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In Context Analytics: The massive disruption of search

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By Simon Thomason, EMEA Director and Kieran McCorry, Strategist and Distinguished Technologist, HP Enterprise Services

 

 

Enterprises are overwhelmed by a torrent of information riches. Cutting edge tools are delivering enterprise intelligence, consumer data, and market statistics that ebb and flow in real time. But have we created a beast? If so, the answer may be HP In Context Analytics.

 

analytics.jpgWe’ve all had the experience of organizing a conference call. Lots of time is spent just prepping the environment to make sure everyone has access to the right information— and the capability to share it. This tedious process hit a boiling point for us about 3.5years ago. We grew tired of trying to deal with the ever-increasing amounts of organizational information applicable to us that wasn’t locatable. Existing systems were so static. Because of either a SharePoint or a Bing or Google search, you had to sift through dozens of search results or go to this or that site. There was no other option.

 

So we asked ourselves, how can we develop tools that learn as a human learns, and search as a human searches? And how do we make it contextual so that we get the information we need, when we need it?

 

Our answer is In Context Analytics, a system that listens in on and analyzes text, chat, or voice conversations, then provides information that is contextually relevant to the conversation. Say, for instance, that you’re in an online meeting and someone suggests that you reference the year-end report afterwards. In Context Analytics reads that dialogue and, in real time, pops up the report on your screen. In simplest terms, it’s like a proactive, highly intelligent online concierge with really good listening skills.

 

Revolutionizing search

At its foundation, In Context Analytics is a structurally aware system that utilizes information about the individuals within the conversation. It doesn’t specifically look at individual key words. Instead, it looks at the conversation as a whole. The system then processes the meaning behind elements of the conversation and finds the relevant content. Results are presented in real time. The information can be retrieved from both private and public clouds.

 

Consider the call center. Call centers often have after-hours coverage by individuals who don’t necessarily understand all of the nuances within their organization. So they read from scripts. But scripts don’t always suffice. Having a separate system observing the conversation and looking for appropriate information to fill in the gaps greatly heightens the call’s effectiveness. 

 

At the other end of the spectrum, high cost professionals such as geophysicists, medical doctors and senior executives will gain time savings through access to the right data at the right time. Increasing productivity at this end of your business, drives real business efficiency.

 

In Context Analytics is a self-learning system that features a heuristics engine. Acronyms, for example, are learned by the system and added to a global acronyms dictionary for later use. The more the system is used, the more it learns about the enterprise. It actually starts inferring about the individuals and the elements in the conversation. We think searches—and results— will never be the same.

 

Meet Simon and Kieran at HP Discover! Register today for their Innovation Theater demonstration of In Context Analytics. Or join them in a continuing conversation in the HP Innovation Insight LinkedIn group.

 

 

About the authors

388588f.jpgkieran_mccorry_74X90_tcm245_1442966_tcm245_1422290_32_tcm245-1442966.jpgSimon Thomason is the EMEA Director of Microsoft Transformation Services for HP Enterprise Services. Kieran McCorry is a Strategist in Applied Innovation for HP Enterprise Services. Simon and Kieran were inspired to make the workplace more productive by empowering employees to work smarter. Together, they invented HP In Context Analytics. 

 

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