Baking analytics into the culture of an organization is not always the easiest thing because it doesn't come intuitively to humans. This presentation was given at Kumpul co-working space in Sanur, Bali and it involves a sharing of my team's experience in building a data-driven culture at TradeGecko.

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