How to Run an Exceptional Data Science Team

Was it because the insight wasn’t clear enough, or because your team didn’t have the appropriate business context when developing the insight?Seasonings for successYou’ll also need the following seasoning elements to make sure your data science team stays exceptional.

Partnership.

The front and back of the house must work well with each other.

For example, strong relationships with data architects and data engineers mean ready access to well-prepared data.

Having the recruiting team in your corner means access to the talent you need.

Close partnerships with consumers of your analytics will help your team better understand their businesses.

Leadership.

Data science leaders should promote a vision that sets the direction for the team and aligns the team with the consumers.

That vision should crisply convey to consumers of analytics the value that can be produced.

That value will ultimately come from the team’s ability to unlock value from data through data science.

For instance, at Credit Sesame, our team’s vision is to improve credit wellness by unlocking the value of our data through data science.

Sponsorship.

Strong executive sponsorship is necessary to promote a data-driven culture, where everyone understands that producing game-changing insights requires time, resources, and investment.

Sponsorship means data scientists are less likely to be treated as short-order cooks who only deliver dashboards and reports, instead of serving as thought leaders who drive strategy.

Virtuous cycle of data science greatnessTakeawayDiners can count on their favorite restaurants to serve up well-prepared deliciousness.

To guide your data science team to greatness, take a cue from the great restaurants.

❶ Understand your consumers’ needs, their AQ, and their businesses.

❷ Source, store, and properly prep data with the right equipment.

(Yes, foraging may be necessary!)❸ Use the right techniques and skills to create work product that delights and nourishes your consumers.

Avoid empty calories!❹ Present your work so it’s approachable.

Deliver it promptly.

❺ Get feedback.

If it’s not explicit, look for clues that indicate feedback.

Go back to the first point.

Rinse, repeat.

Finally, add three more seasonings to complete your recipe for success:PartnershipLeadershipSponsorshipWant to build a Michelin 3-Star data science team?.Use this five-step framework, add the three seasonings above, and your team will consistently serve up hot, delicious business insights that delight your consumers.

References[1] Image credit: “The backbone of the flavor network.

” by Yong-Yeol Ahn, Sebastian E.

Ahnert, James P.

Bagrow, and Albert-László Barabási in the journal Nature is licensed under CC BY 3.

0.

[2] Niko Mohr and Holger Hürtgen.

(April 2018).

“Achieving business impact with data: A comprehensive perspective on the insights value chain.

” Digital McKinsey.

[3] Inspiration for spaghetti charts: C.

N.

Knaflic, “Strategies for avoiding the spaghetti graph” (2013), Storytelling with Data.

Messy spaghetti image credit: © Jose Luis Stephens / Adobe Stock.

Twirled spaghetti image credit: © denio109 / Adobe Stock.

Further ReadingBuilding an Analytics-Driven OrganizationBuilding an effective analytics organizationBecoming an analytics-driven organization to create valueStorytelling with data blogAn Economist’s Guide to Visualizing DataThe Power of VisualizationAbout the AuthorsRaj DevRaj is Head of Talent at Credit Sesame.

He’s an evangelist for using data science and analytics to make people decisions.

Raj was VP of Talent Acquisition and Analytics at Tesla, and prior to that, SVP of Insights & Analysis at Wells Fargo.

Raj holds an M.

B.

A.

from the Yale School of Management.

Ihsan KurtIhsan is VP of Data Science and Analytics at Credit Sesame.

Ihsan was Senior Director of Data Science and Analytics for Home Depot’s online business.

He has built Data Science and Analytics teams in small and large organizations.

Ihsan holds an M.

S.

in Management Science from Purdue University.

Matthew RaphaelsonMatthew is a management consultant specializing in strategic planning and finance, using analytics and data science to solve business problems.

He is Chair, Financial Applications at ProbabilityManagement.

org, and holds an M.

B.

A.

from the Stanford Graduate School of Business.

Design and diagrams done by Corrina Reff of Riddlesticks Creative.

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