Top 5 Ways to Reduce Incident Volume with AI & Analytics
Every IT organization would like to reduce the number of incidents they experience. The rewards for achieving this are substantial: fewer business disruptions, lower IT costs, and the ability to concentrate talent on growth and innovation. However, with your organization experiencing ever-increasing complexity, where do you start? It can be hard to know with service delivery fragmented across multiple systems, processes, geographies, and providers. These silos of teams and data lead to a lack of visibility, process inefficiencies, and knowledge gaps.
What analytics-driven best practice can help you reduce incident volume and improve customer satisfaction? Come hear Numerify’s Jim Henaghan, Solutions Consultant, as he shares ways companies like yours have reduced their incident volumes.
Topics that will be covered include:
- Proactive analytics-driven incident reduction strategies that target the highest impact problem hot spots
- How Machine Learning models can help predict incidents and reduce incident volume
- Using analytics to bring together siloed teams and standardize on best practice processes
- How text analytics techniques can help extract insights trapped in unstructured data