Have you encountered a bad situation that was made worse by something that is meant to help? Here’s a recent example of mine – I had to take my son to an emergency room while vacationing in Asia but the most frustrating part was dealing with insurance when we got home. The agent who initially processed my claim put me (and my money) in limbo – no external or internal follow-up communication, inaccessible and invisible in the client portal – because they didn’t follow the process for handling non-English documents.

Here’s how process mining could have saved present and future costs for the insurance company in my scenario.

Digital process definition: Ahead of my problem, the business process flow for routing claims would have already been discovered and acceptable paths defined.

Omnipresent monitoring: My claim being dumped in no-man’s land would have been flagged as a deviation by process mining not finding any status update after a defined duration.

Active alerting: The deviation would have alerted a supervisor to investigate the claim and properly reroute it, saving a future agent from having to chase it down.

Continuous improvement: From there, the supervisor could have assigned the specific training course on dispositioning non-English documents, preventing a future occurrence and/or laying the foundation for a performance improvement plan. Some process mining vendors provide enhancement features that leverage AI to recommend process improvements which, in this case, could have led to an organization-wide improvement based on the lessons learned from this single process deviation

Since process mining and process intelligence solutions use data available in information systems, companies can gather new insights without having to upgrade entire systems. This means that my insurance company could have a years-old claims management system (let’s be honest, they do) and still deploy process intelligence on it. It also means that the company could leverage the process intelligence tool on their IT ticket management for tracking technical support, their ERP for tracking a procure-to-pay or order-to-cash process, the list goes on.

My ordeal with insurance claims highlights a critical lesson for companies with customers (that’s all of us): effective integration of AI solutions, like process mining, can significantly enhance customer experience and operational efficiency. The example underscores the importance of harmonizing people, processes, and systems to mitigate preventable mistakes and improve profitability. Process mining, by leveraging existing data to provide deep insights and continuous improvements, represents a promising approach to achieving these goals. As organizations contemplate implementing such technologies, it’s crucial to consider relevant use cases, industry expertise, technical integration, unique vendor differentiators, and user needs. By doing so, you’ll not only resolve current inefficiencies but also pave the way for a more responsive and streamlined future.

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