5 Reasons AI and machine learning can help FP&A

Automated forecasting capabilities will enable faster iterations, allow us to run multiple scenarios, develop ranges of outcomes, and do sensitivity analyses.Traditionally, these exercises required substantial iterative cycles and were very manual. This could mean reducing the budgeting and forecasting cycle from three months to three weeks, and even to three days.         

It is no secret that traditional forecasting is excessively manual and really prone to human biases.?

In recent years, there has been a shift away from traditional forecasting. This shift is driven by advances in technology and data science. The newer methods are more accurate, and they provide greater insights into the future.

How can AI and machine learning help improve FP&A?

1. Improving Forecast Accuracy: AI and machine learning can address most complex forecasting situations across various business segments and geographies.?They can enable the organization to customize their datasets and use driver-based self-learning models. This can improve both consistency and accuracy.?Finance teams can flexibly leverage internal and external data. Be better positioned and more accurate in their forecasts.
2. Reduce Cycle Times: Artificial intelligence and machine learning tools can significantly improve cycle times. The automated forecasting and update capabilities enable faster iterations, run multiple scenarios, develop ranges of outcomes, and do sensitivity analyses. Traditionally, these exercises required substantial iterative cycles and were very manual. This could mean reducing the budgeting and forecasting cycle from three months to three weeks, and even to three days.

3. Provide Valuable Insights: AIML can give businesses the ability?to discover and optimize new data patterns. Develop powerful business insights from the stockpile of data available.

4. Real Time Scenario Planning and Sensitivity Analysis: Scenarios are a huge part of the financial plan. Being able to run them in parallel and being able to forecast across all of them will be reality. Looking at the sensitivities, seeing what deviations we see between different scenarios will be key.?

5. Freeing up Time for Business Partnering: Time is money. Freeing up time is valuable. AIML can help do just that. By automating most of the tasks that would normally fall on the finance department. It can free up time so FP&A can focus on more value-adding activities like business partnering.

In conclusion, AI and machine learning technologies have been a catalyst that has forced organizations to relook at how they make decisions, the pace of which they make decisions, and the data they use to make those decisions.?

If you would like to learn more about FP&A, do consider checking out the?13-week FP&A Master class.

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