That the Massachusetts Institute of Technology is one of the premier science, engineering and technology schools in the world is well established. Perhaps slightly less known is that MIT's Sloan School of Business is world class as well, bringing the school's mathematical and technology strengths to business education and research. And though Sloan's flagship journal, the MIT Sloan Management Review, might not have quite the cachet of the Harvard Business Review, I'd certainly put it on the short list of required reading for business leaders. Indeed, the latest issue on IT-Driven Innovation, the New Information Opportunity is essential for those looking at vanguard strategic developments of technology for business.
Putting the Science in Management Science?, an interview with Andrew McAfee of Sloan's Center for Digital Business, makes a strong imploration for business to adopt a scientific and data-driven approach to decision making. McAfee has arrived at this thinking from his studies on how information technology “changes the way companies perform, organize themselves, and compete”, as he investigates “how computerization affects competition itself – the struggle among rivals for dominance and survival within an industry.”
The really hard work for IT is understanding “what new possibilities have opened up, and what important constraints are gone because of this cornucopia of technology that we’re sitting on.....One of the single biggest changes that I see coming is when you have this unbelievable amount of horsepower and a mass of data to apply it to, you can be a lot more scientific about things. You can be a lot more rigorous in your analysis. You can generate and test hypotheses. You can run experiments. You can adopt a much more scientific mindset...when you compare scientific to pre-scientific approaches, there’s one clear winner over and over.”
As an illustration, McAfee notes that a number of years ago, former chess champion Gary Kasparov won 32 simultaneous matches against the then-best computerized chess technology. By 2004, he couldn't even beat good chess programs on commercially-available hardware platforms, one match at a time. Further research has demonstrated that a combination of human intuition and computer power is optimal for chess. That human/computer collaboration is a model that McAfee feels may be optimal for business as well. “We can translate that into all kinds of business environments. People get to make decisions; computers get to be part of it and to second guess and to let them know if it seems to be heading in the wrong direction. “
McAfee is very passionate about the benefits of business as science, but acknowledges the challenges as well. “It’s not easy to become more data reliant, to become more enumerate, to become more quantitatively oriented, to understand what an experiment is and what a control group is and what’s a significant difference. We’re not terribly well trained for it, most of us. And so instilling this philosophy inside an organization is a long, slow transition.....When we look at what real experimenting organizations do, they approach this in an open spirit of, 'I don’t know what the answer is, and that’s what’s really exciting. I’m going to throw something out to see if this heads us in more the correct direction or the wrong one. Based on what I learn, I’m then going to do a subsequent trial.'”
The key for business, from McAfee's perspective, is to simultaneously adopt contradictory notions of what IT should be. The first notion is imposition, wherein technology provides business the “opportunity to become even more tightly orchestrated, regimented, regulated.....If I’m in charge of an organization, I want all of my vendors to get paid via a standardized, completely repeatable process that makes sure that they are going to get paid, that there’s no fraud, and that the potential for abuse is as low as possible.”
The second is emergence, which is a foundation for business intelligence. Use technology to “get out of the way and watch what happens. Let people self-select into their roles into what they’re going to do, who they’re going to work with, what they want to share. Stop presupposing that we know what the right answer is and who should and shouldn’t be involved. What we see over and over again is that surprisingly good stuff emerges, and the bad stuff that happens is not worth worrying about.”
The imposition/emergence dialectic seems to me a lot like planning/searching conundrum I've blogged about many times. While both are critical for business success, technology and data have tipped the scales toward searching/emergence. Ultimately now, it's analytics over experts – time after time. “The main redirection I would urge is turning away from relying on HiPPOs. I forget who coined the acronym, but it’s wonderful. It means Highly Paid Person’s Opinions. These are the business gurus of the world who have been around the longest and who are relying only on their business intuition.”
Imposition, though, remains critical for implementing emergent processes, providing enterprises the means to scale their differentiated IT innovation. “The clearest part of my crystal ball about the future is that it’s going to be a busier place than the world we live in today, in a business or a competitive sense. The rate of change is only going to continue to increase. We have the ability to get smarter more quickly than we used to. The question is, when you come up with a good idea, can you impose it very broadly across your organization with technology?”
Steve Miller also blogs at miller.openbi.com.
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