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Adapting to a complex world:
Implications for organisations
Jean Boulton
Visiting Senior Research Fellow, DSPS
Director, Claremont Management Consultants Ltd
September 2015
jboulton@claremont-mc.co.uk
www.embracingcomplexity.com
1. The science of why we need to be adaptive
2. Implications for organisations
2
1. The science of why we need to be adaptive
Page 3 10/1/2015
Section 1: Traditional science
Traditional mechanical science - Newton
Things work like a machine -
predictable,
clear cause –and-effect links.
4
The machine view
Standardise
Best practice
Plan and define processes
Cause and effect (measure)
Economies of scale
Evolutionary science
Things emerge when something
changes that suits the local
conditions –
What sustains is the system /ecology
best adapted to the local situation at the time
And the future builds on what is already there..
The future cannot
be known
in advance
Change and
adaptability
require
diversity and
messiness
Cooperation
(more than
competition)
5
Complexity science – how physics explains evolution
The machine view
6
Complexity – how physics explained evolution
The science of open evolving adaptive systems
•The world is deeply inter-connected
•Local detail and history matters
•Events and variation and experiment can tip us into new eras
Standardise
Best practice
Plan and define processes
Cause and effect (measure)
Economies of scale
We desire a controllable, predictable and measurable world
– but desiring does not make it so
Interlude: has your life gone to plan?
Page 7
What gets in the way?
The world changed
Actions of others
The legacy of the past
Learning
Catastrophe
Unintended consequences
Chance
3. Implications for organisations
8
What is needed to adapt to local and changing circumstances
-to a VUCA (volatile, uncertain, complex, ambiguous) world?
9
•Look back: build on the past
•Look around and up and down: look widely and at all the issues
and work systemically not thematically
•Look ahead: spot ‘critical junctures’ and be able to modify priorities accordingly
1. Undertake ongoing context analysis
Working with complexity – context analysis
Page 10
The future –
weak signals of change
fore-sighting critical juctures
macro
meso
micro
The past –
History – events, culture, what worked,
key players
The present
Wide-ranging factors – economic, environmental, political
Macro to micro – up and down
What is needed to adapt to local and changing circumstances
-to a VUCA (volatile, uncertain, complex, ambiguous)
11
2. Be adaptive....but not just reactive...
•Be able to seize opportunities, respond to unexpected
problems
•Look for weak signals of change
•Experiment
•Share results and learn by sharing – but don’t set
approaches in stone
•Weave ‘intentions’ and plan in detail short term, review
regularly
•Real effort to understand the background and context
•Build relationships and work with others and in
cognizance of others’ work
•A more flexible way of showing effectiveness – emergent
as well as pre-set measures
•A more devolved organisation
•Within broad guidelines and intentions allow local
interpretation
Summary
12
•Complexity theory is how physics explains evolution – the science of open systems
•It legitimates a more systemic, flexible and adaptive way of working;
•It emphasises that history, context and foresighting are critical aspects of working effectively
•It is a difficult mindset change because it emphasises that we can
know less and predict less and attribute less that we hoped.
•However Embracing Complexity , being adaptive, can lead
to greater effectiveness, increased efficiency and more engaged and
empowered professionals...
•If the world is complex, then acting congruently with that complexity
can be simpler and more effective than trying to control a machine
that does not exist.
Finally – how do you persuade those in power to
‘embrace complexity’?
Be brave, be strategic, take the initiative
• Give examples of where systemic , contexted working yields unexpected results – ie
where projects have been joined up or where there has been sufficient flexibility to
modify the approach to suit the context.
• Track the ‘growing shoots’ of new unexpected outcomes and show how projects often
achieve ‘more or different’ that what original indicators expected;
• Present ideas that come from those closer to the field and come from thinking more
widely and more into the future – about what is happening and emerging now and
what ‘critical junctures’ may be on the horizon. Give examples of how smarter working,
building on a range of factors, and anticipating the future, might lead to better, more
systemic, project design.
