by Judith Curry
How to gain clarity when making decisions in uncertain and complex situations.
Someone emailed me a presentation entitled Introduction to Decision Analysis. The presentation was developed by O.J. Sanchez of Decision Strategies Inc., a company that focuses on helping their clients gain clarity when making decisions in complex situations. From their web site, it appears that their clients are mainly from industry, including the energy sector. Many of these ideas relate to topics that I have touched on in previous posts, and it seems to me that this general approach is scalable to the decision dilemmas surrounding climate change. Below are excerpts from the presentation:
So . . . what is decision analysis? Decision Analysis is a systematic methodology for facilitating high quality, logical discussion; bringing clarity to difficult decisions and leading to clear and compelling action by the decision maker.
- Probabilistic framework
- Incorporates consideration of risk and uncertainty
- Focused on actions
JC comment: For some background, see these relevant CE posts:
What makes decision making difficult?
Definition: Decision – A conscious controllable allocation of resources; the act of making a choice between alternatives
JC comment: The above approach is often referred to as the ‘linear model for decision making’.
How do we recognize and differentiate between ambiguity and uncertainty?
• Ambiguity – Typically, something we don’t know, or are unsure about, but can find out – Can be resolved before the decision has to be made – Examples: Unclear or conflicting goals • Availability of resources • Stakeholder preference
Uncertainty – An unknown event that impacts the outcome of our decision – we may be able to impact the event, but we cannot control – Will not be resolved before the decision is made
JC comment: For a discussion of climate uncertainty, see my Uncertainty Monster paper.
Most decision making processes are not equipped to adequately deal with ambiguity and uncertainty
A London Business School study found a dramatic difference in effectiveness based on decision methods
JC comment: The UNFCCC strategy seems well characterized by Idea Justification • Single Option • Data and Simulation • Edict or Persuasion. Such a strategy doesn’t work well even for simpler problems
Decision analysis is a phased process:
Each phase of the decision analysis process has a set of robust tools and techniques with a logical sequence that encourages open, creative dialog.
This process is scalable to apply the appropriate level of dialogue and analysis consistent with decision complexity
Decision complexity characteristics:
Another way to look at it:
JC comment: For additional context on wicked problems and messes, see this previous CE post: Messes and super wicked problems
So . . . we have available good process and tools. Are we guaranteed a good outcome? Why not? What can we do about this?
In a world of uncertainty, decision quality cannot be judged by a single outcome.
• When risk or uncertainty are present, making a good decision does not guarantee a good outcome will always result.
• Conversely, a good outcome does not mean a good decision was made!
• But… when many, or a portfolio of decisions, are considered, there is a strong relationship between the number of good decisions and good outcomes.
JC comment: The UNFCCC is seeking a ‘silver bullet’ solution in terms of CO2 emissions reductions. A portfolio of decisions (‘silver buckshot’) seems to be a better strategy.
Things that cause poor decisions:
- Improper Frame: Asking the wrong question; Looking at only a subset of the real problem or opportunity
- Failure to consider alternatives
- Lack of meaningful information
- Competing value measures
- Poor logic
- Ignoring risk or taking on too much risk
- Lack of commitment, no buy-in
- Wrong people involved
JC comment: How many of these factors characterize climate change policy making, particularly by the UNFCCC? Too many, I’m afraid.
We have created the Objectives Hierarchy – now we need to frame the Decisions and Uncertainties
Framing uses the insights developed in the Discovery stage to build unique alternatives.
The Decision Hierarchy will clarify the scope of the decision options. • Sets of decisions will need to be pulled together into clear strategic alternatives for analysis. • A qualitative analysis can be done to determine which are viable. • A relevance model for quantitative analysis can then be diagrammed.
Decision Hierarchy is the tool that enables framing of the decision options and ideas that are on the table. The decision hierarchy helps to identify the scope of the problem and to separate constraint and implementation decisions from the focus of the analysis.
Objectives decision maker’s goals and criteria to compare options
- Decisions: Choices we can control, which sets a direction or course of action
- Uncertainties: issues we don’t know, cannot control, and will not be resolved until the decision is made and outcomes begin to occur
- Facts: known laws of nature, policies, or resolved ambiguities
What alternative strategies exist for maximizing value? Developing Creative Strategies from Multiple Decisions
Strategy table tool
Objective – key business outcomes that each alternative aims to achieve
Rationale – Positives: aspects which favor success of each alternative – Negatives:risks of failure or major resistance points for alternative –
Response: what will be the response from other key players – Hunches: intuitive feelings about the potential of each alternative
A simple influence diagram can accurately and concisely convey the essence of the problem or opportunity
This presentation explains why the current climate change decision strategy has left us between a rock and hard place.There are some good ideas in this presentation, and it seems that they would scale to to more complex, global climate change problem. I have a draft post on re-framing the climate change problem; this post motivates me to try to finish that one sooner rather than later.