How Predictive Analytics is Reshaping Enterprise Reporting

How Predictive Analytics is Reshaping Enterprise Reporting

Thanks to the abundance of IT service management (ITSM) tools – technology suites that enable many of the ITIL-espoused, ITSM best practice processes – corporate IT organizations have a wealth of ITSM data. It sounds great, but is it really? When I point to the differences between data, information, knowledge, and wisdom; the wealth of ITSM data isn’t as useful as it could be without additional “processing.”

Some might say that we are lost in a sea of ITSM data, uncertain of both where we are and how best to navigate to where we want, and need, to be. It doesn’t matter which way we look at the water, it’s the aquatic, and data, version of “snow blindness.” There’s so much data that it’s hard to see things clearly, or to use that data wisely.

The Quality of ITSM Reporting and Analytics is a Known Issue

An enterprise’s ability to use the data stored – although some would say “trapped” – inside ITSM tools is a continuing issue for enterprise IT teams. A great proof point is the Service Desk Institute (SDI) report: “Life on the Service Desk in 2016,” which highlights reporting and analytics as both a top frustration with, and top required innovation/improvement in, ITSM tools (via two separate survey questions).

In a third question, the “inability to easily produce metrics and reports” was voted as the thing that causes services desks the most pain. With 53% of respondents pointing the finger at reporting and analytics, placing it ahead of other service desk pain points including: outdated ITSM tools, struggling with knowledge management and self-service, and budget constraints. Unfortunately for enterprise IT teams, it was also top when SDI produced its 2013 report.

Why Does Traditional ITSM Reporting and Analytics Hurt So Much?

Part of this pain relates to the core ITSM technology – that reporting and analytics is seen as an “add-on” to the ITSM-process enablement (incident management, say), and an add-on where “good enough” is probably sufficient to get through the request for proposal (RFP) and purchasing processes. The data is there but customers can’t use it in all the ways they would like to.

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