Data-Driven Effectiveness Is A Team Sport

Smart people and the best technology aren't enough to drive a data-driven culture. It's all about people and collaboration, which is easier said than done. If you're serious about affecting change, consider these best practices.

Lisa Morgan, Freelance Writer

February 2, 2017

3 Min Read
Credit: Pixabay

 More Data & Analytics Live at Interop ITX
More Data & Analytics Live at Interop ITX

Most companies are trying to understand how they can make the best use of their data. They've invested in tools and they've invested in people, but the results continue to fall short of expectations. Competitors are stealing customers, disruptors are upsetting the natural order or things, and business as usual is showing diminishing returns.

Why companies fall so behind or advance so fast isn't always obvious, but there's one thing that separates the leaders from the laggards:  The leaders have integrated data driven decision-making into their culture and business processes. In fact, their ability to use data effectively is part of their core competency.

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"Legacy processes and procedures have led to really siloed organizations," said Rich Wagner, CEO of business performance forecasting solutions provider Prevedere. "The analysts within each function all operate differently. They use different tools, different techniques, and different technologies to build their business plans to run the business so they're not an integrated group."

How to Make Teamwork Work

One sign of analytical maturity is the effectiveness of cross-functional problem solving. IT likely has the data, the data team needs to surface insights for the business, and the business has to be confident that the decisions they make advance their objectives. In today's rapidly changing business environment, cross-functional teams are necessary because their collective knowledge and skills enables more effective problem solving, faster.

"You need to have a team that's focused on a shared understanding of what the business problem is and what the objective is. Do not pass go until you do that because it's a recipe for disaster," said Chris Mazzei, chief analytics officer at professional services organization EY (Ernst & Young).

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Unifying efforts doesn't just happen. Business professionals need to understand what the data team and IT do and vice versa, which is best accomplished by working together to solve a business problem.

"[T]ask a team to solve a pretty big problem with a tight deadline and let each of them see the value that the other brings," said Prevedere's Wagner.

Success may also require some self-motivation. There's significant value in spending time with members of the team that have different areas of expertise. By working together and being inquisitive, individuals can learn more about how other functions operate and why they operate that way, which is essential. Without that, important details may be overlooked.

For example, one of EY's telecom clients wanted to improve its customer retention model. So the analytics team built a new model that could accurately identify customers who would leave within two weeks. That's impressive, but marketing and sales needed four to six weeks to intervene.  

"Nobody asked the marketing and sales team how far in advance they needed to know [a customer was leaving], said EY's Mazzei. "We see that all the time."

One of the cheapest ways to understand what works and what doesn't is to hear what other companies have done right and wrong.

What's Right for Your Business?

Your company probably wants to reach a higher level of data-driven maturity in 2017, and you are part of the solution. If you want to avoid some of the common pitfalls, join Prevedere's Rich Wagner at Interop ITX  when he presents The Data Team and the Business Team: One Big, Happy Family in Las Vegas, Wednesday, May 17, 2017.

About the Author

Lisa Morgan

Freelance Writer

Lisa Morgan is a freelance writer who covers business and IT strategy and emerging technology for InformationWeek. She has contributed articles, reports, and other types of content to many technology, business, and mainstream publications and sites including tech pubs, The Washington Post and The Economist Intelligence Unit. Frequent areas of coverage include AI, analytics, cloud, cybersecurity, mobility, software development, and emerging cultural issues affecting the C-suite.

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