Forecasting is aided by AI tools that learn from a broad set of datasources

Description

AI-aided forecasting in Corporate Performance Management (CPM) Software entails the use of Artificial Intelligence tools to predict future business trends based on a comprehensive set of datasources. This functionality augments traditional forecasting methods by intelligently analyzing data patterns and learning from them to significantly improve prediction accuracy.

Example Use Case

Scenario: A mid-sized enterprise in the retail sector uses CPM software for its business planning. It seeks to leverage AI tools integrated within the software to produce forecasts based on data from a wide array of sources including sales history data, current inventory, market trends, customer behavior, and other external factors.

Solution: The AI-powered forecasting tool ingests and analyses all available data, identifying patterns and correlations that may not be immediately evident to human analysts. The software then uses this learned insight to generate accurate forecasts for future sales, inventory needs, and market trends. Such improved forecasting capabilities lead to better strategic planning and decision-making.

Considerations

The market includes several tools claiming AI forecasting abilities - however, their actual capabilities vary widely. Some analyze data in your model only, similar to a traditional predictive analytics methods. We've heard salespeople and marketing teams talk all day long about their AI initiatives, which, in the end are simply the same ARIMA models we've had since SPSS was invented.

True machine learning requires a lot of data, and a lot of power. There are tools on the market that are analyzing broader market trends by learning from various sources on the internet and distilling those down to something that matters for your industry. This final result may be something as simple as a growth driver - which is still incredibly valuable.

Dig in on this to make sure it provides true machine learning instead of just statistical methods.

Questions to Ask a Vendor

• Machine Learning: What is the data set that your AI is deriving its ability to predict outcomes from?
• AI Outputs: What does the AI output? Do we get monthly predictions, a simple growth driver, or anything else?
• Proof Points: Have your customers been able to validate actual results against your AI predictions to confirm accuracy?
• Learning Frequency: How often does your AI refresh its capabilities with new data?
• Text Commentary: Is the AI able to output written analysis of our forecast and provide reasoning to its predictions?