Tackling complexity : a systemic approach for decision makers
Gilbert Probst (Author), Andrea Bassi (Author)
"Our socio-economic systems continue to grow and evolve. We need to acknowledge that, consequently, our decisions often fail - they are ineffective and create unexpected side effects. The speed of execution is increasing constantly and markets and systems respond almost immediately, making decision-making challenging. There is little or no room for failure
xv, 186 pages : illustrations ; 24 cm
9781783530816, 1783530812
875261973
Machine generated contents note: 1. Introduction
1.1. Purpose of and rationale for dealing with complexity
1.2. Audience and user guidance
2. Case study: why a systemic approach matters
3. Phase 1: Problem identification
3.1. Conceptual mistake #1: Abundance of data allows us to find ultimate solutions and predict system behaviour
3.2. What to do: Delimit the problem, identify the causes and the effects
3.2.1. Step 1: Define the boundaries of the problem
3.2.2. Step 2: Identify the causes and effects
3.2.3. Step 3: Analyse future behavioural paths and impacts
Case study 1 Problem identification with systems thinking: the creation of the Ethiopia Commodity Exchange
4. Phase 2: System characterisation
4.1. Conceptual mistake #2a: Every problem is a direct consequence of a single cause
4.2. Conceptual mistake #2b: We only need an accurate `snapshot' of the actual state of the system to find solutions. Contents note continued: 4.3. What to do: Map the complexity and explore the dynamic properties of the system
4.3.1. Step 1: Build a causal diagram and review the boundaries of the system
4.3.2. Step 2: Create a shared understanding of the functioning of the system
4.3.3. Step 3: Identify key feedback loops and entry points for action
Case study 2 Representing and analysing dynamic complexity to design effective policies: fossil fuel subsidy reform
5. Phase 3: Strategy/Policy assessment
5.1. Conceptual mistake #3: The problem will be solved with the implementation of the intervention selected
5.2. What to do: Identify the learning capabilities of the system
5.2.1. Step 1: Design potential interventions
5.2.2. Step 2: Assess interventions (anticipate gaps, time frames and early warning signals)
5.2.3. Step 3: Select viable intervention options and indicators
Case study 3 Reducing risks and maximising profits with systemic strategy assessment: Nestle. Contents note continued: 6. Phase 4: Decision making and implementation
6.1. Conceptual mistake #4: With a problem-oriented optimisation, the solution will maximise benefits for all
6.2. What to do: Evaluate the proposed solution using different perspectives, and assess the impacts across sectors and actors
6.2.1. Step 1: Use a multi-stakeholder approach
6.2.2. Step 2: Analyse the expected impacts across sectors and actors
6.2.3. Step 3: Define the strategy and action plan
Case study 4 Multi-stakeholder decision making in relief operations: the Agility CSR programme
7. Phase 5: Monitoring and evaluation
7.1. Conceptual mistake #5: Monitoring and evaluation do not affect the decision-making cycle, they only evaluate the system performance
7.2. What to do: Assess the effectiveness of the implemented interventions and the system responses to redefine the top priorities and the need for further action. Contents note continued: 7.2.1. Step 1: Implement the strategy and monitor the development of the system
7.2.2. Step 2: Analyse the impacts across sectors and actors
7.2.3. Step 3: Use lessons learned for the next decision-making process
Case study 5 Monitoring managers' commitment: Deutsche Bank
8. Conclusions
Annex: Overview of key tools
A1. Indicators
A2. Influence tables
A3. Causal loop diagrams
A4. Scenarios
A5. Simulation