People who do analytical work are known for being close to data rather than being thought of as "creative". But as datasets become bigger and broader, creativity is important for analytics teams. So, how can you generate more creativity? Do you mix different people, or mix different skills in the same people? Or do we actually have the opposite problem?
Creativity among Analysts.
Analysis has to do with seeing existing patterns and accumulating evidence. It is not about creating patterns and making up features that don't exist. Excellence in analysis has to do with sharpness of eye and mental integration of what is there.
Creativity expert Linda Naiman says "creativity is characterized by the ability to perceive the world in new ways, to find hidden patterns, to make connections between seemingly unrelated phenomena, and to generate solutions...". And that sounds a LOT like what we increasingly want our analytics teams to do.
Consultant Michelle Wetzler has worked with hundreds of companies on this. She notes that the most common reason for failure in analytic projects is not lack of creativity. It's that most members of the team don't want to get near the actual data. Hmmm.
The Meat of the Data.
"Far too many companies, she says, "collect months and months of interesting data only to have it sitting in the corner gathering dust....If you can find at least one person who is...very curious about what that data might reveal...you need people on your team who enjoy the practice of analytics....if you don't have people who want to learn from your data, you won't be able to extract any value from it."
Is that what creativity in an analytic team is all about? Is it zeal to get into the meat of analysis? There are people who live in a world of numbers. Their mental furniture is made up of numbers. They see patterns in numbers that the eyes of most of would simply blur over. The consultants who put together analytic teams make the point that companies increasingly rely on a relatively scarce breed to maintain their competitive edge. They are people who can use statistics and arrange data in such a way that it can really answer business questions with validity. The best analytic teams, they say, are "working close to the business" and kept "close to each other" for purposes of coordination, mutual learning and support.
Putting Analysts to Work.
Improving analytics teams is most about putting the analytics talent into the right critical projects. Companies run the risk of relegating their best analytical minds to conduct simple analyses or to work on low value projects. Often, people who don't invest their talents in real analysis feel they can devolve the truth without looking at data. Sometimes, when that happens, the slow, isolated, ponderous work of analysis is devalued or ignored.
Sadly, the decentralized model is most often used. Analysts are scattered in different functions and different locations. This model makes the poorest use of analytic teams. Companies which do not engage analytics and in whom analysts have little management support fall into this category. In the functional model, analysts are bunched together in the functions like marketing and supply chain, where analysis is most likely to be used. This model suggests that analytics are not useful in other areas like product design.
In the consulting model, analysts work together, but serve as a kind of internal consulting group, charging their time to business units which request them. The "Center of Excellence" model builds a community of analysts who work throughout the organization, coordinated by a central entity. In the centralized model, analysts reside in one central group where they serve a variety of specific functions and in particular business units or they work on special diverse projects. This structure provides a core of organized analytic support and expertise. The central unit makes it easy to deploy analysts to high priority projects.
SwoopTalent can take away the heavy lifting of data management so your analytics team can be MUCH freer to be creative AND analytical. To learn more, contact us.
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