4. Module Facilitator
• I work with managers to help them
understand how enterprise applications,
web and mobile technologies can enrich
• The client portfolio in the ICT industry
includes Microsoft, Apple, Ernst & Young,
France Telecom, HP, IBM, Oracle and SAP
•The work with the IT industry in Europe
has included fifty partner and customer
conferences, a dozen case studies, and
various marketing support activities.
Prof. Lee SCHLENKER,
Professor ESC Pau
Mail : firstname.lastname@example.org
Skype : leeschlenker
Web : www.leeschlenker.com
6. This a place where managers and
students of management can discuss
and debate best practises in the digital
economy, new developments in data
science and decision making. Ask
questions and get practicable
answers, and learn how to use data in
Analytics for Management
7. • How does the author define the “Fourth
• The concept of looking “outside-in”
suggests that we must understand the
shifting business context affects our
work, our careers and our business. Give
at least one example.
• What are digital natives and how do they
look at business differently?
• How are values changing in a digitally
A Fourth Industrial Revolution ?
Schwab, K. (2017), The Fourth Industrial
10. Grading Scale
Participation: 50% of your grade will be based upon your participation and
engagement in class.
Final exam: 50% of your grade will be based upon your results on the final
multiple choice exam.
• What is the organization’s business model?
• Why does the organization focus on data?
• Which data science techniques does the organization favor
• What is the link between data science and decision
• How is the Data Science team organized?
• How does the organization use Data Science to propel
13. Analytics is the use of data, methods, analysis and
technology to help managers make better decisions.
Data science is the study of the generalizable
extraction of knowledge from data
14. • More data has been created in the
past two years than in the previous
history of the human race
• « Strategists still confuse
technology with purpose … instead
of garnering context and empathy
to inform change…” - Brian Solis
• We have more and more data – but
does this lead to better decisions?
15. • Scan the context
• Qualify the data at hand
• Choose the right method
• Transform data into action
The Business Analytics Institute
• Logic and Statistics
• Programming and Database
• Trade knowledge
• Data Storytelling
18. Data Science Challenges
Data preparation is by far the most
time-consuming part of Data
Science, but case studies rarely
19. Case Groups
Group 1 Community Management
Group 2 Education
Group 3 Financial Services
Group 4 Health Analytics
Group 5 Public Service
Group 6 Privacy and Data Protection
Group 7 Visual CVs - Employment
20. • What is the organization’s business
• Why does the organization focus on
• How is the Data Science team
• Which data science techniques does
the organization favor ?
• What is the link between data science
and decision making?
• How does the organization use Data
Science to propel growth
21. • Carr, N. The World Wide Cage
• Anderson L. and Wladawsky-Berger, L. The 4 Things
It Takes to Succeed in the Digital Economy
• Pine, B. and Gilmore, J. (1999). The Experience
Economy. St. Paul, Minn.: HighBridge Co.
• Schlenker L., (2017), Digital Economics
• Schwab, K. (2017), The Fourth Industrial Revolution