As an example, if your datalakehouse contains both historical and current operational data, trend analysis, a known error database, a forward schedule of change, a capacity plan, an availability plan, service level targets and agreements, customer and supplier portfolios etc, it would be possible to implement AI algorithms that could identify threats to operational stability ahead of time. The more data it contains, the more broadly will be the reach of the AI.
Proactive Problem Management
AI in Problem Management could carry out the incident matching activities previously carried out manually. Using algorithms based on pre-defined pain and impact criteria, it could prioritise the underlying problems and even take that a step further by interrogating vendor websites to automatically identify potential fixes. It could even raise changes and implement the patch if the associated level of risk was deemed acceptable.
Service Level Management
Algorithms based upon service level targets, and the various factors that determine whether they are likely to be achieved (such as capacity, changes, planned staffing levels, budgets etc) could together flag up situations, ahead of time, when service availability might come under threat.
Such an “early warning system” would provide time and awareness, allowing for mitigation activities to be conducted proactively, ensuring that robust and cost effective, long-lasting resolutions can be put in place instead of the reactive,
sticking plaster solutions that might otherwise have been the only viable option.
Conclusion
The simple conclusion to be drawn from this is that Artificial Intelligence and Service Management are made for each other.
Service Management at its best is a simple concept. Define services, measure them, improve them, deliver value. Move from a reactive to a proactive approach whenever possible.
Artificial Intelligence is something that thrives in such an environment, with its algorithms being the perfect tonic to many of the low-level activities that underpin so many of our SM practices.
One thing is sure, we are only just beginning to explore what is possible, but the early signs are hugely encouraging and dare I say exciting. So the only conclusion I can come to is that Artificial Intelligence will undoubtedly play a huge part in the future of Service Management.