This is a talk about how BI develops within a startup, from simple excel files to hard core data science. The talk proposes 4 main stages that BI teams go through as a company grows.

1. The Evolution of BI in Early
Stage Startups
Presented at to
Oct 7, 2015
Montreal

2. Personal Intro
Liberal Arts
Product Manager
+ BI Dabbler
=

3. What is this talk about?
● Business Intelligence (BI) from a
product perspective - How does BI
build tech that people use?
● Organizational dynamics - How does BI
grow within a company and how does it
relate to other teams?

4. What is this talk based on?
● Using BI at Yahoo and Pollenizer
● Running BI at F&O
● Running BI at Flatbook
● BI porn addiction

5. Part 1 - So
WTF is BI?

6. This is BI
https://eng.asana.com/2014/11/stable-accessible-data-infrastructure-startup/

7. This is also BI

8. A: BI is stage
and people
dependant

9. Part 2 - The 4
Stages of BI

10. Caveats
● Stages can overlap
● Stages can be skipped

11. Stage 1 - Analysis

12. Stage 1 - Analysis
● BI = Analysis
● Data availability not a major focus
● Key team member = someone who is
good at excel (generally founder, then
analyst)
● KPI = do analysis that helps business

13. Stage 2 - Dashboards

14. Stage 2 - Dashboards
● BI = Data Availability + Visualizations
● BI now uses tech resources
● Key team member =
○ product oriented data engineer -or-
○ product oriented analyst w/ dev support
● KPI = dashboard usage
● Analysis can stay in BI or move to biz
units (product, marketing etc)

15. Stage 3 - Self Serve
ETC...

16. Stage 3 - Self Serve
● BI = Self Serve Tools + Data Warehouse
● High $$$ for tools and plumbing. . .
● But, this is the only model that scales
● Key team member = BI focused
engineers and product people
● KPI = tool usage + reduced analyst load
● Analysis should move to biz units

17. Stage 4 - Data Science

18. Stage 4 - Data Science
● BI = Data Science (Predictive Analytics)
● Some analysis is too hard for analysts, it
needs devs and math people
● Not for everyone, but high ROI for some
● Key team member = data scientists
● KPI = direct ROI to the business

19. Part 3 - So
What?

20. So what?
● Know what stage you’re at
● Know what people you have (and want)
● Grind out BI value

21. isouweine@gmail.com | @sonofsarah