Part II: The Artistry Required for Data Science Wins

In the second episode of this three-part series, Jacey Heuer helps us dive into the evolving roles and responsibilities of data science. We explore how individuals and organizations can nurture how data is purposefully used and valued within the company.

Show Highlights

In the second episode of this three-part series, Jacey Heuer helps us dive into the evolving roles and responsibilities of data science. We explore how individuals and organizations can nurture how data is purposefully used and valued within the company. 

Missed the first part? Listen to Part I.

Individual Takeaways
  • Adopt a scientific mindset: The more you learn, the more you learn how much more there is to know.
  • Hone storytelling capabilities to engage and build relationships that ensure the lifespan and value of data is woven into the culture.
  • Set one-, five-, and 10-years goals and aim to achieve them in six months to fail fast and advance the work faster than expected.
  • Create buy-in using the minimum viable product (MVP) or proof of concept approaches.
  • Prepare to expand your capabilities based on the maturity and size of the team focused on data science work. As projects develop, you’ll move from experimenting and developing prototypes to developing refined production code.
Organizational Takeaways
  • When your company begins to use data analytics, roles and responsibilities must expand and evolve. Ensure your people have opportunities to grow their capabilities.
  • Data must be treated as an “asset” and viewed as a tool for innovation. It can’t be tacked on at the end. Ideally, it plays a role in both new and legacy systems when aggregating data and capturing digital exhaust.
  • Engage and find common ground with all areas of business by helping them comprehend how data science "expands the size of the pie" rather than take a bigger slice.
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