2. Complexity
Leadership
Theory
IntroducCon
Complexity
Theory
(CT)
Complexity
Leadership
Theory
(CLT)
CLT
CharacterisCcs
CorrelaCon
AggregaCon
AutocatalyCc
Mechanism
Nonlinear
Emergence
Advantages
&
Disadvantages
Conclusion
3. IntroducCon
• In
an
IBM
research
of
more
than
1,500
CEO’s
Howard
Tollit
idenCfied
as
on
of
the
significant
findings:
• “Complexity
has
overtaken
change
as
the
main
challenge
facing
CEOs
across
the
globe
–
and
more
than
half
of
UK
&
Irish
CEOs
doubt
their
ability
to
manage
it
(the
porporCon’s
even
higher
worldwide)”
(management
today,
2010).
4. IntroducCon
• Manville
and
Ober
(2003)
idenCfied
that
“We’re
in
a
knowledge
economy,
but
our
managerial
and
governance
systems
are
stuck
in
the
Industrial
Era.
It’s
Cme
for
a
whole
new
model”
(as
cited
in
Uhl-‐Bien,
Marion,
&
McKelvy,
2007,
p.
298).
5. Complexity
Theory
• CLT
is
derived
from
CT
• CT
“concerns
the
descripCon
and
predicCon
of
systems
that
exhibit
complex
changing
behavior
at
the
macroscopic
level,
emerging
from
the
collecCve
acCons
of
many
interacCng
components”
(Mitchell,
2009,
p.
15).
– The
Brain;
interacCng
neurons
– The
WWW;
Network
of
individual
players
6. Complexity
Theory
• “Complexity
theorists
are
interested
in
understanding
how
the
interacCons
of
people
in
organizaCons
lead
to
the
creaCon
of
paberns
of
behavior,
which
in
turn
shape
organizaConal
strategies,
power
structures,
and
networks
of
relaConships”
(Ardichvili
&
Manderscheid,
2008,
p.
624).
7. Complexity
Leadership
Theory
• CLT
funcCons
to
create
“condiCons
that
enable
the
interacCons
through
which
the
behaviors
and
direcCon
of
organizaConal
systems
emerge.
Leaders
provide
control
by
influencing
organizaConal
behavior
through
managing
networks
and
interacCons”
(Marion
&
Uhl-‐Bien,
2001,
p.
406).
9. CorrelaCon
• Shared
interest
among
agents
(people)
• Common
beliefs
• Similar
world-‐views
• Type
of
bonding
process
between
agents
• Fosters
integraCon
among
agents
• Forms
aggregates
(networks)
10. AggregaCon
• Changes
among
agents
• Changes
are
ogen
caused
by
interacCons
and
correlaCon
between
agents
and
networks
of
agents
• CT
sees
small
changes,
at
the
micro-‐level,
leading
to
large
changes,
at
the
macro-‐level
• Self-‐organizing
11. AutocatalyCc
InteracCon
• The
state
where
different
units
(agents
or
departments)
interact
• InteracCon
cannot
be
predetermined
by
leadership
• InteracCon
must
be
enabled
by
leaders
• Has
a
moderaCng
effect
• Self-‐generaCng
system
12. Nonlinear
Emergence
• Nonlinear
(inter-‐
&
intra-‐department,
internal
and
external
of
organizaCon)
• Sudden
and
unpredictable
change
– InnovaCon
– New
technologies
– Break
into
new
markets
• Structures
evolve
and
reorganize
– Similar
to
a
network
system
• Bobom-‐up
directed
13. Advantages
/
Disadvantages
• Advantages
–
Self-‐organizing
–
less
managerial
funcCons
• Disadvantages
–
OrganizaConal
Culture
Change
•
leaders
have
to
release
control
•
follower
have
more
responsibiliCes
–
HR
Challenge
–
PotenCal
for
Chaos
14. Conclusion
• Through
Complex
Leadership
Theory
Leaders
Should:
– Create
condiCons
for
innovaCon
as
opposed
to
creaCng
the
innovaCon
– Drop
seeds
of
innovaCon
rather
than
mandaCng
innovaCon
plans
– Create
opportuniCes
to
interact
rather
than
creaCng
isolated
and
controlled
work
cubicles
– Tend
to
networks
– Catalyze
more
than
they
control
(Marion
&
Uhl-‐Bien,
2001).
15. References
Ardichvili,
A.
&
Manderscheid
(2008).
Emerging
pracCces
in
leadership
development:
An
introducCon.
Advances
in
Developing
Human
Resources,
10(5),
619-‐631.
Management
Today
(2010,
June
07).
MT
leadership
visions:
Capitalising
on
complexity.
Retrieved
from
hbp://www.managemenboday.co.UK/news/1008266/mt-‐leadership-‐
visions-‐capitalising-‐complexity/
Marion,
R.
&
Uhl-‐Bien,
M.
(2001).
Leadership
in
complex
organizaCons.
The
Leadership
Quarterly,
12,
389-‐418.
Retrieved
from
hbp://
www.elsevier.com/wps/find/journaldescripCon.cws_home/620221/
descripCon#descripCon
Mitchell,
M.
(2009).
Complexity:
A
guided
tour.
New
York,
NY:
Oxford
University
Press.
Uhl-‐Biewn,
M.,
Marion,
R.,
&
McKelvey,
B.
(2007).
Complexity
leadership
theory:
Shiging
leadership
from
the
industrial
age
to
the
knowledge
era.
The
Leadership
Quarterly,
18,
298-‐318.
doi:
10.1016/j.leaqua.
2007.04.002