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What every product manager needs to know about data science (ProductCamp Boston 2016)

Product management and data science work in close partnership at many of the highest performing organizations, which use analytics to develop better products, drive customer acquisition and retention, and create additional revenue streams. Not all organizations have the resources or desire to build an internal data science competency, but all can benefit from some degree of analytical orientation. When armed with basic quantitative literacy, product managers are often among the best positioned individuals in their organizations to recognize and build strong business cases around data related opportunities worth pursuing.

This presentation covers, through practical case studies, the information that all product managers should know about data science. Attendees will leave better able to recognize data related opportunities, understand the potential benefits and risks, build business cases for analytics, and learn more.

About Trevor Bass

Trevor Bass is a data scientist with a decade of experience building highly successful and innovative products and teams. He runs Bitten Labs, a data science management consultancy, education provider, and innovation lab. Prior to Bitten Labs, Trevor founded and built the data science function at payment processor Litle & Co (acquired by Vantiv), which performed product R&D, drove customer acquisition, retention, and upselling, provided quantitative consulting throughout the company and for its end customers, and established clear industry thought leadership. Trevor holds a Master's degree from Rutgers University and a Bachelor's degree magna cum laude from Harvard University, both in mathematics.

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What every product manager needs to know about data science (ProductCamp Boston 2016)

  1. 1. bittenlabs © 2016 What every product manager needs to know about data science Trevor Bass Bitten Labs trevor@bittenlabs.com http://bittenlabs.com
  2. 2. bittenlabs © 2016 Bitten Labs • Data science management consultancy, education provider, innovation lab • Specialize in early and growth stage data science competencies Trevor Bass • Data scientist with a decade of experience building successful products and teams in a variety of industries
  3. 3. bittenlabs © 2016 Source: xkcd.com
  4. 4. bittenlabs © 2016 Source: marriedtothesea.com
  5. 5. bittenlabs © 2016
  6. 6. bittenlabs © 2016 “We are drowning in information but starved for knowledge.” - John Naisbitt
  7. 7. bittenlabs © 2016
  8. 8. bittenlabs © 2016 “...since chocolate consumption has been documented to improve cognitive function, it seems most likely that in a dose-dependent way, chocolate intake provides the abundant fertile ground needed for the sprouting of Nobel laureates.”
  9. 9. bittenlabs © 2016 From absurdist scientific humor publication top medical journal: Messerli, Frank. “Chocolate Consumption, Cognitive Function, and Nobel Laureates.” The New England Journal of Medicine 367 (2012): 1562-1564.
  10. 10. bittenlabs © 2016 Quantitative arguments making people’s brains turn off
  11. 11. bittenlabs © 2016 #1 Data science is about insight (e.g. not information, not technology)
  12. 12. bittenlabs © 2016 +data +science Source: Drew Conway
  13. 13. bittenlabs © 2016
  14. 14. bittenlabs © 2016 #2 The best insights are actionable
  15. 15. bittenlabs © 2016 Source: xkcd.com
  16. 16. bittenlabs © 2016 Goal: data  value
  17. 17. bittenlabs © 2016 #3 Data products are awesome (and your product can probably be one)
  18. 18. bittenlabs © 2016 What is a data product? • Data products: products that derive substantial value from analytics • Data products ≠ information products Example • Information product: Google Analytics • Data product: Google Search
  19. 19. bittenlabs © 2016 “The future belongs to the companies and people that turn data into products.” - Mike Loukides, O’Reilly
  20. 20. bittenlabs © 2016
  21. 21. bittenlabs © 2016
  22. 22. bittenlabs © 2016
  23. 23. bittenlabs © 2016 #4 Pipes are key
  24. 24. bittenlabs © 2016
  25. 25. bittenlabs © 2016 Better pipes > better insights
  26. 26. bittenlabs © 2016 #5 Start with your core competency
  27. 27. bittenlabs © 2016
  28. 28. bittenlabs © 2016 #6 Data products are hard (you need data science help with everything, throughout the lifecycle and the organization)
  29. 29. bittenlabs © 2016
  30. 30. bittenlabs © 2016 #7 There is a communication gap (and you may not know it, and it matters a lot)
  31. 31. bittenlabs © 2016 “Data science is a team sport.” - DJ Patil, U.S. Chief Data Scientist
  32. 32. bittenlabs © 2016 #8 Data science literacy is important and attainable (ditto for data scientists w.r.t. product literacy)
  33. 33. bittenlabs © 2016 Data science literacy • Solving problems with data • Data • Statistics • Visualization • Data analysis methods • Toolsets Making data science work • Applying data science • Organizing data science • Maturing analytically
  34. 34. bittenlabs © 2016 #9 Good PMs copy; great PMs steal
  35. 35. bittenlabs © 2016 #10 Data science initiatives are like startups
  36. 36. bittenlabs © 2016
  37. 37. bittenlabs © 2016
  38. 38. bittenlabs © 2016 #11 Product managers are critical (for both the product and the organization)
  39. 39. bittenlabs © 2016 Data science is about insight The best insights are actionable Data products are awesome Pipes are key Start with your core competency Data products are hard There is a communication gap Data literacy is important and attainable Good PMs copy; great PMs steal Data science initiatives are like startups Product managers are critical 1 2 3 4 5 6 7 8 9 10 11
  40. 40. bittenlabs © 2016 What every product manager needs to know about data science Trevor Bass Bitten Labs trevor@bittenlabs.com http://bittenlabs.com

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