Video conferencing usage gets new analytics to gauge ROI
Instead of assuming video ROI success, enterprises can now see a correlation between video conferencing usage and productivity with the help of new analytics tools.
A strong analytics package has always been part of any well-designed enterprise video deployment. When enterprises spend thousands of dollars on business tools, they'll want to know how the tools are performing.
While measuring results may seem simple, the value of analytics goes deeper. Analytics not only measures video conferencing usage and ROI, but it can help teams achieve higher levels of ROI. While this scenario has always been compelling, today's analytics can capture new types of data, which can be used to glean deeper ROI insights.
Traditional video analytics help achieve and measure ROI. Organizations can achieve video ROI via troubleshooting. Analytics, for instance, can detect problems such as bad connections, packet loss, disconnected microphones or other issues that could potentially ruin a meeting before they affect users.
End users have a low tolerance for failed video meetings and will quickly go back to audio conferencing after a frustrating video experience. By helping to prevent meeting failures, video analytics can keep teams from shifting back to less productive communications.
Analytics also enhances video ROI by allowing organizations to optimize their environments and allocate resources as effectively as possible. If your analytics package shows a facility's meeting rooms are always booked and video conferencing usage is high, perhaps that facility needs to equip more rooms with video. If analytics shows another facility has video equipment that is always idle, perhaps those teams need more training or the equipment should be reallocated.
Entering a new era of video analytics
Clearly, analytics can help you understand, troubleshoot and optimize your deployments -- and achieve ROI. On the other hand, how do you accurately measure those ROI benefits?
Generally, organizations rely on a simple assumption that can be expressed in this formula: Usage equals ROI. This assumption is valid, especially since countless studies have shown the productivity benefits of video conferencing usage. Therefore, if your goal was to get teams to use X minutes of video per month, and your analytics show more than X minutes, then you've achieved ROI.
While this approach has proved successful for previous generations of business video users, we are about to enter a new area of video analytics that will prove ROI far more deeply, directly and specifically, thanks to a wealth of new data.
An analytics package is only as powerful as the data it can collect, process and present.
An analytics package is only as powerful as the data it can collect, process and present. Video analytics packages primarily collect data from the video conferencing services themselves.
Until recently, video systems were not really "smart" devices. They weren't self-aware; therefore, they couldn't tell an analytics package what was going on around them. Basically, video systems could provide simple status data, such as if they were online, if they were on a call, details about the connection and protocols in use.
Going beyond video conferencing usage
Today's newest generation of video endpoints and other in-room collaboration devices are becoming smarter and more aware. They are designed as internet-of-things devices, not mere communication devices.
As a result, they can share much more information with analytics packages. In fact, they can go beyond sharing details about the connection, and they can share information about the meeting itself. For example, some services are already aware of the people in the room, thanks to newer technologies such as facial detection and recognition.
This innovation means video systems not only report on which systems are in use, but also which people are using them and how often. This is a complete game changer.
Now, video conferencing usage can be directly compared with the output of your working teams.
Now, video conferencing usage can be directly compared with the output of your working teams, allowing for true A/B testing of ROI. Instead of assuming you are achieving ROI because you have usage, you can see the direct correlation between usage and productivity.
With today's agile workflows, increases in productivity can be evidenced by shorter development windows and quicker average bug fixing. With these kinds of metrics available and the new generation of video analytics, organizations should find it easy to search for correlations between team productivity and video conferencing usage.
If you are the head of IT and audio visual for a large enterprise, what could be better validation than a specific report proving the theoretical and actual productivity benefits of your work?
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