Building a Data-Driven Culture
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The document discusses building a data-driven culture, emphasizing the need for centralized data and a systematic growth team approach. Key learnings include having an executive champion, centralizing data sources, planning value milestones, and ensuring processes are replicable. It highlights the importance of data in decision-making and mentions examples from companies like HubSpot and Airbnb.
![If 1 book represents 1 petabyte of data…
50 Petabytes
All the worlds data (books, webpages,
videos, songs, etc.) between 4000BC
and 2006AD.
24 Petabytes
Amount of data processed daily by
Google alone in 2008.
[1]
[2]](https://image.slidesharecdn.com/data-drivenculturev2-160412112118/85/Building-a-Data-Driven-Culture-3-320.jpg)
![“We are drowning in data but
starved for information”
~ Gary Cokins [3]](https://image.slidesharecdn.com/data-drivenculturev2-160412112118/85/Building-a-Data-Driven-Culture-4-320.jpg)
![Starting a Growth Team
SystemiseBrainstorm Prioritise Testing AnalyseImplement [4]](https://image.slidesharecdn.com/data-drivenculturev2-160412112118/85/Building-a-Data-Driven-Culture-6-320.jpg)
![Building a Growth Team
SystemiseBrainstorm Prioritise Testing AnalyseImplement
Key Learning #1:
Have an executive champion
[4]
[5]](https://image.slidesharecdn.com/data-drivenculturev2-160412112118/85/Building-a-Data-Driven-Culture-7-320.jpg)
![Sources
[0] Icons from the Noun Project
Title slide: Data Planning and Data Network by Ivan Colic
Slide 6: Advocate by Lorie Shaull
Slide 7 & 8: Database by Shmidt Sergey, Group by Alexandr Cherkinsky, Graph by Vicons Design
Slide 9 & 10: App analytics by Sergey Novosyolov
Slide 11 & 12: Reporting by Alfredo Hernandez, Repeat by Pantelis Gkavos
[1] Kelly Kevin, 2006. http://www.nytimes.com/2006/05/14/magazine/14publishing.html?pagewanted=all&_r=0
[2] Dean and Ghemawat, 2008. http://dl.acm.org/citation.cfm?doid=1327452.1327492
[3] Gary Cokins, 2013. http://www.forbes.com/sites/jeffthomson/2013/10/30/why-cfos-are-drowning-in-data-but-
starving-for-information/#29968dd52623
[4] Brian Balfour, 2014. http://www.coelevate.com/essays/growth-process-first-tactics-second
[5] Josh Schwarzapel https://medium.com/android-news/how-to-start-a-growth-team-ff70cd29c0f2#.uls9ubea6](https://image.slidesharecdn.com/data-drivenculturev2-160412112118/85/Building-a-Data-Driven-Culture-16-320.jpg)
Building a Data-Driven Culture
- 1. Building a Data Driven Culture By Lucas Neo
- 2. If 1 book represents 1 petabyte of data… 50 Petabytes 24 Petabytes
- 3. If 1 book represents 1 petabyte of data… 50 Petabytes All the worlds data (books, webpages, videos, songs, etc.) between 4000BC and 2006AD. 24 Petabytes Amount of data processed daily by Google alone in 2008. [1] [2]
- 4. “We are drowning in data but starved for information” ~ Gary Cokins [3]
- 5. Influencers of Data-driven Growth Brian Balfour, VP of Growth @ Hubspot Andy Johns, VP of Growth @ Wealthfront (previous Growth PM at Facebook, Twitter, Quora)
- 6. Starting a Growth Team SystemiseBrainstorm Prioritise Testing AnalyseImplement [4]
- 7. Building a Growth Team SystemiseBrainstorm Prioritise Testing AnalyseImplement Key Learning #1: Have an executive champion [4] [5]
- 8. Encounters with Disparate Data Multiple sources of data from apps Managed and used by separate teams To produce reports and make decisions
- 9. Encounters with Disparate Data Multiple sources of data from apps Managed and used by separate teams To produce reports and make decisions Key Learning #2: Centralise your data
- 10. Generating Wins Dashboards for key metrics Revamping event tracking Centralising data sources Creating prediction models
- 11. Generating Wins Key Learning #3: Plan your value milestones Dashboards for key metrics Revamping event tracking Centralising data sources Creating prediction models
- 12. Build a Process Standard data science flow Automated data extraction and cleaning Educating the company on SQL and data
- 13. Build a Process Standard data science flow Key Learning #4: Make it replicable Automated data extraction and cleaning Educating the company on SQL and data
- 14. Recap #1 Have an executive champion #2 Centralise your data #3 Plan your value milestones #4 Make it replicable
- 15. What’s next for us? Matrix Organisational structure Build a growth machine Airbnb has a data scientist in every team Hubspot’s growth machine by B. Balfour
- 16. Sources [0] Icons from the Noun Project Title slide: Data Planning and Data Network by Ivan Colic Slide 6: Advocate by Lorie Shaull Slide 7 & 8: Database by Shmidt Sergey, Group by Alexandr Cherkinsky, Graph by Vicons Design Slide 9 & 10: App analytics by Sergey Novosyolov Slide 11 & 12: Reporting by Alfredo Hernandez, Repeat by Pantelis Gkavos [1] Kelly Kevin, 2006. http://www.nytimes.com/2006/05/14/magazine/14publishing.html?pagewanted=all&_r=0 [2] Dean and Ghemawat, 2008. http://dl.acm.org/citation.cfm?doid=1327452.1327492 [3] Gary Cokins, 2013. http://www.forbes.com/sites/jeffthomson/2013/10/30/why-cfos-are-drowning-in-data-but- starving-for-information/#29968dd52623 [4] Brian Balfour, 2014. http://www.coelevate.com/essays/growth-process-first-tactics-second [5] Josh Schwarzapel https://medium.com/android-news/how-to-start-a-growth-team-ff70cd29c0f2#.uls9ubea6
- 17. End / Fin