Machine Learning & Analytics Accurately and Reliably Streamlining FP&A

Presented by: Linda Copeland, The Hackett Group

Historically, FP&A teams have faced significant challenges in producing robust financial analyses. One factor contributing to this issue has been the limited capacity of these teams, which can be traced back to inefficient financial planning processes. Overreliance on Excel, for instance, has often led to a lack of scalability, making it difficult to handle complex data sets and perform sophisticated analyses. As a result, FP&A professionals have struggled to deliver the deep insights and strategic recommendations that business leaders require to make informed decisions. 

The Hackett Group has successfully addressed this challenge by utilizing the advanced capabilities within Oracle's Financial Planning tool, which includes machine learning models and analytical bots. By leveraging these modern tools, financial planning teams can significantly reduce the time it takes to produce and analyze a financial plan. Machine learning models, in particular, can help automate many routine tasks and processes, freeing team members to focus on more strategic activities. Additionally, analytical bots can provide valuable insights and recommendations based on data analysis, enhancing the quality and accuracy of financial forecasts. 

During this webinar, we will cover the following topics:

Learning how FP&A teams can effectively utilize these financial cloud-based tools to enhance their financial planning and analysis capabilities
Leveraging these tools to analyze submitted plans quickly, identify potential risks, and implement best practices, such as rolling forecasts
Understanding how machine learning models and analytical bots can help streamline financial planning processes, improve accuracy and reliability, and ultimately drive better business outcomes