MeetVibe at Big Data Toronto

1. SMALL DEVICES, BIG DATA AND DECISION MAKING
Big Data, Metro Toronto Conven;on Centre
June 15, 2016
Mircea Baldean

2. -Daniel Kahneman
Author of Thinking Fast and Slow
“
”
You can look at a pain;ng all
you want, but asking about its
provenience is usually a good
guide whether the pain;ng is
genuine or not.

3. THE MAP AND THE TERRITORY
A Primer in Decision Making
Small Devices, Big Data
Understanding Data
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2
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4. A PRIMER IN DECISION MAKING
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5. A PRIMER
Before We Start
We tend to be op;mis;c about the
things that are important to us...

6. A PRIMER
Noise vs. Signal: Law of Small Numbers
Source: Michael J. Mauboussin, “Capital Ideas Revisited-Part 2,” Mauboussin on Strategy, 2005.
Heads or Tails?
Short-term results show mostly noise:
50/50 normalized results

7. A PRIMER
Inside View vs. Outside View
The Inside view is based on intui;on.
The Outside view will, at least, gives us
a ballpark.
Which one will you act upon?

8. A PRIMER
Why is Change so Hard to Implement?
Big data implies changes within most
ins;tu;ons. In the context of changes
or reforms, there will be losers and
there will be winners.
You can know ahead of ;me that the
poten;al losers will fight harder than
the winners.

9. A PRIMER
Why is Change so Hard to Implement?
Losses hurt roughly twice as much
as gains feel good!
Source: A. Tversky and D. Kahneman, “Prospect Theory”, 1979. Chart: SSgA, “The Exchange”, 2011.

10. A PRIMER
Why is Change so Hard to Implement?
Unlike Google, most organiza;ons do
not experiment. Few employees agree
with each other, and in fact their views
can differ by as much as 45-50%.
And many organiza;ons don't even
know that!
Source: D. Kahneman, “Big data, intuiPon and decision-making in finance”, Santa Fe InsPtute, 2015.

11. A PRIMER
Inside View vs. Outside View
Experience does not bring Convergence,
it increases Confidence.
Focus on beder insights and
fewer blind spots.
Source: D. Kahneman, “Big data, intuiPon and decision-making in finance”, Santa Fe InsPtute, 2015.

12. A PRIMER
Inside View vs. Outside View
In the knowledge economy making
beder decisions is key.
The rest is increasingly becoming
automated anyways.

13. SMALL DEVICES, BIG DATA
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14. SMALL DEVICES, BIG DATA
Small Devices, Big Data
“Big Data” represents techniques and
technologies that make handling data at
extreme scale affordable.
Source: Forrester Research, Inc. The PaSerns Of Big Data, June 2013.

15. SMALL DEVICES, BIG DATA
Small Devices, Big Data
Mobile is all about opportunity.
Technology and social connec;vity
should be seamless.

16. SMALL DEVICES, BIG DATA
Mobile Web vs. Apps
Mobile Web is
transac;onal.
Apps have a
specific intent
and a much richer
experience.

17. SMALL DEVICES, BIG DATA
Mobile Web vs. Apps
Mobile is mul;-dimensional:
Loca;on, Proximity, Immediacy

18. SMALL DEVICES, BIG DATA
Value of Big Data
Web and Mobile sta;s;cs are by far
the most measurable and accurate
source of marke;ng data available.

19. SMALL DEVICES, BIG DATA
Value of Big Data
However, the most common obstacle to
successful analy;cs is not technology,
but rather cross-team integra;on.

20. SMALL DEVICES, BIG DATA
Handling Big Data
Data doesn't age well.
Don't make bad decisions using bad data.

21. SMALL DEVICES, BIG DATA
Handling Big Data
Invest in
tracking
Leverage
the data

22. UNDERSTANDING DATA AT MEETVIBE
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23. UNDERSTANDING DATA
MeetVibe is about connec;ng people
and ideas.
We give them access to the world
around them: people, places,
rela;onships, interac;ons and
meaningful connec;ons.

24. More importantly, people choose
MeetVibe because they trust us with
their privacy.
To simplify scheduling, we provide a
convenient and safe way of viewing the
available ;mes.
UNDERSTANDING DATA

25. UNDERSTANDING DATA
Understanding Data at MeetVibe
Proprietary Real-Time BI Dashboard
App Store Analy;cs
Google Analy;cs
Proximity / Loca;on-based CMS Social Analy;cs
Email Analy;cs
SalesForce.com
Project Management Analy;cs
Hub-and-Spoke Model

26. UNDERSTANDING DATA
Understanding Data at MeetVibe
Proprietary Real-Time BI Dashboard

27. UNDERSTANDING DATA
Understanding Data at MeetVibe
Footprint, App Versions

28. UNDERSTANDING DATA
Understanding Data at MeetVibe
Proximity InteracTons

29. In analy;cs, success is dependent upon
asking the right ques;ons.
Some;mes thinking fast can lead to
false posi;ves.
THE END

30. THANK #YOU!
Thank #You!
Mircea Baldean
meetvibe.com/baldean
@baldean
Surprise.. No Test!