his article excerpt, by Dave Stein, originally appeared here: http://ubm.io/ZovEL4
We’ve seen a variety of analytic-type tools develop in the contact center space. Since at least 2010, recorded voice calls have been analyzed for word spotting, indexing, and emotion detection. This, in turn, has been used to improve training, sales success and workforce optimization.
We also see “Big Data” analytics gaining momentum in virtually every industry in both premises and cloud implementations. This type of analytics, often done in real-time, provides the deploying organization with a significant competitive edge in speed and Business Intelligence (i.e. Walmart knows what is selling well in Los Angeles on Tuesday morning and can increase orders and improve delivery time by Tuesday afternoon).
So how does this apply to the subject at hand? From a Unified Communications standpoint, I see two separate areas of analytics that have developed: system-oriented analytics and end user/BI-oriented analytics.
I see the system type of analytics as being able to inform administrators as to what functions are being used and by whom. In other words, which specific users (and/or groups) are utilizing presence, IM or video? How often are they using it, and who are they using it with?
If you thought that the system type of analytics would be basic and offered on most UC platforms, you’d be incorrect. We are currently asking for these tools in Unified Communication RFPs; we most often see vendor responses that this is a future roadmap item. Products such as Microsoft Lync provide basic analytical reports with some useful information.
A pleasant surprise is the reporting information available from the Microsoft ecosystem partners such as Unify Square. Their Powerview product includes items such as actual usage analytics, conferencing analytics and adoption analytics. On the cloud front, Masergy recently announced their UCaaS Analyst tool, which promises real-time quantitative and qualitative info somewhat similar to that offered by Powerview.
Rather than have system admins cobble this information together (if it’s available at all) or guess at how the system is being used, tools of this type provide empirical information that can be used to determine if the initial procurement assumptions regarding UC usage and ROI were accurate. It also informs what changes should be made for training programs and even licensing. I believe that analytics of this type should be included in every UC product and should be widely deployed. We will see if the vendors agree.
While very useful, this type of analytics pales in potential value compared to the Business Intelligence information provided by Big Data analytics. There hasn’t been much product specifically for the UC market in this area to date. Some vendors have announced big data analytics as part of their next-generation offerings (such as Unify’s Ansible). However, with small market shares, limited adoption to date and limited marketing budgets, this has not been top of mind for most of my client base.
However, times are changing. With the recent announcement of Microsoft Office 365 Delve, there is a strong likelihood of this becoming mainstream in the medium-term. It will take some time for the software to be developed that will “automatically” identify process improvement as well as mine the UC interaction data for other useful information.
This is an area to watch closely in the next two years to see what develops. I am on the fence as I weigh the past failures of artificial intelligence vs. the potential of deriving useful information from UC systems and user interactions.
So, bottom-line, the system-oriented analytics is here today, has value and is ready for prime time. It’s “wait-and-see” on the UC BI/Big Data analytics.