3 Ways to answer “What’s Next” faster, by using AI in WebFOCUS

Get from “What happened” to “What’s next?” faster than ever

For years, business intelligence teams have been using analytics tools to get a clear answer to the question: “What happened?” This analysis of the past laid the crucial foundation for the work these teams would do to predict the future of the business and the larger industry as a whole. Essentially, these teams would answer the question of “What’s next?” based on the analytics tool’s finding of “What happened?” 

Today, the expectations around data analysis have changed drastically. In many organizations, teams far outside of business intelligence departments are expected to make predictions about the future and use those predictions to drive their business strategy. These teams often do not have deep data analysis training or experience. This means that it is not enough for the analytics tools we use to simply answer the question of “What happened?” Even for teams equipped with the training necessary to do this analysis, the expectation is for these teams to complete that analysis and subsequent predictions faster than ever before. For organizations to thrive in this current environment, the foundational question our tools must answer has shifted to: “What’s next?”

Rising to meet the occasion is the power of AI, and more specifically Machine Learning (ML) Functions. The power of ML functions is directly accessible within the ibi™ WebFOCUS® interface. Using AI in your environment gives your team the opportunity to transform your analytics tool from a rear-view mirror into a forward-looking GPS. 

Let’s dive into three key benefits of using ML functions in your WebFOCUS® environment and what this could mean for you and your team. 

1. Democratize predictive power for your business teams

Historically, ML functions have been the exclusive domain of data scientists. Business users had the questions, but the predictive answers were locked in complex models they couldn't access or use.

WebFOCUS breaks down that wall. With predictive functions built directly into the platform, a business user can apply sophisticated models without writing a single line of code.

This dramatically shortens the time from question to predictive insight. A sales manager doesn't need to file a request and wait weeks for an analysis. Now, they can apply a customer churn model to their own data and instantly see which accounts need immediate attention.

2. Enhance existing dashboards with a view of the future

You don't have to replace the dashboards your teams rely on. Machine learning in WebFOCUS enhances your existing analytics by adding a crucial new layer of forward-looking context.

Imagine your standard quarterly sales report. It shows a solid trend line of what you've accomplished. Now, with a simple click, you apply a native forecasting function. Instantly, get a view that extends beyond today’s date to show a data-driven prediction of where sales are headed next quarter.

This transforms a static report into a dynamic strategic tool. You’re no longer just reviewing past performance, you’re actively comparing it against a future forecast, allowing you to make smarter, more proactive decisions about resources and strategy.

3. Drive proactive actions, not reactive fixes

The ultimate goal of prediction is to get ahead of the curve. By embedding ML functions into your analytics, you empower your teams to move from reacting to problems to preventing them altogether.

This is the difference between analyzing why a piece of equipment failed last month and seeing a real-time list of equipment with a high probability of failing next month. It’s about a marketing team shifting from analyzing campaign results to predicting which customer segments will be most receptive to a new offer.

This proactive stance has a direct impact on the bottom line. It allows you to reduce churn, optimize inventory, prevent fraud, and improve efficiency by solving problems before they happen.

How it works in WebFOCUS

Since ML functions are natively available in WebFOCUS, our users get a head start utilizing the power of AI to drive their predictive analytics strategy. Users in WebFOCUS can access a library of native ML capabilities for things like forecasting, clustering, and outlier detection. And, these capabilities are available as if they were any other data function. WebFOCUS users can apply these models to their reports, charts, and dashboards to enrich their analysis with powerful, on-demand predictions, without needing to manage a separate data science environment.

The future of analytics is about looking forward. WebFOCUS gives your team the tools to do just that.

Ready to put prediction into practice?

Our WebFOCUS AI Bootcamp is a hands-on program designed for users already on WebFOCUS 9.3 to help you go from theory to practice by applying native AI capabilities to your own data.

Register for WebFOCUS AI Bootcamp, today!

Not yet on 9.3?

Our streamlined WebFOCUS Upgrade Program is the fastest way to access the latest features, including the machine learning integrations discussed here, and set the stage for your own AI initiatives. Learn more here.