Predictive Contextual Collaboration

Contextual prediction is hot. I am not just saying that because I am in the prediction, forecasting and analysis business. I am talking, for instance, about the ability that businesses have to predict what we are going to buy, how much we are willing to pay, whether we can pay to begin with, whether we are potentially fraudulent and so on. Business intelligence and analytics software vendors provide tried and tested tools to telecoms operators giving useful contextual intelligence about their (potential) customers in the virtual and connected ecosystem.

Contextual prediction is hot in the physical world as well. Through sensors the Apple iPhone knows it should power off the touch screen if I bring the phone to my ear. It predicts I am making a call. The Samsung Galaxy S3 predicts I am reading an e-book because the front camera sensor says so. Smartly, it keeps the backlight on. Gesture-controlled laptops shut off automatically if I walk out of the room. Through the Doppler effect measured by the built-in microphone and speakers the laptop predicts I will not need it for the time being.

But while a great deal has been done in predicting customer behavior, we have done very little on the employee side. That is about to change.

Google mail, for instance, features an automatic reminder if you forgot to attach a file that you referenced in the email text. It also comes up with suggestions of contacts to include in your mail based on your email usage history. Plantronics’ Voyager PRO UC headsets incorporate sensors that detect aspects of your physical world. Application vendors can incorporate this contextual intelligence into their applications to know when the headset is worn, user proximity to their PC, mobile call state, and with whom the user is talking.

Going forward, the effectiveness of collaboration and communication in the enterprise will greatly improve through what I call predictive contextual collaboration sessions. In such a session, contextual collaborative intelligence will predict which content and contacts are relevant for an interaction. Just like Facebook and LinkedIn provide suggestions on which friends and business relationships you should connect to.

But there are some problems to be solved before predictive contextual collaboration will take off. Given the fact we collaborate across departments, systems and companies, it will need to work across the entire range of IT systems and applications that are in use by a company. It will need to work across the multitude of communication channels, features and tools we have at our disposal today.

Vendors like Qontext are solving part of the problem through providing dedicated social collaboration platforms that facilitate content sharing, contextual conversations and collaboration across business applications. Expect vendors that sell broad communications and collaboration platforms such as Avaya, IBM, Microsoft and Cisco to follow suit.

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About Pim Bilderbeek