Decision analysis

Eike Luedeling, Keith Shepherd

Research for impact

Most science never supports any decisions, even though decision-makers

are hungry for information.

http://www.mynamesnotmommy.com

Most research does not answer questions that are critical for decisions, or it is not readily available when it is

needed.

Tailor research specifically to address particular decisions

Decision making under uncertainty

Identify all uncertainties in the decision of interest

Make probabilistic projections of likely decision outcomes

http://www.relationshipeconomics.net

Engage directly with decision makers

This is the core of WLE’s decision analysis procedures

Identify uncertain variables with high ‘information values’. These are priorities for measurements

WLE’s decision analysis approach

Optimize the decisionUse preferences of decision makers to determine best decision

YesIs there significant value to

more information? Yes

No

Compute the value of additional informationDetermine where and how much measurement effort is needed

Model the current state of uncertainty of all relevant factors Initially use calibrated estimates and then actual measurements

Define the decision(s) – Identify relevant variablesSet up the ‘Business Case’ for the decision.

Measure where the information value is

high – Reduce uncertainty using proven empirical

methods

Outputs

Replenishment

Irrigation growth

Initial irrigated area

Water use per hectare

Aquifer size

Natural water use

Importance threshold

Identification of high-value variables

Probabilistic impact projections

Aquifer size after 70 years of abstraction (% of original)

Advantages and applications• Inclusion of uncertain variables allows truly holistic

impact assessments• High information value variables are almost always

not those typically measured• Probabilistic impact projections can often provide

sufficient certainty about decision outcomes• Possible applications include:– Quantitative and probabilistic impact pathways– Ex-ante impact projections– Counterfactuals for impact assessments– Definition of priority variables for impact monitoring

Thanks for your attention!

Eike Luedeling (e.luedeling@cgiar.org)