A Disruptive Moment
It is very hard to pinpoint a disruptive innovation and the moment it hits the market and I have said this many times before. It’s easy to know that you use this or that technology today and couldn’t imagine living or working without it but, really, can’t you imagine the time before you started using this stuff? Social media might be a good example since most of today’s users still kind of remember what life was like before. Today is one of those days, I think.
Today Ayasdi came out of start-up stealth-mode and announced itself and you can see an article about it here in the New York Times.
So what is it in a nutshell? It’s only the first really new and different way to analyze big data since we started collecting it. Ayasdi uses something called topological data analysis and here’s one place where it’s different. Rather than type a query or ask for a report from a big data set, Ayasdi just looks at the whole data set and tells you where the interesting clusters of data are — clusters in places you may not have thought about.
So that means you no longer have to more or less know what you are looking for to use analytics, you simply need to know that you want to understand the interesting clusters. That’s a disruptive moment if you ask me — presuming it works as well as the early hype says it does. To me this sounds more like advanced data mining than business intelligence but I am not an analytics guru so this is simply speculation.
So what’s it good for? Well, if you’ve collected a lot of data about a molecule you think might have beneficial pharmaceutical properties, rather than performing a lot of screening tests, you might first examine the data topology and then investigate where the data says there are interesting relationships. And, yes, substitute customer for molecule in the above and more interesting things happen.
As with any disruption, it’s hard to think of what the world will be like in the aftermath, but if this works as advertised a few years hence we might all be scratching our heads trying to recall what life was like before.
Think Bigger
I spent the best part of last week cruising up and down Silicon Valley checking in with customers and would be clients. The consensus from this non-scientific survey is that business is better than OK and most people are expecting this year to be the best in a while. Of course there is a cloud—literal and figuratively—to go with that silver lining. After all, we’re bouncing off a long fall to what’s still a soft bottom.
Business is good enough out there that many companies can’t find enough qualified people. Ted Elliott, CEO of Jobscience, sometimes refers to it as a skills gap with many older workers not having all of the skills that newer companies seek. People with all the requisite skills are rare and valuable and Elliott refers to them as “unicorns” because they’re so hard to find and, yes, he’s got and app for that.
While you might say that such gaps are generational and common it’s still noteworthy that a generation ago the gap was between laid off steel workers and service sector job requirements. Today it’s between laid off tech workers and new tech job openings.
Interestingly, if you have a Ph.D. especially in a science or math, there’s no job shortage especially if you like to work at IBM. A recent story in the New York Times said that IBM hires more math Ph.D.s than anyone else in the world. You could have figured that out from all of the patent applications they file.
What’s been interesting to me in the last couple of weeks has been the intersection of big data, IBM’s quest for brains and a recent report from Forrester Research. The report in question is a project led by Phil Murphy titled: “BT 2020: To Thrive In The Empowered Era, You’ll Need Software, Software Everywhere.” I can’t critique it because I don’t have the $499 necessary to read it but I also happen to think that’s right, but what kind of software?
The report talks about the coming reality that software is and will be even more ubiquitous in the future and interestingly it posits the emergence (according to Forrester) of “cloud cartels”—large corporations dedicated to serving the processing and storage needs of the future. We’re talking more about big data than about running ERP in the cloud. With some 22 billion attached devices by 2020 (also according to the report) spitting out second by second data, a lot of processing and storage will go to machines understanding machines.
I can buy all that but what I find harder to internalize is that the short list of winners quoted in the Times story about the report includes “Amazon, Cisco Systems, Google, I.B.M., Microsoft, Oracle and a few competitors.”
While those are all good names the list fails to mention any of the companies that started it all such as Salesforce.com. The report reveals an assumption that though the data center might be moving to the cloud the fundamental software paradigm isn’t changing. But I disagree. In my little corner of reality I think about things that haven’t been invented yet that are going to need all of that processing horsepower. Many of the companies not making the short list have a foot on the ground in the Valley and they are exciting for the novelty of the solutions they envision.
The Times article, and to a degree the report, support the kind of linear thinking that I have always criticized because the forecast looks more like a scientific experiment that keeps all variables constant save one. But in the real world systems are dynamic (yes, IT is a system) and change cascades through systems leaving no stone unturned—exactly the opposite of straight line forecasting.
If Forrester is right, and I think they are but perhaps for different reasons, then much of the processing power in the cloud will not be taken up by mundane ERP and CRM applications but by applications demanding computational answers to figure out what people want and need and what the connected devices need as well.
I am certain that the actual processing will be as different from that conducted by today’s applications as a fish swimming is different from a bird flying. I’ve lately been reading Isaacson’s “Steve Jobs” with great interest in the emphasis that Jobs put on the customer experience. Interestingly, while the book spends a great deal of time on the customer experience it is almost mute about loyalty and promoting it. Not that it matters—Jobs fixated on the customer and got loyalty and then some. Yes, we need more software in our civilization but it’s time not just to think different but to think bigger, if you ask me.













