How do you leverage AI and automation features in your rolling forecast software?

1 Streamline data collection and integration

One of the first steps in rolling forecasting is to collect and integrate data from various sources, such as accounting systems, CRM, ERP, and external market indicators. This can be a tedious and error-prone task, especially if you have to manually input or copy-paste data. AI and automation features in your rolling forecast software can simplify this process by automatically connecting to your data sources, extracting and transforming the relevant data, and loading it into your forecast model. This way, you can ensure data accuracy, consistency, and timeliness, and save hours of work.

2 Enhance scenario analysis and sensitivity testing

Another key benefit of rolling forecasting is that it allows you to explore different scenarios and test the sensitivity of your assumptions and drivers. This can help you identify risks and opportunities, and evaluate the impact of various actions and events on your financial outcomes. However, creating and comparing multiple scenarios can be complex and cumbersome, especially if you have to manually change the inputs and formulas in your model. AI and automation features in your rolling forecast software can make this easier by enabling you to create, modify, and run scenarios with a few clicks, and generate interactive dashboards and reports that show the results and variances. This way, you can quickly and easily analyze the implications of different situations, and make informed decisions.

3 Improve forecast accuracy and reliability

One of the main challenges of rolling forecasting is to ensure that your forecasts are accurate and reliable, and reflect the current and expected conditions of your business and market. This requires you to constantly monitor and update your assumptions and drivers, and adjust your forecast model accordingly. However, this can be difficult and subjective, especially if you have to rely on your intuition or historical trends. AI and automation features in your rolling forecast software can help you overcome this challenge by applying advanced algorithms and machine learning techniques to your data, and providing you with intelligent insights and recommendations. These features can help you identify patterns, trends, anomalies, and correlations in your data, and suggest the optimal values and ranges for your assumptions and drivers. They can also help you detect and correct errors, outliers, and biases in your data and model, and improve the quality and validity of your forecasts.

4 Automate workflow and collaboration

The final advantage of using AI and automation features in your rolling forecast software is that they can automate your workflow and collaboration, and make your rolling forecasting process more efficient and effective. These features can help you set up and schedule your forecast cycles, tasks, and deadlines, and send reminders and notifications to your team members and stakeholders. They can also help you share and communicate your forecast data, scenarios, and results with your team members and stakeholders, and enable them to access, review, comment, and approve your forecasts online. This way, you can streamline your rolling forecasting process, and ensure alignment and accountability across your organization.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?