I had the good fortune to be invited as a “futurist” to the #IBMInsight conference in Las Vegas in late October. Along with about 30 others we were exposed to some of the amazing things IBM is doing with what they call “cognitive computing.” The conference had several themes wrapped around the power of data, which included positive disruption and collaboration. We also talked about a #NewWaytoWork and how that is being driven by data.
I don’t know if IBM invented the term cognitive computing, but they seem to embody it. With Watson, and its ability to process unstructured data, companies can sort through massive amounts data quickly and make “sense” out of the noise. Watson doesn’t just process data, Watson can learn and you can teach Watson as well.
Wikipedia describes cognitive computing as:
Cognitive computing (CC) makes a new class of problems computable. It addresses complex situations that are characterized by ambiguity and uncertainty; in other words it handles human kinds of problems. In these dynamic, information-rich, and shifting situations, data tends to change frequently, and it is often conflicting. The goals of users evolve as they learn more and redefine their objectives. To respond to the fluid nature of users’ understanding of their problems, the cognitive computing system offers a synthesis not just of information sources but of influences, contexts, and insights. To do this, systems often need to weigh conflicting evidence and suggest an answer that is “best” rather than “right”.
They point out that it makes “context” computable. That is powerful.
For three days during the opening general sessions we got example after example of the power of data in cognitive computing. From something as simple as helping you make the appropriate wine selection for the dinner you are preparing to assisting in the search for extraterrestrial life by sorting through massive amounts of data produced each day from searching the skies.
Wine4.Me, from VineSleuth, is an application powered by Watson that allows you to input data as to your tastes and preferences and it provides suggestions to meet your need. It eliminates the guessing.
As a cyclist, one story I found interesting was that of Dave Haase, an endurance cyclist. Dave rode this year in the Race Across America, for his fifth time. It is a race where the riders ride for 22 hours and sleep for 2 hours. They are going 3000 miles and ride around 400 miles per day. Compare this to the Tour de France where those riders ride 130 miles per day or so. He has finished in the top three American racers in the past, but this year at the age of 47 the task was more daunting. He turned to IBM and Watson for help. They measured his physical performance prior to the race, his physical performance during the race and combined that data with weather and geographic data to come up with a plan for the ride. The result was a second place finish, having saved 12 hours of ride time over the almost 9 days of riding. A triumph of man and data. You can read more here about this fascinating story.
Data convert and the challenge
As a result of my attendance at #IBMInsight I have become a data convert. I now see the value and power of collecting and analyzing data, especially for the HR department. The challenge I see is in getting smaller companies to collect and analyze the data on their employees. It is sitting there, sometimes, but not coordinated and certainly unrealized. Performance data, attendance data, quality data, accident data, health data, personal data, resume and job history data and more are all waiting to be analyzed to bring the power of prediction to the smaller HR department.
Right now Watson and cognitive computing are a “no brainer” (pun intended) for larger HR departments. How to scale it to smaller organizations and bring the power to the vast majorities of companies is the challenge. After attending this conference however, I am confident we can find a solution. As a result we may see a #NewWaytoWork.