• Point out where current thematic project designs and indicators reduce overall impact
(e.g. where several agencies are tackling the same issue in one location and none in
another location, where agencies have money for children but cannot help mothers etc)
If you are interested to explore more of these ideas, browse www.embracingcomplexity.com and/or buy
Embracing Complexity (2015) Boulton, J et al: Oxford University Press (quote AAFLY7 for a 30% discount)
13

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Complexity aa sept2015

  • 1. Adapting to a complex world: Implications for organisations Jean Boulton Visiting Senior Research Fellow, DSPS Director, Claremont Management Consultants Ltd September 2015 jboulton@claremont-mc.co.uk www.embracingcomplexity.com
  • 2. 1. The science of why we need to be adaptive 2. Implications for organisations 2
  • 3. 1. The science of why we need to be adaptive Page 3 10/1/2015
  • 4. Section 1: Traditional science Traditional mechanical science - Newton Things work like a machine - predictable, clear cause –and-effect links. 4 The machine view Standardise Best practice Plan and define processes Cause and effect (measure) Economies of scale
  • 5. Evolutionary science Things emerge when something changes that suits the local conditions – What sustains is the system /ecology best adapted to the local situation at the time And the future builds on what is already there.. The future cannot be known in advance Change and adaptability require diversity and messiness Cooperation (more than competition) 5
  • 6. Complexity science – how physics explains evolution The machine view 6 Complexity – how physics explained evolution The science of open evolving adaptive systems •The world is deeply inter-connected •Local detail and history matters •Events and variation and experiment can tip us into new eras Standardise Best practice Plan and define processes Cause and effect (measure) Economies of scale We desire a controllable, predictable and measurable world – but desiring does not make it so
  • 7. Interlude: has your life gone to plan? Page 7 What gets in the way? The world changed Actions of others The legacy of the past Learning Catastrophe Unintended consequences Chance
  • 8. 3. Implications for organisations 8
  • 9. What is needed to adapt to local and changing circumstances -to a VUCA (volatile, uncertain, complex, ambiguous) world? 9 •Look back: build on the past •Look around and up and down: look widely and at all the issues and work systemically not thematically •Look ahead: spot ‘critical junctures’ and be able to modify priorities accordingly 1. Undertake ongoing context analysis
  • 10. Working with complexity – context analysis Page 10 The future – weak signals of change fore-sighting critical juctures macro meso micro The past – History – events, culture, what worked, key players The present Wide-ranging factors – economic, environmental, political Macro to micro – up and down
  • 11. What is needed to adapt to local and changing circumstances -to a VUCA (volatile, uncertain, complex, ambiguous) 11 2. Be adaptive....but not just reactive... •Be able to seize opportunities, respond to unexpected problems •Look for weak signals of change •Experiment •Share results and learn by sharing – but don’t set approaches in stone •Weave ‘intentions’ and plan in detail short term, review regularly •Real effort to understand the background and context •Build relationships and work with others and in cognizance of others’ work •A more flexible way of showing effectiveness – emergent as well as pre-set measures •A more devolved organisation •Within broad guidelines and intentions allow local interpretation
  • 12. Summary 12 •Complexity theory is how physics explains evolution – the science of open systems •It legitimates a more systemic, flexible and adaptive way of working; •It emphasises that history, context and foresighting are critical aspects of working effectively •It is a difficult mindset change because it emphasises that we can know less and predict less and attribute less that we hoped. •However Embracing Complexity , being adaptive, can lead to greater effectiveness, increased efficiency and more engaged and empowered professionals... •If the world is complex, then acting congruently with that complexity can be simpler and more effective than trying to control a machine that does not exist.
  • 13. Finally – how do you persuade those in power to ‘embrace complexity’? Be brave, be strategic, take the initiative • Give examples of where systemic , contexted working yields unexpected results – ie where projects have been joined up or where there has been sufficient flexibility to modify the approach to suit the context. • Track the ‘growing shoots’ of new unexpected outcomes and show how projects often achieve ‘more or different’ that what original indicators expected; • Present ideas that come from those closer to the field and come from thinking more widely and more into the future – about what is happening and emerging now and what ‘critical junctures’ may be on the horizon. Give examples of how smarter working, building on a range of factors, and anticipating the future, might lead to better, more systemic, project design. • Point out where current thematic project designs and indicators reduce overall impact (e.g. where several agencies are tackling the same issue in one location and none in another location, where agencies have money for children but cannot help mothers etc) If you are interested to explore more of these ideas, browse www.embracingcomplexity.com and/or buy Embracing Complexity (2015) Boulton, J et al: Oxford University Press (quote AAFLY7 for a 30% discount) 13