Comment: How Big is Your Big Data Universe: A Lesson from the Men in Black
by Cary Burch*
So you want to introduce Big Data in your organization. Yet how big will your Big Data universe be? Will it be large, sweeping, and all-encompassing? Or will it be small enough to fit on Orion’s Belt? (See the movie Men in Black ..Ed)
This post is the first of many to come regarding the organization of the future, something I like to call The Org 3.0. When we look to the future of our workplace, Big Data will have a primary seat at the table. Getting there, however, will not be without its challenges. The first of which is to thus define our Big Data universe, or perhaps more pointedly, which areas of the business we wish to impact.
One of the key features of Big Data when comparing to other forms of analytics is its unstructured nature, yet that does not mean the approach to adopting big data has to be as well. While normally big data is first introduced to the organization via a leader’s pet project or other skunk works operation, to truly succeed with Big Data we must embrace a holistic view of its possible application from the beginning. Put another way, Tom Davenport in Big Data @ Work reminds us that:
“Targets means that organizations need to select where they are going to apply big data and analytics within their businesses… At a high level, will the resource be applied to supply chain decisions, customer decisions, financial decisions, human resource decisions, or some other area?… Rarely do organizations make a concerted attempt to determine what the most important or strategic [Big Data] project would be before beginning work on something.”
If we are going to understand how Big Data should impact our business, we must first understand how that’s even possible with Big Data. The organization of the future will very likely include a c-suite position dedicated to Big Data, but how do we decide just what facets of our enterprise should be contained within its microcosm? Here are some key points to consider:
Internal vs External Environment. A traditional SWOT analysis – the sort of thing requiring no additional work on the behalf of leadership as it remains a core component of any enterprise strategy – can be a great first place to look to determine whether your focus will be on tackling the business’ internal or external environment. Key decisions in this instance include whether the focus will be on strengths and weaknesses, or on opportunities and threats.
Activity vs Reward Systems. Do we want Big Data to change the way we do business? Or do we want Big Data to change the way we identify what systems and processes are already working well? Key decisions here include whether Big Data is to affect process excellence, performance management, or a combination of the two.
Dedicated Team vs Everyone’s Business. Traditional analytics, or what the experts dubbed Small Data Analytics, concerns the tabular data models, OLAP cubes, KPIs, and performance dashboards of today. The proliferation of analytical tools, atop the proliferation of resources around analytical thinking has meant that small data analytics has become everyone’s job. Key decisions to make here include whether we feel the same should be a key pursuit of Big Data.
Value Proposition vs Business Model. One way of looking at how technology such as Big Data can impact the business model is via The Innovation Matrix. Yet even as we determine the proper alignment between technology and the business model we must still consider both the efficacy and point of that alignment. Key decisions more pointedly include determining whether we choose to introduce Big Data to enhance our value proposition to customers, or to change the way we generate revenue.
Asset Contribution vs Asset Creation. It may also be meaningful to augment our thinking around the paradox of value proposition versus business model innovation. To do this teams must consider whether entering Big Data is with the intention to contribute toward existing enterprise assets with such examples as increasing the understanding of key customer segments, or whether the technology developed around Big Data is to become a stand-alone enterprise asset. Key decisions in this area include a determination of how Big Data is to impact competitiveness, and/or whether Big Data will simply become an additional space where the enterprise shall eventually compete.
As we consider these key decisions, and to give us some additional context around how we make these decisions, I recently interviewed Dr. Justin Barclay – professor of critical thinking and change management at Walden, Grand Canyon, and South Universities – who had this to say:
“The opportunity with Big Data lies not only in a chance to expand the absorptive capacity of an enterprise’s relative teams, the opportunity equally lies in inspiring lasting change through a multitude of new data sources and ways of both thinking about and acting upon the insights created through the use of Big Data. What is pivotal to remember, however, is the size, scope, and speed of change is predicated on the team’s sensemaking ability. Only after the team has had a chance to perceive a change, process what that change means for them, and incorporate that change into their daily work meaningfully, can such efforts as realigning strategic objectives and relevant reward systems create any lasting impact.”
So you see, the Men in Black movie provides us an important lesson regarding Big Data. Namely, that size and scope are relative. They are relative to your business, relative to your value proposition, relative to your systems, relative to your people, and most importantly relative to your business model. Only you can properly define your Big Data universe, and the beauty of it is there is no wrong answer. The size of your Big Data universe is only what you determine it to be.
* Cary Burch is the Senior Vice President of Innovation at Thomson Reuters Corporation. Prior to taking on the lead innovation role for TR, he was recently President & Managing Director of Thomson Reuters Elite.