Applied Information Economics/ Decision Analysis Workshop
“How to Measure Sustainable Agriculture”
13 – 17 August 2012
World Agroforestry Centre (ICRAF), Nairobi, Kenya
Background
The CGIAR Research Program on Water, Land and Ecosystems aims to improve natural
resources management for food security and livelihoods. A key question facing this and other
CGIAR programmes, as well as many donors and development agencies, is how to measure
sustainable agricultural intensification (sustainable agriculture) and then use the measure to
evaluate research or intervention impacts both ex ante (research, intervention or information
systems design) and ex post (reliable learning through rigorous evaluation and impact
assessment). This involves being able to measure and assess trade-offs among the CGIAR
system-level outcomes of reducing rural poverty, increasing food security, improving
nutrition and health, and sustainable management of natural resources. A way of measuring
sustainable agriculture is needed for evidence-based decision-making at a cascade of levels,
ranging from setting goals and measuring achievement for international agreements to local
schemes for providing rewards for environmental services.
At the same time, the Program’s Information Systems strategic research portfolio is seeking
to strengthen the science behind understanding development decision processes, identifying
where are the main uncertainties and identifying areas of high-value information support. We
are seeking a quantitative and yet practical approach to determining what are high-value
information products that can support decision-making for sustainable agriculture at different
levels. The results of applying the approach will be used to develop priorities and target our
research investments in data collection and information product development. The
measurement methods developed will also be used to monitor impacts of information
products on system level outcomes.
Workshop objective
The aim of this on-site training and consulting workshop is to learn about and evaluate the
use of Applied Information Economics (AIE) for solving this type of difficult measurement
challenge. The workshop will be led by Doug Hubbard, author of the books “How to
Measure Anything” and “The Failure of Risk Management” and developer of AIE
(www.hubbardresearch.com).
AIE synthesizes several methods from economics, actuarial science1, decision theory, and
Modern Portfolio Theory2. For example unlike methods that produce arbritrary “scores” or
speculative Return-on-Investment analysis, AIE uses an approach that conducts a true
“Risk/Return” analysis that would be recognizable to actuaries, economists, and financial
analysts. AIE has been applied to a wide range of decision and measurement problems in
both the private and public sector.
1
Actuarial science is the discipline that applies mathematical and statistical methods to assess risk in the
insurance and finance industries.
2
Modern portfolio theory is a theory of finance which attempts to maximize portfolio expected return for a
given amount of portfolio risk, or equivalently minimize risk for a given level of expected return, by carefully
choosing the proportions of various assets.
1
A typical result of applying AIE is that it is found that most variables considered or currently
being measured have an information value at or near zero; and only a few variables, often not
intuitive ones, have an information value that is so high that some deliberate measurement
effort is easily justified (Hubbard, 2010). Much of the value of the analysis may be obtained
in the first stages of defining and decomposing the problem into quantifiable dimensions,
determining what we know in terms of uncertainties, and computing the value of additional
information. Further steps include designing and applying measurement instruments and
analysis for making a risk versus return decision.
The workshop will have a two-day course on AIE, followed by 3 days of working through
example decision problems with Doug Hubbard. We do not expect to fully solve a decision
problem in this time frame but rather have sufficient insight into how we could apply the
methods as part of our way of doing information systems research, and acquire enough
knowledge to start routine application.
Workshop structure
Day 1 & 2
AIE Module I
The first 3.5-hour module of this two-module training is the AIE Module I, an overview the
AIE measurement approach. This module is intended for any analyst to C-level person who
has responsibility for creating, reviewing or acting on business cases or performance metrics.
This introductory module is for executives, managers or analysts who need to find better
measurement, risk analysis, and value assessment solutions. It includes the following topics:

Introduction to Applied Information Economics & Measurement: A method for
measuring anything and the three reasons why all perceived "immeasurability" is an
illusion

Dangerous Pitfalls: Why some popular decision making and risk assessment
methods may seem to work but don't

Understanding Measurement & Risk: How to think about risk quantitatively

Calibrated Probability Estimates: An introduction to methods to quantify your own
uncertainty about anything

Monte Carlo Simulations: How we “do the math” when we have no exact numbers

The Impact: How AIE can radically effect what and how you measure and the
decisions you make
Calibration Training
In the calibration session, HDR will teach the techniques behind subjectively assessing the
probability of uncertain events and the ranges of uncertain quantities. This is an essential skill
for anyone who needs to consider chance in decisions. Participants will see their skills
2
measurably improve during the training with a series of "calibration exams." You will also
learn some of the techniques involved in training others to be calibrated.
AIE Module II
This second 3.5-hour module builds on Module I and focuses on practical examples and cases.
In AIE Module II, the participants will see and be involved in an application of AIE in
practical case examples including:

Converting the basic business case to a Monte Carlo case with calibrated estimates,

Computing information values,

Selecting and using measurement methods including sampling methods, and
Plotting results against risk/return preferences and conducting basic portfolio optimization.
Days 3 – 5
Overview of approach to three contrasting decision problems leading to selection of one
decision problem for detailed analysis. (1/2 day on each topic).
Detailed analysis of selected decision problem. Stakeholders relevant to the decisions will be
invited.
Candidate decision problems:



Research targeting and evaluation: How to measure sustainable agriculture in terms of
CGIAR system level outcomes.
National decision: What information is needed to spatially target soil fertility
recommendations in Ethiopia.
Local decision: How to reward upstream land users for providing environmental
services to downstream water users in Sasumua watershed, Kenya.
Further information
For further information or to express interest in participating in the workshop, kindly contact
Keith Shephed (k.shepherd@cgiar.org).
3