Course support for the module "Digital Technologies and Innovation"

1. Digital Technologies and Innovation
Introduction
April 2018
http://DSign4Change.com

2. ©2016 L. SCHLENKER
Agenda
Introduction
The Data Revolution
Time, Space and Organization
The Analytical Method
Introduction

3. Module Facilitator
I work with managers to help them
understand how enterprise applications,
web and mobile technologies can enrich
their careers.
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,
The Business Analytics Institute
Mail : lee@lhstech.com
Skype : leeschlenker
Web : www.leeschlenker.com
Introduction

4. • Management is about taking decisions
• Improving decision making through the study
of digital economics, managerial decision
making, machine learning and data
storytelling
• Innovation isn’t a consequence of
technology, but of a state of mind
http://baieurope.com
lee@baieurope.com
@DSign4Analytics
Skype : leeschlenker
©2017 Business Analytics Institute
Introduction

5. Course Portal:
http://DSign4Change.com
©2017 Business Analytics Institute
The objective of this course is to
build the students’ knowledge of the
practice of Business Analytics in a
variety of industrial settings
Introduction

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
decision making.
Analytics for Management
https://www.linkedin.com/
groups/13536539
Introduction

7. • How does the author define the “Fourth
Industrial Revolution”?*
• 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
intermediated world?
A Fourth Industrial Revolution ?
Schwab, K. (2017), The Fourth Industrial
Revolution
Introduction

8. 8©2017 LHST sarl
• Analyze the context of each case to document the
key processes of the organization or the market
• Qualify the data at hand to understand the nature of
the business challenges
• Apply the appropriate methodologies in your
predictive and prescriptive analyses, and
• Integrate elements of visual communications in
transforming the data into a call for collective
action
In this module , you will
www.Dsign4change.com
Adminstration

9. 9
Innovation is a State of Mind
©2018 LHST sarl
Introduction
Session 1 The Building Blocks
Session 2 Data
Session 3 Digital Technologies
Session 4 Decision Making
Session 5 Innovation
Session 6 Social Business

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
making?
• How is the Data Science team organized?
• How does the organization use Data Science to propel
growth?
Adminstration

11. Decision
Trees
 Supervised
 Categorical
It’s sunny, hot,
normaly humid, and
windy – should I play
tennis?

12. To help us understand the motivations, experience and
objectives of the internal and external clients of the
organization
 ROI
 Real time data
 ...
Stockholders
 Competition
 “made in”
“made by”
 ...
The State
 Peu de
barrières
d’entrée
 Acquisitions,
OPA...
Partners
 Loyalty
 Real costs
 ...
Clients
The Enterprise
 Mobility
 Empowerment
 ...
Employees
Introduction

13. ©2016 LHST sarl
Introduction

14. Introduction

15. • Management is all about taking better
decisions
• What do better decisions mean (faster,
more impressive, more precise) ?
• Is it observable – how is something more
precise answer to a problem?
• The challenge is deciding what we want to
measure
Lewis Mumford, Technics and Civilization
Decision
Making
©2016 L. SCHLENKER

16. • 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?
What is data?
Introduction

17. • Scan the context
• Qualify the data at hand
• Choose the right method
• Transform data into action
The Business Analytics Institute
https://baieurope.com
Introduction

18. Lee SCHLENKER
Results
Actions
Knowledge
Context
Data
Process
Interprets
Decisions
Measures
Obtain
Define
Require
Drive
The ladder of initiatives™
Introduction

19. • What if the devices “completely go away
to be absorbed into the fabric of our lives?”
• Smart pills are an example of ambient
technologies that integrate into our
environments
• These Invisibles will create a world in
which we don’t see technology or sensors
• Can technology become human –
reacting to what makes each one of us
unique?
http://youtu.be/-hhOtjdkU34
©2014 L. SCHLENKER
Introduction

20. • Properties - digital experiences put in place to
enrich organizational conversations
• Platforms – digital technologies that create
proximity between those that produce, and those
that consume, experience
• People – the managerial mindset
• Practice - the operational realities of management
Schlenker (2015)
Introduction

21. • What is the organization’s business
model?
• Why does the organization focus on
data?
• How is the Data Science team
organized?
• 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
Case Methodology
Case Study

22. Case Groups
Case Study
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

23. • 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
Bibliography
Next Steps