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GECAFS DSS Inaugural Workshop
Jan 11, 2005
Steve Sonka
University of Illinois
Agenda• Philosophy
• Demonstration
• A Case Study– Results, – Effects, and – Lessons
Philosophy (1)• Factors in the “external environment”
– Government policies– Technology– Biogeophysical
• Human decision making processes are challenged when decisions involve– Time lags (between decision and outcome)– Uncertainty– Causal ambiguity
Philosophy (2)
• Strategic versus operating choices, – Climate versus weather– Operating choices
• Routine• DSS’s enhance
– Strategic choices• Humans & DSS’s tend to struggle
• Effective DSS’s for strategic choice– As much to generate better questions– As to provide answers
Philosophy (3)Decisions, Decisions, Decisions
• DSS’s inform, don’t make decisions
• Decision will come from some group process
• DSS not likely to be “used” by decision maker
• Credibility must be earned, but not by use
• Decision maker(s) won’t be able to give enough attention
• Decision makers– Can describe problems/issues/concern– DSS developer is responsible for design
Visualization Principles:Tufte
• Escape the Flatland (of 2 dimensions)
• Color
• Compared to what ?
• Time as the 4th dimension
• Macro / micro perspectives
The Case Study• Client
– Illinois Soybean Program Operating Board– NGO– Mission components
• Market development• Research
• Charge: Help us better anticipate the future global need for protein– Longer term perspective– Enhance commonality of perspective– Improve communication across sector
The Dynamics of Protein and Malnutrition
• Charge from soybean industry leaders: Help us better anticipate the future global need for protein– Longer term– Commonality of perspective– Accurate, science-based methods
The Protein Consumption Dynamics (PCD) Model
• The PCD model– A system dynamics simulation engine
(Powersim)– A visualization delivery tool (In3D)
• Driving forces in the simulation– Population– Total income– Diet choices relative to per capita income
Relationships Underlyingthe PCD Model
TotalAppetite
Per CapitaAppetite
Total Population
Total Income
Cultural Influences
Income DistributionPer Capita Proportion
Malnourished
TotalMalnourished
Commodities of Interest
Regional Aggregations
Move to Visualization
• Fisher, D. K. 2000. Assessing how information affects cognitive maps of strategic issues. Unpublished Doctoral Dissertation. University of Illinois, Urbana-Champaign.
• Fisher, D. K., S. T. Sonka, and R. E. Westgren. "Strategic Decision Making in the Quasi-Government Sector: The Illinois Soybean Program Operating Board" International Journal of Organization Theory and Behavior, 7(2004):42-65.
Effects
• Quasi – experimental measurements
• Anecdotal interpretation of actual decisions
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Before After
Population
Income
Malnutrition
Meeting demand
New markets
Ranking of Strategic Issues:Before and After Intervention
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Before After
Population
Income
Malnutrition
Meeting demand
New markets
Marketing
Soy foods
Global
Health benefits
Ranking of Strategic Issues:Before and After Intervention
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k: (
1 is
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10
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Before After
Population
Income
Malnutrition
Meeting demand
New markets
Marketing
Soy foods
Global
Health benefits
New uses
Biotech acceptance
Soybean price
GMOs
Ranking of Strategic Issues:Before and After Intervention
Ran
k: (
1 is
MO
ST
impo
rtan
t)
Implications / Effects• Existing marketing / promotion skills and
resources are aligned with past, not the future (geography and practices)
• Global income growth is #1 strategic issue (international trade policy)
• Efforts to reduce malnutrition should be on the strategic agenda for human and business reasons (World Initiative for Soy in Human Health)
• Development of Version 2 funded
Lessons• Strategic choices / DSSs have distinctive
characteristics
• Philosophy: goal is better conversation
• Visualization: Tufte principles are helpful
• Case study: – intervention and– the IT-based tools
