We know that there are generally very few new ideas. I remember how crestfallen I was when, in a previous life, a friend and colleague of mine (Bill Blitch – who hired me into American Software, Inc.), appraised me of this fact. “Andrew”, he said, “there are not many new ideas – just lots of old ideas re-connected in new ways that leads to what some might think as new ideas”. I was about 30 or 31 years old, and keen as mustard to make my place in the world. My head was brimming with ideas and goals and missions and then here was my new boss, telling me this. I was not a happy camper.
It turned out that Bill was preparing me for a fun carrier nonetheless. If it were not for Bill, I would not have learned how great the country I now call “home” is, and the people within it too. I would not be here if it were not for that wise man. But, notwithstanding Bill’s lament, I have had the good fortune of being part of seeing some pretty interesting (and in some cases, new) developments at Gartner. MDM is not really new – the problem is as old as we are (or almost). But recently Gartner set about trying to put a framework around another problem that has plagued business for the last few years. We all know that there is too much data; and we all know that data needs to be made information for us to get value from it. But what happens when there is just too much information?
Tom Austin shared an interesting article on this point: Data Mining Isn’t a Good Bet For Stock-Market Predictions, posted August 8th, on The Wall Street Journal. The premise of the research cited in the article is this:
The stock market generates such vast quantities of information that, if you plow through enough of it for long enough, you can always find some relationship that appears to generate spectacular returns — by coincidence alone. This sham is known as “data mining.”
Given the inexorable and increasing rate of data, and information growth, how will the winning business of the future dictate its own terms of success? The idea that emerged, led by Yvonne Genovese, is called Patter-based Strategy (PBS). From, Introducing Pattern-Based Strategy:
The environment after the recession means business leaders must be more proactive in seeking patterns from conventional and unconventional sources that can positively or negatively impact strategy or operations, and set up a consistent and repeatable response by adjusting business patterns.
This research uniquely weaves together some pretty interesting stuff; pattern recognition; the emerging understanding of “collectives”; command and control; performance based management; operational rhythm, transparency, and more. For a really wild ride, and to get a sneak peak into some really new stuff emerging at Gartner, you need to watch for Pattern-based Strategy:
- Balance Investment in Four Categories to Support Pattern-Based Strategy, led by Tom Austin
- Five Eras of IT Business Value Add: From Automation to Pattern-Based Strategy, led by Tom Austin
- CEO’s and Chief Strategy Officers: Balance Investment with Pattern-Based Strategy, led by Betsy Burton
So Bill was pretty much right – there are very few new ideas. At least I have the pleasure of calling Bill (and his lovely wife, Sue), “friends” and I have much to thank them for.
Pattern-based Strategy is a good example of one of those rare new ideas that was given a chance.
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