The ambidextrous balancing act: IT-based exploration vs. exploitation

At a recent conference of information systems department chairs, there was frequent discussion of the emergence of new analytics degree programs, minors, certifications and specialties. Many university business schools are grappling with the internal university processes to get new courses approved and qualified faculty hired.

By Michael Goul  |  Chairman, Department of Information Systems

At a recent conference of information systems department chairs, there was frequent discussion of the emergence of new analytics degree programs, minors, certifications and specialties. Many university business schools are grappling with the internal university processes to get new courses approved and qualified faculty hired. We have been ahead of the curve with our Master of Science in Business Analytics program offered in partnership with the W. P. Carey School’s supply chain management department (see Chronicle of Higher Education story).

We also have a proposal for a new Bachelor of Science degree in Business Data Analytics that is moving through the ASU process and is well on its way to approval. But the advent of new analytics programs as processed and routed through academic channels is not what I am writing about today. It’s the implications of having two potentially conflicting modi operandi going on simultaneously in corporate IT departments that has me wondering about the future.

There will soon be a new cadre of analytics program graduates working side by side with graduates of our traditional information systems programs. These analytics professionals will be prepared to tackle projects that are more ad hoc in nature (prediction and discovery) than the projects tackled by their traditional IT project cousins (e.g., application updates, productivity improvements, infrastructure management, etc.).

Exploratory projects in the prediction and discovery space are more like R&D — they are basically IT-enabled expeditions because they are data-driven, but they’re intended to drive innovation, and they probably need to be managed as R&D. Traditional IT projects can be thought of as more exploitative – providing execution and operational efficiencies. I wonder — should our educational preparation address both prediction/discovery and traditional IT project tenets so that graduates can move seamlessly back and forth between these project types? Or should we prepare different cohorts for each type independently, but somehow emphasize the interdependence between the two?

Traditional IT projects are managed quite differently than are exploration projects. For example, in this month’s Computerworld, the cover story pits innovation vs. maintenance. The author refers to the latter as “keep the lights on” activities, and the discussion revolves around how much of the IT budget to allocate to each. Many of today’s CIOs emphasize keeping the lights on while still allocating budget to innovations that can serve to grow the business. After all, if the main systems are down, nobody is going to be discussing innovation. But there is some sort of yin and yang going on here; CIOs are being naturally pulled in different, but interrelated directions.

A big challenge is that technology infrastructures and data architectures can either impede or accelerate analytics projects. Therefore the analytics and traditional IT groups often need to work together. Donald Marchand and Joe Peppard offer another vantage point in the 2013 January-February issue of Harvard Business Review in a paper titled, “Why IT Fumbles Analytics.”

The paper is very direct about the need for new approaches to manage analytics projects: “In their quest to extract insights from the massive amounts of data now available from internal and external sources, many companies are spending heavily on IT tools and hiring data scientists. Yet most are struggling to achieve a worthwhile return. That’s because they treat their big data and analytics projects the same way they treat all IT projects, not realizing that the two are completely different animals” [pg. 3].

Marchand and Peppard argue that information use should be emphasized — they suggest, “… analytics projects succeed by challenging and improving the way information is used, questions are answered and decisions are made.” But what of predictive models that are intended to be taken out of the analytics lab and embedded in business processes – many of which are automated? This capacity for assimilation and application of innovation for commercial exploitation is one of the most important critical success factors, isn’t it? If so, exploration and exploitation are intertwined like nobody’s business.

Well, we probably won’t have all the answers any time soon, but IS in the W. P. Carey School has a unique vantage point for getting to work. For sure this will be an important topic of our upcoming department’s Executive Advisory Board meeting  where we always learn a great deal from our industry colleagues. And it will be a topic for ongoing faculty discussion and research. I can say that some of the world’s best-known business gurus have contemplated similar issues in relation to organizations in general.

For example, in a classic Harvard Business Review article, Charles O’Reilly and Michael Tushman discussed the work of management theory pioneer James G. March in a paper titled, “The Ambidextrous Organization.” They discovered that companies who have been successful at exploiting the present and exploring the future separated their new exploratory units from their traditional, exploitative ones, “… allowing for different processes, structures and cultures [but] at the same time, they maintain tight links across units at the senior executive level, [i.e.], they manage organizational separation through a tightly integrated senior team” [pg. 2].

The authors assert that a business doesn’t have to escape its past to renew itself for the future. It is certainly going to be an interesting next decade for business information systems, isn’t it? Stay tuned…