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Using Data Strategy Design to Build Data-Driven Products

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Everyone is talking about Big Data, Deep Learning and Artificial Intelligence. But the reality in some companies looks different, especially when developing new products: (the relevant) data is missing. Without predictive models and recommendation systems cannot be trained and the value is consequently low. This so called cold-start problem is especially concerning startups, since without own data treasure the companies are missing a defendable unique value proposition. Successful startups solve this problem with the help of „Data Traps“ and develop products with „Data Network Effects“. What exactly stands behind these terms and how companies design their own successful and data-driven products, will be demonstrated by Martin Szugat based on samples from his occupation as Data Strategy Consultant.

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Using Data Strategy Design to Build Data-Driven Products

  1. 1. Using Data Strategy Design to Build Data-Driven Products Martin Szugat at Product Tank Munich on 26.06.2017 datentreiber.de
  2. 2. Driving your business forward. Consulting, workshops and seminars on data strategy design.
  3. 3. 1996-2008 Software developer, consultant, trainer and author Study & research of bioinformatics (Data Science) 2001-2008 Managing director & shareholder of SnipClip GmbH 2008-2013 Program director of Predictive Analytics World conferences in Germany 2014-dato Managing director & owner of Datentreiber GmbH 2014-dato Founder and director of Datengipfel academy 2017-dato
  4. 4. Drivers for AI spring:  Improved methods & open source tools  Processing power (i.e. GPU) & memory  Availability and quality of data
  5. 5. Breakthroughs in AI are mainly driven by data. Source: http://www.kdnuggets.com/2016/05/datasets-over-algorithms.html
  6. 6. How machine programs work. Data Algorithm Infor- mation
  7. 7. How machine learning works. Past Data Training Algorithm Trained Model Future Data Trained Model Infor mation
  8. 8. http://www.r2d3.u s/visual-intro- to-machine- learning-part-1/
  9. 9. What makes data valuable? Quantity (i.e instances) Density (i.e. features) Quality  Completeness  Currentness  Correctness  Reliableness  Representativity  …
  10. 10. More data means better predictions (in general). Source: https://medium.com/mmc-writes/the-fourth-industrial-revolution-a-primer-on-artificial-intelligence-ai-ff5e7fffcae1
  11. 11. „Data is the new oil.“ So what?
  12. 12. The startup founder ... … looking for data.
  13. 13. “Accessing and owning a large, domain-specific dataset to build high accuracy models can be the single hardest problem that founders need to solve in the beginning.” Source: https://medium.com/@muellerfreitag/10-data-acquisition-strategies-for-startups-47166580ee48
  14. 14. “Owning a large, domain-specific dataset can therefore become a significant source of competitive advantage […]” Source: https://medium.com/@muellerfreitag/10-data-acquisition-strategies-for-startups-47166580ee48
  15. 15. The Chief Data Officer … … is drowning in data ...
  16. 16. … but his company is … … thirsty for information.
  17. 17. Most data lakes are … … data swamps.
  18. 18. Data exploitation
  19. 19. Data refinement
  20. 20. Data utilization
  21. 21. Big Data Ansatz Big data approach: finding the needle in the haystack … … by accumulating more hay.
  22. 22. The alternative: data strategy design
  23. 23. Data utilization
  24. 24. Data refinement
  25. 25. Data exploitation
  26. 26. Data-driven business is lead by a value-oriented strategy. Exploitation Refinement Utilization
  27. 27. What‘s a „data product“? Data Algorithm Infor- mation „Data Product“ [2]: “A data product is a computer application that takes data inputs and generates outputs, feeding them back into the environment.” „Data Product“ [1]: “Customers buy the data 'product' once, and continue to use it as is.” „Data Product“ [3]: “A data product is digital information that can be purchased.”
  28. 28. What‘s a data-driven product? Data Algorithm Infor- mation It‘s valueable.It‘s unique. It‘s an unique value proposition. (model) It‘s a driven-driven product. It‘s customer needs.
  29. 29. Predicting blockbusters. Source: http://dataconomy.com/using-wikipedia-activity-data-forecast-movie-success/
  30. 30. Data Strategy Design Kit by Datentreiber
  31. 31. Data-driven Business Model Generation https://www.amazon.com/Business-Model-Generation-Visionaries-Challengers/dp/0470876417/ref=sr_1_1
  32. 32. Cinema Operator Prediction of percentage of seats sold License cost reduction Website SaaS Email Predictive Modeling Marketing & Sales Data Scientists M&S Manager HR Software Marketing Budget Monthly Pay per Cinema Hall
  33. 33. ??? Prediction of percentage of seats sold
  34. 34. Prediction of percentage of seats sold Predictive Model: Total Revenue Predictive Model: Seats Sold Wikipedia Movie Data Movie Total Revenue Figures Seats Sold per Movie
  35. 35. Wikipedia Movie Data Movie Total Revenue Figures Seats Sold per Movie Movie Name Mapping Table ???
  36. 36. Data Traps
  37. 37. Wikipedia Movie Data Movie Total Revenue Figures Seats Sold per Movie Movie Name Mapping Table Prediction Game
  38. 38. Prediction of percentage of seats sold Predictive Model: Total Revenue Predictive Model: Seats Sold Wikipedia Movie Data Movie Total Revenue Figures Seats Sold per Movie Movie Name Mapping Table Prediction Game Data WarehouseETL Tool Predictive Modeling Tool Website Development Tools Data Engineers Data Scientists Web Developers Seller: Movie Total Revenue Figures
  39. 39. Cinema Operator Prediction of percentage of seats sold License cost reduction Website SaaS Email Predictive Modeling Marketing & Sales Seats Sold per Movie HR Software Marketing Budget Monthly Pay per Cinema Hall Prediction Game Movie Name Mapping Table Prediction Game Seller: Movie Total Revenue Figures
  40. 40. Data Network Effects
  41. 41. More Data (Seats Sold) Smarter Algorithms Better Product More Clients
  42. 42. Get started. Go to www.datenstrategiedesign.de.
  43. 43. May the data be with you.
  44. 44. datentreiber.deWir treiben Ihr Unternehmen voran. Martin Szugat Managing director Telefon: +49 [0]881 12 88 46 53 E-Mail: ms@datentreiber.de Web: www.datentreiber.de Blog: www.datenstrategiedesign.de

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