As the year progresses, FP&A teams begin to take PTOs to take a much-needed break before the busy budget season begins. Budgeting is a time-consuming procedure that lasts 2-4 months each year. It begins with the sales budget, then moves on to the operational budget, and lastly to the P&L forecast.

A budget takes high-level goals (revenue, profit growth, etc.) and turns them into a workable plan by allocating resources. The traditional bottoms-up approach has its own set of restrictions.

The budgeting process requires a large amount of time and effort, which causes finance teams to lose sight of strategic projects. This is where artificial intelligence (A.I.) can help. Though artificial intelligence (AI) cannot replace traditional bottom-up budgeting, it can assist teams in becoming more productive.

For forecasting, FP&A teams in several firms have used A.I./Machine learning algorithms. However, because of  lack of finances, time, and technological knowledge, just a few organizations have used them in budgeting.

How AI/ML can aid budgeting: 

  • Traditional budgeting does not generate data at the same granularity as actuals. Artificial intelligence, on the other hand, can make granular forecasts.
  • Based on historical run rates, AI makes it simple to incorporate organizational goals into operational expenses.
  • It also simplifies the calculation of business drivers and their econometric impact on various P&L components. 
  • AI can generate several scenarios in a fraction of the time.
  • AI can assist with budget validation and anomaly detection. This saves time for the teams and aids in business partnering.

Budget time is the most stressful time of the year -Allison Johnson, FP&A Manager

Points to Consider:

  • In time series modeling, the forecast horizon specifies the projected time frame. The prediction horizon for budgeting should be 12 months, whether you utilize traditional machine learning models or products like However, most budgets are created in September or October, when there are still a few months left in the year. As a result, choose a forecast horizon of 15 to 16 months.
  • FP&A team should feed data points on market circumstances, competition, and organizational changes to AI models to generate accurate data.

If you’d like to learn more about incorporating AI into your budgeting and forecasting, feel free to send us an email

 How can we leverage all the data points we have in our budget preparation




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