Most customers don’t like calling customer support. It takes too long to get the answers they want, and they walk away feeling exasperated. Many organizations find themselves frustrated with their customer support experience as well. They know they need to provide a better, seamless experience for their customers, but they are challenged with information silos, an incomplete view of the customer, and a support team that has to hunt and peck to find the right information.
The concept of Garbage In, Garbage Out (GIGO) is almost as old as computing itself. Its origins have been traced back to the 1950s and basically means that if you start with bad information, you get faulty results. It’s a pretty simple concept that remains at the core of computing.
We’re delighted to announce today that we’ve formed a partnership with MC+A, a Chicago-based search technology innovator and systems integrator.
Not only will MC+A act as a reseller of the Attivio platform, they will assist companies in upgrading from legacy search applications, such as Google Search Appliance (GSA). MC+A’s connector bridge solution simplifies the transition to Attivio’s modern, machine-learning-based platform.
Even as the press is filled with stories of artificial intelligence and cognitive technologies, the market isn’t entirely sure what to make of these advances. As with any emerging technology, the question arises of whether it’s all hype or if it’s truly transformative.
We used to think of knowledge workers as a few librarian-like employees responsible for managing all kinds of information. But information has become like currency: the more you have, the more you can do with it. And that means everyone has the potential to leverage information to perform their jobs better and increase the quality – and speed - of their decisions.
At the 2107 Sohn Conference, Social Capital CEO and founder Chamath Palihapitiya declared, “Watson is a joke, just to be completely honest.” Of course, this quote got a lot of play. But another quote from the same interview is actually more revealing about why so many cognitive computing initiatives eventually circle the drain — and why they take so many resources with them.