The document discusses visionary leadership in contexts of volatility, uncertainty, complexity and ambiguity (VUCA). It defines leadership, context and followers as key factors. Leadership requires vision, understanding, clarity and agility. Big data and rapid reflection forces can help leaders gain understanding of complex situations and make wise decisions. The document provides examples of how Netflix and a small butcher shop leveraged big data insights to improve their businesses. It identifies areas for further research around how organizations structure leadership and decision-making when using big data and machine learning.

1. Visionary Leadership IN VUCA CONTEXTS
INTRODUCTION

2. Some Definitions - Continued:
To effectively influence individuals leadership needs to account for the Leadership
(Nahvandi, 2015), the Context (Northouse, 2016), and the Followers (Grint, 2010).
Leadership
Context
Followers

3. LEADERSHIP
VOLATILITY
UNCERTAINTY
COMPLEXITY
AMBIGUITY
The rate of
change is
exponential
The ability to
plan based
upon
predictable
outcomes no
longer works.The multiplicity
of decision
factors becomes
overwhelming
The cultural
mores that
used to
determine
right and
wrong don’t
work in a
multi-
cultural
world.
The 21st
Century
Organization
moves away
from heroic
leader to
leadership

4. LEADERSHIP
VISION
UNDERSTANDING
CLARITY
AGILITY
A Clear
Picture of Our
Desired
Future State
(Appreciative
Inquiry).
The
ability to
stop,
look, and
listen to
the
factors at
play (Big
Data and
Critical
Thinking)
The ability
to formulate
and
articulate
logical
choices in
the midst of
complexity
The ability
to invoke
collaborativ
e decision
making and
experiment
ation at the
margins.
The 21st
Century
Organization
moves away
from heroic
leader to
leadership

5. Grint, K. (2005).
Problems,
problems,
problems: The
social
construction of
“leadership.”
Human Relations,
58(11), 1467–
1494.
http://doi.org/10
.1177/001872670
5061314
Big Data

6. Organization as a Complex Adaptive System (Elkington, van der Steege, Moss-
Breen, Glick-Smith, 2017).
VUCA:
olatility
ncertainty
omplexity
mbiguity
Leader
L
L
L
L
R
R
F
E
E
E
E
E
E
E
E

7. Explaining the Diagram and Leveraging Big Data
for Effective Leadership Decision Making in the
midst of VUCA
What is RRF?
Rapid Reflection Forces (Lagadec,
2009).
These are data scientists and/or
mechanisms set in place within
organizations to monitor trends
through the ongoing analysis of
trends revealed by Big Data
What is E?
Experimentation at the Margins
(Dervitsiotis, 2005)
Once a trend is revealed by RRF we
ideate solutions and experiment
with these before mainstreaming
them
What is L?
Leadership (Either Emergent or
Assigned) (Vardiman, Houghton, &
Jinkerson, 2006)

8. VISION
• What is Vision?
• How do we develop
Vision?
• How do we embed
Vision?

9. VISION IS
A CLEAR PICTURE OF A DESIRED FUTURE STATE
1. “To become the world’s most loved, most flown,
and most profitable airline.” – Southwest Air
2. “Our vision is to create a better every-day life for
many people.” – IKEA
3. “To be a nerd for all your needs.” – Nerdster
4. “A world without Alzheimer’s disease.” –
Alzheimer’s Association
5. “To teach others to become successful.” – Anago
Cleaning System

10. HOW DO WE DEVELOP VISION?
1.Know your organization.
During the initial phase of formulating a
vision, it is important to learn everything
about the organization as it currently
exists
2. Involve critical
individuals.
The individuals or groups
identified as constituencies
include those that are the most
critical, both inside and outside
3. Explore the possibilities.
In her definition of future vision
Manasse (1986) advocates considering
future developments and trends that
may influence
4. Put it in writing.
The final step is writing a clear and
concise vision statement. This step
uses all the information gathered
and discussed,

11. HOW DO WE DEVELOP VISION? AI
METHOD1.FRAME THE GENERATIVE
QUESTION
How will we, ACME Widgets, delineate
ourselves as the best … in the next ten
years?
2. DISCOVERY.
In groups of two to three people
share stories of when you were
at your best within ACME
widgets (your organization), or
when you accomplished
something meaningful within
ACME Widgets.
3. DREAM.
If you were to fall asleep and wake up in
ten years and ACME Widgets (your
organization) is the best in the world,
what would that look like.
4. DESIGN.
What action steps, roles, goals, and
milestones need to be set to
accomplish the dream?
5. DESTINY.
How do we embed the design pieces
into the organization through metrics,
reporting, coaching, etc?

12. How do we embed the
Vision?

13. Communicating the
Vision Constantly
In our management processes and
related decisions.
In our workplace communication
pieces such as our e-mail signature,
our artefacts, our meetings.
By modelling our commitment to the
Vision through what we celebrate,
and how we act as leaders.

