Enabling proactive problem management and reducing major incidents with data analytics
It is Monday morning, and once again, everyone in the organization drops what they are doing to take on unplanned work due to another major incident. Sound familiar? If so, then your organization is struggling with the challenges related to systemic problems caused by technical debt, unstable snowflake environments, and issues related to process capability.
To reverse this trend, organizations need to go on the offensive by moving from a reactive Incident approach to proactive problem identification and management. However, to do this successfully, Lean teaches that you need data since you cannot avoid a problem you cannot see.
Join Troy DuMoulin, VP of Research and Development at Pink Elephant, and Amit Shah, Director of Product Marketing at Digital.ai, as they discuss the critical success factors for enabling proactive problem management and how data, analytics, and machine learning can enable organizations to avoid major incidents and reduce un-planned work.
Topics that will be covered include:
Reactive versus proactive problem management
Major Incident reviews and trend analysis
Using root cause analysis techniques to improve incident prediction
Using risk management to manage problem backlogs
Using AI/ML techniques to create early warning systems