Centralized service processes have improved cross‑department visibility but reporting still needs workThe machine learning capabilities in OpenText Service Management (SMAX) are somewhat not published the way they should be. They work pretty well, but they are not used as much in the current experience of our customers. They have them; the solution has them, but they usually go a little bit below the radar in terms of visibility. I believe there is room for improvement when it comes to machine learning capabilities. OpenText Service Management (SMAX) has room to improve mainly on reporting components. The reporting components include dashboards, and while OpenText Service Management (SMAX) has a reporting module, it's somewhat limited, so I believe it has room to improve there, with more inclusion of artificial intelligence in the models and more in project management and portfolio management capabilities. We want to see better use and more functionalities enabled with the already existing capabilities such as AI and reporting in the next OpenText Service Management (SMAX) release, but one important thing we think should be included is a module for metrics, similar to Google Analytics, that focuses on the metrics of the tool usage. The module shouldn't just report on the components of OpenText Service Management (SMAX) but also track how the tool is used by end users, for example, what functionalities users utilize more frequently, the performance of those functionalities, and how long it takes them to open a ticket or log in, focusing on applicational monitoring metrics and performance management metrics.
