A recent Harvard Business Review blog suggests that successful analytics efforts are largely based on the quality and the uniqueness of the data that’s used and less dependent upon the people and programs that are used to make sense of the information. While the quality of the data that’s used is absolutely essential to achieving successful outcomes, what ultimately delivers superior results is a careful blending of the right data, tools, and people skills.
As data management continues to move closer to real-time execution, data quality issues remain top of mind for many practitioners. The ability for analysts to be able to make sense of this information quickly and make it applicable in business terms for key decision-makers is critical to helping business leaders act on relevant information quickly. In turn, these capabilities can help an organization to obtain a competitive edge, whether this involves identifying an emerging market opportunity ahead of industry rivals or discovering and reacting to the root causes of customer churn in a particular region.
Of course, if an organization is simply using common data that other companies have access to, as HBR blogger and Houston Rockets General Manager Daryl Morey speaks to in the column – then it will be hard-pressed to achieve a competitive advantage.
Morey points out that fresh analysts are “minted” each year and that sports teams are hiring them in big numbers. Morey contends that “if talented analysts are becoming plentiful, however, then it follows that analysts cannot be the key to creating a consistent winner, as a sustainable competitive edge requires that you have something valuable AND irreplaceable.”
The blemish in Morey’s argument is that better, unique data is ultimately the only real competitive differentiator. Granted, if sports teams – or for that matter retailers, banks, energy companies, etc. – hired analysts who each evaluated and approached the use of data the same way, then even the brightest analysts wouldn’t offer their organizations a competitive edge.
However, what if a savvy analyst for, say, a fashion retailer has the vision and wherewithal to examine data in a fresh and unique way that hasn’t been considered by the retailer’s competitors? And, what if the analysis helps yield compelling business results – such as identifying an opportunity to target an underserved demographic? Then it wouldn’t be so far-fetched to suggest that analysts can also help organizations be more competitive.
Of course, another critical component to supporting this three-legged stool is the effective use of the right tools to help harness data successfully and apply it properly.
Clearly, using the right data is critical to a winning strategy. But in order to develop a well-rounded approach to analytics, good data is ultimately just one piece of the puzzle.
