Resolution beyond response
Closing tickets is a bit like gardening. You keep pulling weeds in the same space every day until you stop them from growing back. So, how do you stop pulling weeds and spend more energy making the garden flourish?
The practiced answer? Analyses such as the one we detail below, but conducted on an infrequent or ad-hoc basis. For example, when you’re planning a major hardware upgrade or digitalization initiative. Outages persist and someone calls for a review. Providers consistently under-perform, so “Something has to be done.”
Project and event-driven analysis tends to be reactive in nature and there is no easy way for IT to respond, much less become more forward-looking. Pure-play metrics generated by monitoring platforms mainly talk to your current state. Ticketing systems are a better source of truth but offer little context or actual insight.
Platforms like Jira and ServiceNow optimize activities around workflow processes – which queue should something funnel into, or how long did a particular issue take to close – not true resolution. Combining the two sets of outputs—which isn’t easy—still doesn’t get you to the root of the problem.
CIOs can’t immediately use data from these platforms to extrapolate and drive meaningful conclusions toward a clear course of action, and the absence of an aggregate bird’s-eye view creates extra work downstream.
![Man-machine reduction of noise and collaboration with customers](https://netenrich.com/hs-fs/hubfs/blog/resolution-intelligence-for-outcomes-driven-it.png?width=1024&height=534&name=resolution-intelligence-for-outcomes-driven-it.png)