By Richard Boire
For years, data and analytics capabilities have typically resided in the dark silos of organization charts. Without an enterprise view and access to other departments’ data assets or business problems, the full potential of analytics could never be realized. But today, many forward-thinking executives are realizing that the proper place for an organization’s data and analytics strategy and leadership is at the C-Suite. Beyond breaking down silos, what’s driving the imperative to approach analytics with a top-down, enterprise-wide perspective?
Consider first how very quickly analytics has evolved in just the past few years. The most significant development in this evolution is the ability to gather and analyze much more data, especially mobile, social media, and sensor data. This capability, achieved through the adoption of parallel data processing technologies, such as Hadoop and its underlying Map Reduce software (see image below), has altered the analytics landscape.
To give you some perspective on these growing data volumes, here are a couple of statistics from a September 30, 2015 Forbes magazine article:
- 1.7 megabytes of information will be created every second by each human being on the planet by the year 2020.
- Data will grow from 4.4 zettabytes today to around 44 zettabytes, or 44 trillion gigabytes, by 2020—a tenfold increase.
Clearly, the old data science approach of “asking for all the data” no longer applies. There is simply too much data that would be irrelevant for a given business problem or challenge. At the same time, access to larger amounts of data means we can solve many more business problems. Data itself no longer provides a strategic advantage. Instead, strategic advantage results from creating the right information environment to solve the specific business problem or challenge.
Data-driven corporate strategies are now the norm, which means that the C-suite must assume leadership in big data analytics. Through data leadership at the top, big data and analytics can become embedded in the corporate culture. However, in shifting to a much stronger data analytics culture where analytics is cross-fertilized throughout an organization’s departments, new skillsets and knowledge are also required.
For example, in addition to technical and mathematical capabilities, data scientists need to develop a better understanding of the business application that their solution is designed to address. Meanwhile, the business practice users should no longer completely rely on the data scientists for their expertise on data and advanced analytics. Business users don’t need to be able to develop programming code, but they do need to have enough understanding of the nuances of the data to be able to solve business problems sufficiently. At the same time, they need to understand advanced analytics at least to the extent of how it might be used to solve a given business problem. They need to know how to interpret results but not necessarily understand the arcane math behind a certain machine-learning algorithm.
Analytics practitioners who touch on both the data science area and the business area are essentially hybrids who marry the left brain with the right brain (see image above). As hybrids gain a broader or generalist perspective on analytics, they become spokespeople, thought leaders, and evangelists, explaining how a given analysis was conducted and how it will be applied.
But this generation of hybrids requires a stronger C-suite involvement in creating the right infrastructure and corporate structure/flow. As the industry evolves into higher and more advanced forms of machine learning and in particular artificial intelligence, the demand for hybrids will be even more pronounced. And the key to creating more of these versatile, ambidextrous hybrids will lie in the C-suite’s continued commitment to big data analytics top-down, and enterprise-wide.
Richard Boire is Senior Vice President of the Boire Filler division of Environics Analytics, a marketing and analytical services company.