Will Big Data Replace Strategy?

First published December 27, 2012 in Mediapost’s Search Insider

Anyone who knows me knows I love strategy. I have railed incessantly about our overreliance on tactical execution and our overlooking of the strategy that should guide said execution. So imagine my discomfort this past week when, in the midst of my following up on the McLuhan theme of my last column, I ran into a tidbit from Ray Rivera, via Forbes, that speculated that strategic management might becoming obsolescent.

Here’s an excerpt: As amounts of data approaching entire populations become available, models become less predictive and more descriptive. As inference becomes obsolete, management methods that rely on it will likely be affected. A likely casualty is strategic management, which attempts to map out the best course of action while factoring in constraints. Classic business strategy (e.g., the five forces) is especially vulnerable to losing the relevance it accumulated over several decades.

The crux of this is the obsolescence of inference. Humans have historically needed to infer to compensate for imperfect information. We couldn’t know everything with certainty, so we had to draw conclusions from the information we did have. The bigger the gap, the greater the need for inference. And, like most things that define us, the ability to infer was sprinkled through our population in a bell-curved standard distribution. We all have the ability to fill in the gaps through inference, but some of us are much better at it than others.

The author of this post speculates that as we get better and more complete information, it will become less important to fill in the gaps to set a path for the future — and more important to act quickly on what we know, correcting our course in real time: With access to comprehensive data sets and an ability to leave no stone unturned, execution becomes the most troublesome business uncertainty. Successful adaptation to changing conditions will drive competitive advantage more than superior planning.

Now, just in case you’re wondering, I don’t agree with the premise, but there is considerable merit to Rivera’s hypothesis, so let’s consider it using a fairly accessible analogy: the driving of a car. If we’re driving to a destination where we’ve never been before, and we don’t know what we’ll encounter en route, we need a strategy. We need to know the general direction, we need a high-level understanding of the available routes, we need to know what an acceptable period of time would be to reach our destination, and we need some basic strategic guidelines to deal with the unexpected – for example, if a primary route is clogged with traffic, we will find an alternative route using secondary roads. These are all tools we use to help us infer what the best way to get from point A to B might be.

But what if we have a GPS that has access to real-time traffic information and can automatically plot the best available route? Given the analogous scenario, this is as close to perfect information at we’re likely to get. We no longer need a strategy. All we need to do is follow the provided directions and drive. No inference is required. The gaps are filled by the data we have available to us.

So far, so good. But here is the primary reason why I believe strategic thinking is in no danger of expiring anytime soon. If strategy was only about inference, I might agree with Rivera’s take (by he way, he’s from SAP, so he may have a vested interest in promoting the wonders of Big Data).

However, I believe that interpretation and synthesis are much more important outcome of strategy.  The drawback of data is that it needs to be put into a context to make it useful.  Unlike traffic jams and roadways, which tend to be pretty concrete concepts (stop and go, left or right — and yes, I used the pun intentionally), business is a much more abstract beast. One can measure performance indicators ad nauseam, but there should be some framework to give them meaning. We can’t just count trees (or, in the era of Big Data, the number of leaves per limb per tree). We need to recognize a forest when we see one.

Interpretation is one advantage, but synthesis is the true gold that strategic thinking yields. Data tends to live in silos. Metrics tend to be analyzed in homogenous segments (for example, Web stats, productivity yields, efficiency KPIs). True strategy can bring disparate threads together and create opportunities where none existed before. Here, strategy is not about filling the gaps in the information you have, it’s about using that information in new ways to create something remarkable.

I disagree most vehemently with Rivera when he says: While not disappearing altogether, strategy is likely to combine with execution to become a single business function.

I’ve been working in this business for going on three decades now. In all that time, I have rarely seen strategy and execution combine successfully in a single function (or, for that matter, a single person). They are two totally different ways of thinking, relying on two different skill sets. They are both required, but I don’t believe they can be combined.

Strategy is that intimately and essentially human place where business is not simply science, but becomes art. It is driven by intuition and vision. And I, for one, am not looking forward to the day where it becomes obsolescent.

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