Blog: MDM alone is not enough
In my previous blogs I’ve shown how organizations can benefit from intelligent asset management and avoid having to return devices from the field by monitoring device performance with mobile device management (MDM) and mobile device analytics. It is important to understand that mobile device management and mobile device analytics are not the same thing. You need both of them to achieve the best possible uptime for your mobile devices, and the best productivity for the workers who rely on them.
The main differentiator is that a typical mobile device management system tells you what state your mobile devices are in right now (i.e. is there a critical problem or is the device operational?) and allows a remote fix if required and if it’s possible to do so. Mobile analytics focus on device and application layer performance, can perform some root cause analysis for any inconsistencies, provide insights in to potential problems such as battery failure, and does it all in real time. That makes mobile device analytics a predictive tool that you can use to change device settings or operational practice to optimize performance, prevent slowdowns or crashes, and thereby protect worker productivity.
Mobile device analytics do more than mobile device management, but don’t do everything an MDM can do. That is why the solutions are complementary. Mobile analytics should be viewed as an enhancement to your MDM system, not a replacement for it. We believe mobile analytics should also be viewed as essential—because business is more dependent than ever before on mobile workers, applications and data access, enterprises need to do more than they’ve done in the past to improve device performance and uptime.
Examples from the Field
Let’s look at some common mobile device work scenarios to see how MDM and mobile device analytics complement each other and provide value to the enterprise. Suppose an IT support desk gets an emergency notification that a mobile computer used by one of the company’s workers has crashed. The sooner the support team can diagnose the problem, the sooner it can get the device rebooted and get the user back to work. Ideally, the fix can be made over the air, which is a capability that many MDM solutions provide.
But before the device can be fixed, support needs to know what went wrong. Did the network connection drop? Was there a resource conflict among the applications being used? Was it operator error? Was it something else?
The MDM will probably be able to report when the device crash, its approximate location based on the nearest cell tower, and perhaps what applications were running at the time of the failure. That information will give the support team clues to solve the problem. The support team still needs to figure out why the failure occurred, and whether the conditions were device-specific or if the entire device population is at imminent risk.
Mobile device analytics can provide deeper insight so the problem can be diagnosed and solved faster. In many cases, real-time performance monitoring prevents a problem from occurring at all. For example, the failure may have occurred because a repair technician was using the camera built into his mobile phone or computer to take a lot of pictures to document damage to an asset. The field service software application may have been set to update in real time. That could result in the large image files sent wirelessly, straining bandwidth and processing power on the mobile device to the point it crashes. Mobile device analytics would alert the user and/or system administrator to the increased bandwidth/memory use in real time. It could work with the MDM to automatically switch the application to offline mode, or could issue alerts to the mobile worker and system administrator.
A more common reason that devices crash unexpectedly is that too many applications were running. Software updates that launch unexpectedly and run in the background are a real risk here. An MDM would provide the forensic evidence that a software update or other application conflict caused a crash. In contrast, a mobile device analytics solution would issue an alert that CPU cycles were running especially high on the affected devices, and would provide real-time documentation of which specific apps were consuming devices resources. Administrators could then stop and reschedule the update or remotely shut down some applications (including those running in the background, and personal or non-authorized applications like games or Facebook) so essential mobile work processes could continue.
Mobile device analytics make MDM more proactive, and as a result, make mobile workers more productive. At a time when organizations depend on their mobile workers more than ever to keep the business running, they need more than MDM to keep mobile devices as reliable as possible. Mobile device analytics are what organizations need to avoid preventable mobile device failures, work disruptions and customer service disappointments.