Process prediction

It’s one thing to understand what has happened in your processes in the past and even better to understand what is happening at the present moment. But even more powerful is the ability to understand the future of your processes—the direction that things are moving, and what is going to happen in the process before it actually takes place. This is what process prediction offers—the fact-based data that is needed to mitigate or better prepare for what is ahead.

Traditional process mining is focused on looking at historical data. While this approach can offer valuable insights into what worked well and what didn’t, it falls short of offering solutions for present and future iterations.

Predictive analytics help businesses make smarter, more strategic, fact-based decisions by relying on data to determine potential outcomes.

Predictive analytics data supports risk management, enabling companies to predict events, outcomes, and behaviors and develop risk mitigation strategies for potential risks.

Predictive analytics informs customer experience metrics, providing insights about customer behavior that marketing and other teams can take action on.

Predictive analytics improves operational efficiency by guiding the utilization of future resources based on the outcomes of past events.

Process prediction uses historical execution patterns to train an artificial intelligence (AI) engine to predict the likely outcome of a process very early on. For example, an insurance company may use this approach to predict the likely outcome of a claim based on historical data. This proactive approach allows the insurance company to address any potential issues early, leading to faster claims resolution, reduced costs, and improved customer satisfaction.

Because business process prediction is based on historical data, the accuracy of the prediction is dependent upon the quality of the data. AI-based predictive analytics can enhance its accuracy as new data becomes available. Real-time predictive analytics enables an organization to predict outcomes based on the most recent data as it’s coming in, on a continuous basis.

Not all process intelligence tools on the market are the same. Many legacy process mining tools fall short of the expectations of organizations today for a comprehensive process intelligence solution. Organizations should look for a modern tool that is designed to fully meet the demands of today’s enterprises and go beyond surface-level issues. Process prediction can be effectively implemented as part of a complete solution that comprises process discovery, process analysis, process prediction, and process simulation.