The document discusses the concepts of big data and smart data, emphasizing the importance of understanding the 4 V's: variety, volume, velocity, and value creation from consumer interactions. It highlights the challenges of information overload, including risks such as data blindness and analysis paralysis, while advocating for a focus on precision and proper data management to enhance decision-making. Additionally, it stresses that personalization derived from data analysis is critical for improving business outcomes and consumer satisfaction.

1. Big data, real time data, too much data...
The 4 V’s of Smart Data
SAP Forum 2015
Marcelo Coutinho
EAESP-FGV
marcelo.coutinho@fgv.br @mcoutinho

3. Source: Capgemini, Digital Shopper Relevancy, 2014
Brazilians like omnichannel

4. Retail “Big Data”: creating Value from variety
(of consumer touch points), volume (from
their interactions) and velocity (from their
desires)

5. Fonte: A.T. Kearney, Connected Consumer 2014
Brazilians are “always-on” consumers

6. Number of
smartphones
sold PER
MINUTE in
Brazil
between July
/September
2014
115

8. Source: Data Never Sleeps 2.0 – Domosphere (Google, NY Times, Apple, Cisco, The Guardian)

9. We are producing 9.300 buildings of information / hour

10. “In an information-rich world, the wealth of
information means a dearth of something else: a
scarcity of whatever it is that information
consumes. What information consumes is rather
obvious: it consumes the attention of its
recipients. Hence a wealth of information creates
a poverty of attention”.
Herbert Simon, 1971

11. Technology helps to capture, share
and save attention

12. “Data is the new oil”
Really?

14. Risks = Data Blindness + Analysis Paralysis

16. Quantity of information
Impactover
decision
efficiency/timing
Source: Kettinger and Rollins, MIT Sloan Mngt. Review
Precision beats volume

17. Oil has little value
Oil + Pressure + Heat + Chemicals = Big Value

18. Pressure = Force/Area
• Ensure data integrity (correctly report
the event)
• Garbage in, garbage out
• Problems on data capture often
involve human resources (training ,
processes, understanding the
importance of proper recording, etc. )
• If the Area is large ( several sources,
points of contact with the consumer,
geography, etc ) and you do not have
enough resources (Force), start
"pressing" one segment at a time

19. Tracking technologies allow us not only show segmented ads,
but segmented invitations for consumer research

20. • Application of the scientific
method : inferences,
deductions, hypothesis
testing, statistical methods,
multivariate analysis (cluster,
conjoint , factorial , etc )
– Attention: correlation is no
causation and linear regression
is not forecast
• Always related to business
objectives
Heat

22. Big Data Catalysts:
People, Process, Platform

23. “Data” don’t buy. People do
Personalization = data translated in behavior

24. “Smart Data” = measured value for the CEO/CFO
Revenue
Expenses
Cash Flow
Consumer
Satisfaction

25. It's hard to be simple

26. Big data, real time data, too much data...
The 4 V’s of Smart Data
SAP Forum 2015
Marcelo Coutinho
EAESP-FGV
marcelo.coutinho@fgv.br @mcoutinho