If you’re building your Big Data strategy based on what people are talking about today, you need to start over. Most of what’s being talked about today is relevant to today’s conditions: today’s issues and the technology that’s suitable to meet today’s challenges. Unfortunately, that’s not where your Big Data strategy unfolds. The reason it’s important to clearly define Big Data in competitive terms is to ensure your strategic implementation continually fits within the correct context. You must constantly evaluate whether or not your strategic pursuits align with your competitive definition of Big Data.

For example, we’ve already established that competitive Big Data is extremely expensive and difficult to mine by traditional means. As you well know, what’s difficult to mine today won’t be difficult to mine tomorrow. To formulate a Big Data strategy, you must start with a frame of the future and progressively fill in the details; then constantly monitor your strategy to ensure it stays within the competitive Big Data context.

There are three general approaches to building any strategy, and only one of them is correct. The first is what we just mentioned–building a strategic vision based on today’s conditions. Patrick Gray, veteran management consultant who specializes in technology, pointed out the second approach in an earlier post: Big Data: The perils of past performance. As Gray accurately points out, extending the past to anticipate the future is a common mistake in strategic planning, and should be avoided. The correct way to project out into the future is to envision what the future will look like based on an iterative process that I call cinematic visionography.

Cinematic visionography starts with a target time frame, and systematically frames the future using first a macro-economic picture, then a competitive picture, and finally an internal picture of where Big Data can be used to its maximum potential.


The biggest influences on what Big Data looks like in your strategic future, comes from your projected macro-economic setting. Projecting your macro-economic environment sets the initial frame, and subsequent iterations progressively fill in details. For instance, think about what the political, social, and technological climate will look like in 2015. Is there any chance it will look like today? Not a chance!

Regardless of your political preferences and/or projections, the next three years are certain to see changes in political policy, which will affect the way Big Data is competitively defined. For instance, privacy will continue to be a concern, and we may see more government oversight in this area, especially if the administration continues to progress down a more Democratic ideology. This is an opportunity: prohibitive regulations make it unattractive for new entrants. However, if the Republicans start exerting more influence, we may see the private sector step up to handle privacy in a more laissez-faire fashion. Again, this could be an opportunity for a new strategic alliance. These are all considerations as we start to paint our picture of the future.

Of course the biggest macro-economic influences will probably be in the social and technical areas. The 75 million millennials have already shown their proclivity for technological socialization, and as they move their way into the workforce, they will become a huge supplier of Big Data. As long as the economy doesn’t dramatically recess, the demand for social sharing will drive technological advances far beyond what we see today. Since economic growth should be a top priority for either political administration, we may even see a giant leap in the direction of social technology, making the challenges of today pale in comparison to 2015. The International Data Corporation (IDC) measured our digital footprint in 2011 at approximately 1.8 zetabytes. It’s quite possible that number could reach 6 or 7 zetabytes or more by 2015. Think about what capabilities would be necessary to support this volume of data processing in your organization.

Competitive environment

As you can see, if the initial frame painted by your macro-economic projections radically adjusts your projections of Big Data, it follows that your competitive environment will also be affected. This is the second iteration of cinematic visionography; your future competitive environment starts filling in the details of the frame initially established by your macro-economic projections. Your operational definition of competitive Big Data is of particular help in this stage, as it’s built and modeled from a competitive perspective.

Our working definition of competitive Big Data was previously defined as the massive amount of rapidly moving and freely available data that potentially serves a valuable and unique need in the marketplace, but is extremely expensive and difficult to mine by traditional means. Your Big Data strategy must create information that is “valuable and unique” to your customers, so you need to think about what will be both valuable and unique to your customers in 2015. To do this, you must first understand who your customers will be in 2015. Using a Boston Consulting Group (BCG) matrix, or any other effective strategic marketing tool, analyze your business units, and identify where your best customers are. Then depending on your overall attitude toward using Big Data in your strategy, either experiment with your questionables, or double-down on your cash cows and rising stars.

At the same time, you want to be cognizant about the capabilities that build out your strategy: they need to stay competitive. Right now, a mix of data scientists, agile processes to support an innovative culture, a high-powered Hadoop or Teradata back-end, and a SAS front-end may be the answer; however, that may not be the answer in 2015. Staying on the cutting edge is what makes and keeps you competitive. Although it’s hard to keep pace with technological advances, much less predict what technology will look like in the future, you must make some assumptions for the formulation, and constantly keep tabs during the implementation on whether or not you’re still in a competitive context. The reward for holding tight to these principles, is keeping new entrants out of your competitive space, and pushing out current competition that can’t keep up the pace.


The third and final iteration of cinematic visionography is formulating a strategy for Big Data within your organization–a topic for a future post. The importance for today is the starting point and the sequence. Don’t start by asking what Big Data can do for you today, ask what Big Data will look like tomorrow. Frame the future with macro-economic projections, and then fill in the details with competitive projections. Once you’ve completed these two iterations, you’re well positioned to understand how Big Data can push you ahead of the competition.