Customers often have a clear vision of how an ITSM system should function, but they frequently bemoan of a lack of built-in automation and intelligence, “Why doesn’t this tool automatically tell me that these two outages are related?”, “Can this system predict when I will have an outage or when I will need to add more capacity?” Often these requirements are very intuitive and easy to justify.
However, providing intelligent insight and automation requires foreknowledge. Historical data needs to be gathered from a variety of perspectives, spanning different ITSM processes, in order to glean the appropriate trends via analysis. The first and most important questions to answer are: What are you trying to predict or automate? What data can you store and for how long? How can the data be correlated and analyzed to give you the predictive insight that you’re looking for?
What quickly becomes apparent in the effort to move to more proactive or predictive ITSM is that having the right data available is the largest hurdle to surpass. A strategic vision that aligns with the core needs of the business is needed to firstly zero-in and reach a consensus on the ITSM operational areas which can be improved by automation. Objectives and goals can then be prioritized and aligned with the data that can be made available.
The second and equally complex hurdle is how to use the data. All environments are unique; in order to successfully automate a customer’s process or provide the right predictive insight best-practices are not enough. A customized solution often needs to be built based on an assessment of the customer’s process and operations as well as an analysis of the available data.
It’s safe to say that even the most intuitive ideas can hide a depth of complexity.
Softential Senior Consultant