Structured Decision Making briefly explained
Structured Decision Making is an organized approach to identifying and evaluating alternatives that engages stakeholders, experts and decision makers in productive decision-oriented analysis and dialogue and deals proactively with complexity and judgment in decision making.
Rationalizing decision making through Structured Decision Making has the following benefits.
Quality and Defensibility
Transparency and Accountability
Learning and Capacity Building
Structured Decision Making Process
Process steps explained
1. Clarify the Decision Context
Clarify what decision is being made, why and within what scope. Establish roles and responsibilities. Identify the constraints within which the decision will be made.
2. Define Objectives
Seek out interest-based objectives. Expect objectives to be mutually contradictory. Objectives always have a preferred direction.
3. Define Evaluation Criteria
Evaluation criteria are required for comparing alternatives. Each of the lowest-level objectives needs an evaluation criterion.
4. Develop Alternatives
You must orient your group to the problem. Specify what matters in the decision. Decide how potential solutions can achieve the objectives. Create a variety of alternatives for decision makers to consider.
5. Estimate consequences
Estimate each alternative in terms of the evaluation criteria. Represent consequences BEFORE considering preferred alternatives. Consequence table illustrates the consequences of each alternatives.
6. Evaluate trade-offs and select
Find ‘win-wins’ and highlight trade-offs between alternatives. The selection should be logged including the reasons why.
As decisions are implemented, some of the uncertainties inherent in the analysis will be resolved. Because of this, it is important to continually assess the outcome of the decision.
Why do we need this now?
Reduce complexity and uncertainty
Rapidly changing business context
Coping with high stakes
Need to take calculated risks
Which tools can support us?
Process Mining Techniques
Use a Desicision Databases with open, scraped and internal data
Simulation using Decision Trees
Use Statistical Techniques and Algorithms
Use Interactive Dashboards
Biases that cloud our judgement
The misconception that events that are more easily brought to mind, are more likely to occur.
People take a piece of known information and extrapolate that to estimate an unknown quantity.
People generally prefer avoiding a loss over making a gain.
People tend to favor information that confirms their preconceptions.
The demonstrated systematic tendency to be overly optimistic about the outcome of planned actions.