Every Organization Needs a Data Analytics Champion
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For analytics to gain widespread acceptance and usage across an organization, an analytics champion can play an important role.
By Jack Rosenberger
As part of a self-directed, professional effort to increase my knowledge and understanding of data analytics, I've been reading most everything I encounter online about the subject. One timely blog post that recently grabbed my attention is "Fostering an Analytics-Driven Culture" by Steve Leung, a director at TIBCO Software, in which he writes about how to use data analytics to empower the workforce across an entire organization.
To accomplish this, Leung advocates that every organization have "an analytics champion," someone who supports the use of data analytics in decision-making and actively promotes its use throughout an organization.
If you think your organization needs an analytics champion, Leung advises that this person be "a widely respected senior executive who can clearly communicate the benefits" of data analytics for different departments across the organization. In smaller or growing companies where the appropriate senior executive talent is unavailable, it's also possible for a rising and well-liked star to play the role of analytics champion.
Leung isn't the only blogger to comment about the need for an analytics champion. In "How to Become an Effective Champion of Analytics," Eric Stephens writes about the necessity of an analytics champion, which he describes as being "an evangelist preaching the gospel of how data can be used to solve widespread problems."
If you want to be the analytics champion for your organization, or if you know someone in your organization that would be ideal for this role, here are five key ideas about what an analytics champion needs to do:
Use analytics to improve business decisions.
For analytics to be accepted and actively used across an entire organization, its business value needs to be demonstrated. Which means the analytics champion needs to show how analytics improves business decision-making. For this reason, Leung suggests "it's helpful to have an analytics champion whose primary focus is as a line-of-business leader. This leader can help demonstrate how analytics can strengthen decision-making, not just for data scientists but also for other leaders, accountants, HR, operations, logistics and IT professionals."
When analytics is being introduced in a department, there is bound to be some naysayers, passive-aggressive behavior and outright resistance. But it can be overcome. When CNA Insurance began using analytics to help identify fraud a few years ago, Tom Scott, head of its special investigations unit, told Computerworld, "we had pushback from our own people, especially those who had been doing the job a long time and were used to using their own intuition… We had to make it clear that we weren't replacing them with technology but that technology was augmenting what we do. It's a two-part arsenal."
Get people involved.
Include key people in a department or across the organization in the development of an analytics culture. You can accomplish this, as CNA Insurance did, by having these individuals help select analytics tools and be test users of data models before a launch. By including influential or pro-data people in the analytics process from the beginning, and by actively seeking their advice and expertise, they are naturally more inclined to commit to the project and to buy into analytics usage.
Make analytics widely accessible.
For analytics to thrive across an enterprise, it needs to be available to the CEO and other C-suite leaders as a self-service data dashboard on his or her iPad for immediate decision-making. It also needs to be available as a self-service for marketing, HR and other departments, so they can explore the data for themselves, develop business intelilgence, and discover new developments and trends as they happen in real-time.
Publicize your victories.
This last tip comes from Eric Stephens. If you don't let others know how analytics helped improve the business, you're not fulfilling your role as an analytics champion. When an analytics project produces actionable data or new insights, you must tell others how that data was used to take advantage of new developments, make improvements in efficiency, and reduce or eliminate costs. Those are the type of success stories that help analytics gain widespread acceptance.
Finally, if you want to create a culture of data analytics in your organization, do what an increasing number of data-based outfits do: let employees know that their performance evaluations and bonuses will be based, in part or in whole, on their use of analytics. Salary-related announcements like that tend to get people's attention.
About the Author
Jack Rosenberger is the managing editor of CIO Insight. You can follow him on Twitter via @CIOInsight. To read his previous CIO Insight blog post, “Dell: CIO: Don't Ask Employees What They Want," click here.