As a child I first learned about Thing 1 and Thing 2 from the esteemed Dr Seuss http://seuss.wikia.com/wiki/Thing_One_and_Thing_Two . Even then “things” were defined as strange fury critters. Behold, today it’s savvy to be describing perhaps the greatest revolution of all time (“Internet of Things”) as a thing. But what does IoT mean? For some reason we are ok to leave it undefined. The problem is, the thing is not a “no”thing at all. Many are using this term loosely and perhaps this is to be perceived as “in the zone”. What is most disturbing is most are playing catch up or making it up.
This talking in riddles needs to be explained more definitively. At the heart of the IoT, is predictive analytics. This is a fancy word for knowing with a high degree of confidence what is about to occur. Something like forecasting the weather but with much better accuracy. When I first went to university and studied numerical processing and digital signal processing I learned about the fundamental principles of predictive analysis. This is the “stuff” that NASA uses to ensure space ships are safer and the same “stuff” others use to avoid nuclear melt downs in power stations. So you see, we already have this technology in the industrial space, but not everyone is using it yet, especially at a consumer or domestic level.
I was recently listening to perhaps the largest software company in the world talking about the IoT and it became clear that Thing 1 and Thing 2 had much more purpose and meaning than much of the hype on the internet about IoT. Yes a revolution is coming, but it is interesting to watch as the major software vendors are using smoke and mirrors to draw in customers.
At the results end of predictive analysis is early warning of impending failures. This is its most common application to date. For the few mature companies who already have this worked out, they are already working on the next wave – predictive diagnostics. Next generation thought is now about automatically responding to predictive warnings and responding in a predefined and calculated manner. So while the “majors” sell with smoke mirrors to keep up, it’s becoming clear they are not even yet qualified to be at the table to make the next move. In the same vein as predictive analytics, my “early warning alert” is that many will be caught in the hype, and spend their life savings funding the majors who are still spending their energy trying to define what a “thing” really is. For the few craftsman who practice in predictive analytics and are now developing predictive diagnostics for their existing real customers, they won’t be paying much attention to things. The savings can be as great as 6 digits for those who embark on this strategic technology journey with purpose and commitment. Let us know if you would like to learn more.