FP&A Board gathered on 25 January 2017 to discuss FP&A Analytical Transformation.
Following on from the success of the 7th London FP&A Circle, I had the pleasure of attending the 21st London FP&A Board which shares the latest professional trends and developments with the UK FP&A community, open exclusively by invitation to senior finance practitioners.
Mature driver-based planning models are an essential component of effective rolling forecast processes in complex, global organizations. They provide the foundation for profitable growth by enabling strategy and cost structures to quickly self adjust to changing business objectives and market conditions.