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UCC's future could lie with cognitive computing

Cognitive computing could usher in a new era in UCC that prioritizes finding and delivering vital information to employees.

Unified communications and collaboration (UCC) have preoccupied vendors for a decade or more. Every year they claim a revolution is just around the corner, yet enterprises never see it. Instead, the technology grows more complex and difficult to use.

As a result, companies have embraced separate applications and processes for email, voice calls and instant messaging to the point that there seems little reason to try to unify them. Instead of a single application to manage communication channels, businesses would be better served with technology that delivers information that helps employees do their jobs efficiently.

To do that, UCC vendors have to take a giant step forward, and two developments offer a hint at where they should go next to make their products and services truly essential to the enterprise.

Digital assistants and cognitive computing

One important development is the intelligent personal assistant. Examples include Apple's Siri, Google Now and Microsoft Cortana. These technologies combine voice recognition and response with search to make better user-to-information connections.

Instead of a single application to manage communication channels, businesses would be better served with technology that delivers information that helps employees do their jobs efficiently.
Tom Nollepresident of consulting firm CIMI Corp.

In terms of collaboration, this is an important development because it is based on the assumption that users can find what they need by simply asking a question. That implies computer access to information, along with the ability to do ad hoc analysis of both questions and data to present answers. Sadly, most users feel that these voice-agent products fall short of the mark.

That problem may be fixed by the second development, which is IBM's decision to provide its Watson cognitive computing platform as a cloud service.

"When asked a question, Watson relies on hypothesis generation and evaluation to rapidly parse relevant evidence and evaluate responses from disparate data," IBM said at its PartnerWorld conference.

That sounds like a way to bring value into the personal digital assistant space. It's also a reasonable description of the goal of collaboration, so it raises the question of whether we should switch from thinking about collaboration in terms of the user’s information goals to connecting people to meet those goals.

Why would Watson, or something like Watson, be better than a simple speech-to-text search? The one-word reason is context.

The biggest difference between communicating and searching the Web on a desktop and mobile device is that mobile devices provide information relevant to users' location and what they are doing at the time. Mobile devices and mobile services generate considerable information on location, movement and social context, meaning the human relationships a given worker might have. The challenge has been to incorporate this knowledge in developing answers to user questions.

Siri marries Watson

The wedding of a mobile personal assistant and a cloud-based cognitive computing application creates a model for answering a person's question that would look something like this:

Answer = UserInquiry + UserContext + InformationResources

Analyzing inquiries, their context and the available information would provide people with more relevant answers. Something like Watson could provide the analysis, if we delivered the inquiry and the context of the request in a form that could be understood by a machine.

Speech recognition,  location-based and social-driven services are already advancing, so it's reasonable to think that the critical ingredient is the ability to harness what we have to develop better answers for employees.

More important than unifying the information channels of voice, email or instant messaging is determining in real-time which expert in a person's contact list is available with the needed information.

Think of a search that returns not only multiple answers, but sources of information based on the knowledge of each expert and his availability. An employee standing with a mobile device in front of a refinery manifold might ask, "What valve does this tag belong to?" and be given either a map of the manifold or be connected to the worker who attached the tag.

So far, IBM's deployment of Watson in the cloud seems more an extension of traditional analytics than a move into contextual intelligence for mobile productivity enhancement. That doesn't mean that a union of mobile personal agents and cognitive computing wouldn't be a major opportunity or that other vendors won't try to exploit it. The competition among mobile personal assistants seems to be heating up and expanding the scope of things these assistants can do beyond simple voice search.

As stated previously, users don't necessarily need a single application to manage their communication channels. Instead, they need better context-related information to do their jobs efficiently. The mistake UC/UCC vendors have made is focusing only on human exchanges to provide that information. That mistake has stalled collaborative growth within the enterprise. Perhaps a marriage of Siri and Watson, even as an extension of IBM’s enterprise partnership with Apple, could break the logjam.

Next Steps

How cognitive computing could work for your business

See what experts say about deploying mobile UCC in the enterprise

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Dig Deeper on Unified Communications Architecture and Service Models

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Do you believe cognitive computing could revolutionize unified communications and collaboration?
Yes, I could definitely see this happening - but cognitive computing capabilities need to be combined with a user-friendly interface to drive adoption.