Enterprise Connect Transformative Companies 2019

Enterprise Connect Transformative Companies 2019

26 Mar 2019

Before getting to a few companies that I believe can be transformational, a few comments on the event in general. This week the annual gathering of the Business Communication industry occurred in Orlando. While the formal name is Enterprise Connect, this year I would refer to it as Easy Connect. Virtually every session and presentation included the easy or simple or intuitive word to describe the user experience. The vendors have concluded that the biggest barrier to adoption (and revenue growth) is the complexity for the users: from Cisco, with their one touch join and Cognitive Collaboration, to Microsoft, moving to a common UX across all their partner products or Zoom/RingCentral, etc. focusing on ease of use as a common message. And from talking to end users, ease of use is seen as critical to adoption and growth.

The second clear trend was that “cloud,” and more importantly Monthly Recurring Revenue (MRR), is a key theme, whether in traditional telephony, UC or Contact Center. The focus for the vendors to meet the financial markets goals in MRR are driving a range of new capabilities and positioning.

As a BC Expert/Analyst/Consultant, I enjoy access to a continual stream of information about what is happening in the industry. For example, Brent Kelly and I do a session that contrasts Cisco and Microsoft. This session has been the most popular non-plenary session for the last five years; in fact, this year it was done in the plenary room to accommodate the volume. As part of preparing for that session, we spent over 34 hours with Cisco and Microsoft, reviewing their products, capabilities, architecture and go-to-market. The result is that most of the “major” announcements are essentially passé. I will leave the details of those to others.

Instead, I want to focus on the companies/announcements that represent either potential disruption in the market or that have technologies that are transformational. Last year, Nureva fit that class with their mist microphone technology that uses Cellular-based beam interference pattern shaping to create 8,000 individual virtual microphones in a conference room to maximize the capture of actual communications versus noise. As expected, the base technology is leading to innovations. This year they were demonstrating how they can minimize noise (paper rustling, etc.) while simultaneously enhancing actual speakers. By controlling which microphones are working, the pick-up can be limited to a portion of the room. For example, the active area can be limited to the front of a room during a presentation and then expanded to cover the audience during a question period.

This year there were three companies/announcements that I believe will have major ramifications, potentially for many years to come. The first was an announcement by Amazon that they will be offering on-demand (per minute) SIP PSTN access trunking services from the AWS cloud. That fact is interesting, but the price point was positioned as half of what is typically charged for SIP trunking by the major carriers. And if you already have high-speed pipes to Amazon for applications, they can carry your SIP traffic. Clearly, this has the potential of disrupting the price point for SIP trunking, impacting a range of vendors from the large carriers, (AT&T, Verizon, BT, DT, etc.), the CLECs (TATA, Broadband, IntelePeer) and the MSPs that sell SIP trunking as part of their offer. However, it may be a more long-term Amazon strategic move. Many of the early partners of Broadsoft that offered the initial “IP Centrex” were SIP trunking providers that added the hosted/Cloud PBX services as their customers migrated from older premise gear. The potential for Amazon to leverage these relationships based on SIP trunking into full blown cloud communications solutions may change the landscape dramatically. This reflects the changes in the Contact Center space in the last year with Amazon Connect and Twilio Flex.  In the Connect case, the per-minute CC model was/is transformational and the adjacency of CPaaS to CC enables Twilio to have a unique offer to their developer driven CPaaS community.

While a big player may drive a change, often it is a smaller start-up. The first company I saw that has a potentially disruptive technology/business model is Red Box (it is a UK company and probably did not realize that Redbox in the U.S. is already a brand in media distribution). Red Box is building an “open” voice recording solution with open APIs to allow capture from a range of communications platforms and enable open access for analysis by a range of analytical and machine learning systems. The Red Box proposition is that leaving voice recording in a closed platform like Nice or Verint restricts innovation and use outside of those products’ own analysis solutions. The Red Box proposition is to move captured voice to an open platform, where a range of new analytic/machine learning solutions can be used to transform the value proposition. While this may be an uphill battle for adoption, the premise is very interesting and, I expect, may be replicated in some of the other platforms. Treating the volume of captured voice recordings as a data archive for a range of uses could open significant opportunities for AI and other uses.

Finally, I met with a small company, Voicesense. The founder of Voicesense, Yoav Degani, combines a background in clinical psychology with work in defense signals processing. The company claims it has identified 220 pattern elements in speech (not the words that are said, rather the way they are said and the patterns in speech) that can be used with machine learning to identify human behavioral traits. This is fundamentally different than sentiment analysis or traditional analytics as it uses speech patterns to predict future behavior (scary, I know). The company claims that it can take voice recorded data, marked for the speech parameters and use machine learning to correlate specific speech patterns and tonal/pacing nuances to predict behavioral outcomes. Using a set of speech samples with known outcomes and using the speech patterns associated with the people in those events, the machine learning can learn which speech factors correlate to a specific defined behavioral outcome. The company’s first commercial bundle offer is a machine learning prediction for loan defaults. Voicesense claims their algorithm has been trained to detect the speech patterns that correlate to defaulting on a loan and within 60-90 seconds of recorded speech from a prospective borrower (on any topic) can predict the potential of that person defaulting on a loan. While I cannot directly comment on the validity of the claim, the potential in business applications behavioral predictor solutions is huge. Also, similar skills in identifying speech patterns are regularly used by criminal justice specialists. From predicting buying patterns to analyzing interview candidates, the capability to use speech patterns as predictor for behavioral outcomes is profound. While the business applications are mind-boggling, the potential social issues are earth-shaking. How this technology might combine with the Chinese “social credit” system or in criminal justice or even in education may have long term impacts. Having insights into the behavioral soul through a short speech snippet is unsettling at best.

In conclusion, once again Enterprise (Easy) Connect produced some surprises and some predictors for our future.


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