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The Four Ways IT Is Revolutionizing Innovation simultaneously: measurement, experimentation, sharing and replication

By annie shum | June 4, 2010

MIT Sloan Management Review

The Four Ways IT Is Revolutionizing Innovation Michael S. Hopkins 05.21.10

There has always been a performance gap between companies that embrace technology and companies that resist it–what Erik Brynjolfsson, Schussel Family Professor at the MIT Sloan School of Management, director of the MIT Center for Digital Business and co-author of Wired for Innovation (MIT Press, 2009), calls the productivity gap between “leaders and laggers.”

What is new is that the gap has widened, and it has widened most in information-technology-intensive industries. There the leading companies, which Brynjolfsson calls “digital organizations,” know how to tap the flood of data created by information technology with a “higher information metabolism.” Here, a conversation with him on the subject.

You say that leading companies have figured out how to capitalize on technology advances and that they are using IT innovation to create a new kind of R&D.

Information technology is a catalyst for complementary changes: It’s what economists call a “general purpose technology” that can set off waves of complementary innovations. IT is setting off a revolution in innovation on four dimensions simultaneously: measurement, experimentation, sharing and replication. Each of these is important in and of itself, but, more profoundly, they reinforce each other.

Measurement, experimentation, sharing and replication. Let’s go through each of them.

Measurement has become radically improved through nano data. That includes clickstream data, Google trends, detailed e-mail data, the trillions of bits of information that are thrown off by enterprise planning systems. Even without any conscious effort on the part of the designers, this information is just generated. By studying these data very carefully, companies can have much better knowledge of their customers, of their business processes, of their product quality and of defects of their supply chains.

IT-based experimentation is the second category of innovation. It’s most obvious in companies like Amazon, which regularly conducts “A/B experiment,” testing different versions of the same Web page at the same time to different visitors, monitoring customer experience and follow-through. The big advantage of an experimental approach that uses IT is that you can get at causality in a way that you can’t with just pure measurement and observation. That’s the gold standard for being able to have actionable knowledge about what innovations are paying off.

A third thing that’s changed a lot over the past 10 years is the way that companies can share not only data but insights. The Internet and information technology are uniquely well designed for this kind of sharing, of course. An example is what happened spontaneously at Cisco Systems. The central information systems department didn’t support Macintosh computers, and there were about 10,000 users of Macs, so they set up their own wiki internally to share tips on things like how to get their Macs to work with the company’s Linux printers. It’s an effective way of sharing micro-innovations so that each person doesn’t have to reinvent the wheel or reinvent the printer routine.

The fourth change is replication. IT makes it dramatically easier to replicate and scale up innovations once they’ve been identified. The first three approaches help companies find and share new innovations, but then IT makes it possible to take that innovation and copy it many times.

You’ve found that Harrah’s, the casino company, is using IT in all four ways to drive innovation.

The chief executive there, Gary Loveman, was a Ph.D. student here at MIT with me. And I think he’s an exemplar of a new kind of senior executive. He has created a culture where employees are regularly doing business experiments and carefully measuring their results through their information systems, from tracking which discounts encourage visitors to play more expensive machines to what practices lead to higher customer service satisfaction scores for the wait staff. The successful findings are shared with business managers at other locations and then scaled up to become part of corporate policy going forward.

It’s interesting that Loveman studied at MIT. What kinds of training or changes in attitude do you think this “new kind of senior executive” will need?

One of the things that I see changing is a shift from a lot of long-term planning. Instead, there’s more sense and respond: Experiment so that you can learn about your customers’ needs, what supply chain changes could make a difference, how to redesign your products.

This is a mentality that requires much quicker cycle times. It requires people to be flexible and nimble. And it requires a set of skills that, frankly, we at business schools need to work harder at bringing together. Specifically, these managers need knowledge of business analytics, the way to understand the numbers to drive the statistics and to design intelligent experiments–but also deep knowledge of the business itself, to know how to ask the right questions.

What we’re going to see in the coming decade are companies whose whole culture is based on continuous improvement and experimentation–not just of specific processes, but of the entire way the company runs. People have called this the Great Recession, but when historians look back on this era, I think many will also call it the Great Restructuring, because of the way that businesses are changing how they’re working and because of the central role that IT has in driving some of those changes.

This article is adapted from “The 4 Ways IT Is Revolutionizing Innovation,” by Michael S. Hopkins, which appeared in the Spring 2010 issue of MIT Sloan Management Review. Copyright © Massachusetts Institute of Technology, 2010. All rights reserved.

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