Projects as complex adaptive systems - understanding how complexity influences project control and risk management. Warren Black
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1 1 Projects as complex adaptive systems - understanding how complexity influences project control and risk management Warren Black
2 2 Opening Thought Complex projects are merely chaotic systems in hibernation, just waiting for an excuse to unleash Think about that a while
3 The Current Reality of our Working World 3 Over the past two decades our working world has moved out of an age that thrived on structured and systematically-linear management processes towards an age enabled by connectivity, agility, adaptability & responsiveness
4 4 A brief introduction to Complex Systems Theory and how it relates to Projects
5 The Complex Systems Maturity Scale 5 Simple Obvious System Simple Ordered System Complex Physical System Complex Adaptive System Simple Systems Complex Systems
6 Feedback Feedback What is a Complex Adaptive System? A highly energised entity comprising of an advanced number of internal contributing parts which are continually interacting with and adapting to their environmental circumstances, whilst in pursuit of a common goal Contributing Agents The Weather A Language Interactions & Relationships A Rainforest A Food Chain A Political System Pandemics Signals An Eco-System The Human Brain War An Economy An Immune System An Organisation Ripples A Social Network A Project Behavioural Outcomes
7 What can escalate a Project from a simple state to a complex state? 7 Advanced shifts in; Scale (size, range, scope, magnitude, constituent parts etc.) Uncertainty (unknowns, variables, assumptions) Change (dynamic, compounding, adaptive, momentous) Dependency (integration, sequencing, stakeholders, networks) Behaviour (erratic, deviant, emergent, illogical, chaotic)
8 States of Complexity (Cynefin Framework) 8 Simple/Obvious Complicated Complex Chaotic Ordered Static Predictable Linear Certain Disordered Dynamic Unpredictable Erratic Uncertain
9 9 Eight Habits of Highly Complex Systems aka how complexity can manifest itself within your Project
10 10 Complex Systems Phenomenon #1 The Butterfly Effect States that a seemingly insignificant change in one area of a complex system can ripple and compound to create momentous, possibly even uncontrollable, impacts elsewhere within the system
11 11 Complex Systems Phenomenon #2 The Edge of Chaos States that a complex system is at all times no more than a transition or two away from descending into wild disorder (chaos) and thus should be considered at all times to be an inherently chaotic entity
12 12 Complex Systems Phenomenon #3 Emergence States that a highly complex system will create new emergent behaviours, properties and characteristics that are not an outcome of design
13 13 Complex Systems Phenomenon #4 Sum of Parts States that a complex system comprises of an advanced number of internal contributing agents whose total integrated behaviour is so much more momentous and impactful than the combined sum of the individual parts
14 14 Complex Systems Phenomenon #5 Strange Attractors States that the primary contributing agents of a complex system, will not necessarily engage with each other through logical means of attraction (e.g. cause & effect)
15 15 Complex Systems Phenomenon #6 Fractals States that although numerous recognisable patterns and relationships may exist within a complex system, their behavioural outcomes will rarely be consistent, logical nor repeatable
16 16 Complex Systems Phenomenon #7 Non-linearity States that a complex system is a highly dynamic, evolutionary and unpredictable entity and thus past performance is not a reliable indicator of future performance
17 17 Complex Systems Phenomenon #8 Signals States that complex systems are highly responsive entities which are driven by signals generated from the internal contributing agents continually interacting with and adapting to both each other, and their surrounding environment
18 Rationalising these complexity phenomena into complex project risk management (as an example) 18
19 19 Learning #1 We need to move beyond the traditional industry over dependence of having to first predict (aka identify and measure) a risk in order to control it Complex Systems Thinking means acknowledging that one can not predict the behavioural outcomes of a highly complex project system because as internal complexity increases; consistency, rationality and predictability decreases
20 20 Learning #2 We need to acknowledge that a one size fits all approach to risk management is impaired within a system that is continually transitioning Complex Systems Thinking means acknowledging that any chosen control framework must offer at least as many control solutions as the number of differing challenges being offered by the system.and that Risk Control Solution A Risk Control Solution B Risk Control Solution C Risk Control Solution D all control solutions must be determined based on the specific degree of difficulty in play
21 Learning #3: We need to understand the true purpose of Project Risk Management i.e. to prevent the entire project system from escalating into Chaos 21 For the longest time we were taught Risk Management is about controlling Uncertainty (alone) But where there is Uncertainty, Complexity follows and where there is Complexity, Uncertainty follows. Thus the two are inter-dependant Complex Systems Thinking means acknowledging that in order to reduce a system s exposure to risk, one needs to reduce both the environmental Uncertainty and Complexity
22 Learning #4: We need to start viewing and treating project risks as systems, not autonomous isolated scenarios (i.e. single line items on a risk register or audit list) 22 World Economic Forum, Global Risk Maps 2017 Complex Systems Thinking means acknowledging that risks are a behavioural outcome of a highly energised and inter-connected system, thus risks need to be treated as a system
23 Physical Behavioural Learning #5: Need to focus on maturing, integrating and adapting the project s risk control framework, so that it steers the project system towards positive outcomes 23 Positive Agent Relationships Negative Agent Relationships Positive Interactions Negative Interactions Positive Signals Negative Signals Positive Ripples Negative Ripples Positive Outcomes (Opportunities) Source: Warren Black, Queensland University of Technology, 2016 Negative Outcomes (Threats) Complex Systems Thinking means acknowledging that a system s behavioural outcomes (whether they be positive or negative) are determined by the manner in which its internal contributing agents are allowed to exist and interact
24 24 Closing thought If you accept that your project is a complex system, then you also have to accept that the scientifically valid laws of complex systems theory apply to your project s control framework you can not accept one premise without the other
25 Warren Black Project Engineer, Risk Professional & Complex Systems Theorist Warren currently consults as an industry specialist who helps the invested stakeholders of complex projects to embed appropriate governance, risk and assurance practices which might better reflect the degree of investment at risk. In this regard, Warren works as an associate for ICCPM and is currently engaged in Higher Research at the Queensland University of Technology on how complex systems theory may offer a new generation solution to controlling complex project risk Questions? International Centre for Complex Project Management P: E: admin@iccpm.com
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