With the increased use of data in business, organizations are scrambling to mount data science teams. Because these teams are relatively new, there is no precedence on how companies should structure them, and many experts have differing opinions. Of course, the structure of the data science team will differ based on the company focus, team size, and the data itself. Companies, however, can take successful operational elements from startups and apply them to data science teams.

Because most startups fail, experts have narrowed down operational elements that are more likely to give a startup a chance to succeed. Three of these elements include using Lean and agile methodologies, instituting a flat structure, and pivoting quickly. As data science teams emerge and grow, they can adopt these three tactics to increase productivity and operate effectively.

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