14. Stories
• Form the foundation of sensegiving
• Influence beliefs, attitudes, and
behaviors
• Help leaders to unite people
• Help people make sense of complex
situations
• Bind people together in a shared
purpose and inspire action

15. NETWORK LEADER TYPOLOGIES
(Willburn & Campbell, 2012)
Popularity: A person with great
influence due to the sheer volume
and quality of interpersonal
relationships managed on a daily
basis.
Prestige: Possess valuable
information that others in the
organization want/need and look to
this person to supply.
Facilitation: Leader who builds
relationships with key leaders to exert
“Ghost influence.”
Brokerage: Ability of the leader to
bridge fragmented groups within
networks.

16. UNDERSTANDING
• What is Understanding?
• How do we develop
Understanding?
• How do we practice
Understanding?

17. Understanding = Stop, Look, and Listen to the Factors at Play
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18. The Impact of the 4th Industrial
Revolution

19. It is in the realm of
“Understanding” that
leadership can
leverage Big Data for
effective decision
making.
• As Migliore & Chinata (2017) state:
•
• Big Data and Machine Learning provide
opportunity to balance the realms of bounded
and unbounded rationalities in decision-
making and, therefore, can help leaders
overcome the psychological traps of
misperceptions and bias that can
subconsciously trick the mind (Hammond et
al., 2006). For this reason, leaders who want
to improve strategic decision-making abilities
need to understand IT capabilities and
combine IT resources in a way that gains new
insight and creates new value for the
organization. Using Big Data and Machine
Learning practices is a revolutionary way to
discover new opportunities for improved
decision-making.
•

20. It is in the realm of “Understanding” that
leadership can leverage Big Data for
effective decision making.
• According to Migliore and Hubbard (2016):Company
leaders who understand data analytics have greater
professional advantage over those who do not,
mainly because of the ability to interact
competently with data science teams and envision
opportunities to either improve decision-making or
see competitive threats using new or existing data
resources for competitive advantage (Provost and
Fawcett, 2013).
Rapid Reflection
Forces

21. Leadership (Either Emergent or Assigned) (Vardiman, Houghton, & Jinkerson, 2006)
• When it comes to Rapid Reflection Forces and the use of Big
Data both assigned and emergent leadership leverage Big
Data to assist in making wise and effective decisions. As
Tunguz & Bien (2016) state:
• Data-Driven companies want every employee to discover
new information, understand it within the context of their
existing frameworks, determine what assumptions are no
longer true, and then evolve the way they think to move
things forward. When we do that we harness the power of
curiosity and transform it into innovation.

22. Some Examples of Decision-Making Using
Big Data
• Netflix and House of Cards (Tunguz and Bien, 2016)
• “Most recently, Netflix have moved towards positioning
themselves as a content creator, not just a distribution method for
movie studios and other networks. Their strategy here ahs also
been firmly driven by their data – which showed that their
subscribers had a voracious appetite for content directed by David
Fincher and also starring Kevin Spacey. After outbidding networks
including HBO and ABC for the rights to House of Cards, they were
so confident it fitted their predictive model for the “perfect TV
show” that they bucked the convention by producing a pilot and
immediate commissioned two seasons comprising 26 episodes.
Every aspect of the production under the control of Netflix was
informed by data, even the range of colours used on the cover
image was selected to draw viewers in.”

23. Pendleton and Son Butchers (Tunguz and Bien, 2016)
• Pendleton and Son are a local Butcher based in north-west
London. They started in 1996 and enjoyed a steady customer
base since their inception.
• In 2014 when the local library closed down a supermarket
chain moved into the area and this affected revenue for the
local butcher.
• Their product was excellent, but they were now struggling to
get customers through the door. Trying to compete on price
was not working and falling revenues meant that something
had to be done. Son Aaron Pendleton turned to big data to
turn things around:

24. How Pendleton and Son Turned Around a Bad
Situation.
• Worked with a Big Data consultant:
• Install sensors in the window
• To monitor footfall
• Measure the impact of Window Displays and promotions
(by who then came into the store…)
• Armed with this information they were able to refine
their displays and messaging based on what
interested customers the most.
• The sensor data also pointed to an unexpected
revenue stream…

25. How Pendleton and Son Turned Around a Bad
Situation.
• As two popular Pubs were located at the end of the street,
the hours of 9 pm to midnight proved particularly busy in
terms of passers by, almost as many as the lunch hour.
• So the Pendleton's decided to a trial opening at night and
serving premium hot dogs and burgers to hungry folk
making their way home from the pub.
• In order to decide on what products to offer at night,
Aaron analyzed trend data from Google Trends to see
what food items were particularly popular. This lead to
the creation of their pulled pork burger with chorizo.
• The butchers continue to use Big Data to know and
understnd their customers even better.

26. Areas for
Further
Research
Organizations that
are using Big Data
and how they are
using Big Data
How these
organizations are
structured in terms
of leadership
How the leadership
in these
organizations use Big
Data to make
decisions
The dynamic
interplay between
algorithms, machine
learning, and:
•Leadership emergence
•Leadership decision
making and
•Leadership wisdom.

27. LET’S DISCUSS
WHAT ARE WAYS IN
WHICH YOU MIGHT
DEVELOP
UNDERSTANDING IN
YOUR ORGANIZATION?
This Photo by Unknown Author is licensed under CC BY-SA