Understand endpoint analytics
It's not uncommon for end users to experience long boot times or other disruptions. These disruptions can be due to a combination of factors, such as:
- Legacy hardware.
- Software configurations that aren't optimized for the end-user experience.
- Issues caused by configuration changes and updates.
These issues and other end-user experience problems persist because IT doesn't have much visibility into the end-user experience. Generally, the only visibility into these issues comes from a slow, costly support channel that doesn't usually provide clear information about what needs to be optimized. It's not only IT support bearing the cost of these problems.
The time information workers spend dealing with issues is also costly. Performance, reliability, and support issues that reduce user productivity can have a large impact on an organization's bottom line as well.
Endpoint analytics aims to improve user productivity and reduce IT-support costs by providing insights into the user experience. The insights enable IT to optimize the end-user experience with proactive support, and to detect regressions to the user experience by assessing user impact of configuration changes.
Endpoint analytics currently focuses on three things:
- Recommended software: Recommendations for providing the best user experience.
- Proactive remediation scripting: Fix common support issues before end-users notice issues.
- Start up performance: Help IT get users from power-on to productivity quickly without lengthy boot and sign in delays.