Invited talk, describing the exciting work at Blue Yonder (www.blue-yonder.com), 'congress smart services - new business models' in Aachen, Germany 2015

1. Data Scientist –
‚The sexiest job of the 21 century‘
Frank Kienle | @byanalytics_en

5. 2008: Founded by
CERN Data Scientists
Since 2011: Award-
winning retail
solutions
2014: International
expansion, predictive
applications

6. Blue Yonder History
2008
2011
2012
2013
2014
Founded Karlsruhe &
Hamburg with a team
of 15
Re-branding to Blue
Yonder
Cyber One Award
RetailTechnology
Award
Top Retail Product
Award
Data Mining Cup
BlueYonder UK
Forward Demand 1.0
Data Science Academy
Finalist: Entrepreneur of
theYear 2012/13
BlueYonder Platform
Internet ofThings
Award
RetailWeek Supply
Chain Award
150 employees

7. •Individual product
predictions for more
than 700 locations
•35 million product-
location
combinations
•30.000 decisions per
second
•300 million data sets
evaluated per week
•5 billion individual
forecasts annually
•20% reduction in
surplus stock
•2 million article
returns avoided
•14% reduction in
write-off-rate
•9.5% reduction in
tied-up capital
•1.3% increase in sales
due to increased item
availability
•€40 million sales
increase
1
Predictive Applications at Scale
2 3

8. Europe’s largest team of PhD-
level data scientists among
Blue Yonder’s 150 employees.

9. Data Scientist:
finding the gold nuggets in big data -
extracting value out of data

15. Data Scientist:
extracting value out of data -
its all about predictions

17. More than half of the apps on
a typical iPhone home screen
are predictive applications.

18. Predictive Applications
Foresight
Hindsight
Strategy
Execution
Predictive
Analytics
Business
Intelligence
Dashboards &
Visualization
Predictive
Applications

19. — Thomas J. Watson Sr* (CEO IBM 1943)
“I think there is a world market
for about five computers.”

20. — Niels Bohr
“Prediction is very difficult,
especially if it's about the
future.”

21. Data Scientist:
extracting value out of data -
its all about predictions

22. Programming/
Technology
Statistics/
Mathematics
Business/
Processes
p(w|D) ⇠
p(D|w)P(w)

23. Data Scientist Skill/Mindset
Programming
• Programming is the process
that leads from an original
formulation of rules to
executable computer programs
• Its all about automatization
Statistics
• Statistics is the study of the
collection, analysis,
interpretation, presentation,
and organization of data
• Its all about data
Business
• A business is an organization
involved in the trade of goods
or services to consumers
• Its all about decisions
p(w|D) ⇠
p(D|w)P(w)

24. Automation of
gut feeling 2.0
Coding
• automatization
Business
• decisions
Danger Zone
• first step:
simple rule, if this than that
• next step:
add a rule/process to adjust
• last step:
blocked by contradicting rules
+ =

25. Automation of
modern art
Coding
• automatization
Statistics
• data
Art Zone
• solving problems which never
occurs
• defining new problems
• we might need this
+ =

26. Gut feeling 2.0
gets proven wrong
Business
• decisions
Statistics
• data
Theory Zone
• traditional business research
• new ideas how business should
work in theory
• proof me wrong!
by the way, I already updated
my theory
+ =

27. Programming/
Technology
Statistics/
Mathematics
Business/
Processes

28. Team building

29. The key to becoming a better
company are better decisions.
The key to better decisions is
using your own data.

30. Sensor Data Scientist — www.blue-yonder.com
Frank Kienle

31. 1
Categorizing Analytics
Descriptive
• Focused on gathering and
collecting data
• Key challenges: data volume
and data variety
• Key outcome: hindsight
• Examples: reports, dashboards
• Answers“What happened?”
Predictive
• Focused on understanding
and explaining data
• Key challenges: data velocity
and complexity
• Key outcome: insight
• Examples: prediction models
• Answers:“Why did it happen
and what will happen next?”
Prescriptive
• Focused on anticipating and
recommending action
• Key challenges: execution
• Key outcome: foresight
• Examples: decision support,
predictive apps
• Answers:“What should we do?”
2 3

32. — Jeff Bezos
“Your margin is my opportunity.”