Decision support systems in practice - some observations. David Freebairn
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This document discusses observations about decision support systems in practice based on the author's experience. Some of the key points made include: 1) Simple systems tend to work best and be most transparent, while complex systems can be opaque and inaccessible. 2) Farmers are experts in decision making for their operations based on a variety of factors, while external experts can play a supporting role. 3) Decision support tools should acknowledge limitations, focus on providing information rather than recommendations, and recognize farmers as the primary experts in their decision making.
Decision support systems in practice - some observations. David Freebairn
- 1. Decision support systems in practice - some observations David Freebairn RPS Brisbane, Australia
- 2. Outline • Simplicity and transparency • Who says the world has to be complex? • Acknowledge stakeholders as experts • Modesty and limitations • Ideas, comments, suggestions
- 3. Experience -background And many good ideas from my colleagues in DPI, DERM and CSIRO
- 4. General observations • Many decisions are simpler than we think • Many analytic tools are complex, inaccessible or opaque • Computers are good at simple tasks (e.g. arithmetic) • Humans are good at complex tasks (e.g. decision making)
- 5. Complexity and Generality Relative aerial applicability Detail Rules Simple Complex DSS Of thumb simulation simulation
- 6. The struggle between usefulness (goodness) and complexity http://www.dau.mil/pubscats/PubsCats/atl/2005_11_12/war_nd05.pdf
- 7. Soil management, water conservation, erosion
- 8. Rainfall simulation - a research and extension tool Stubble cover Bare soil
- 9. Howwet?
- 10. Simplicity and transparency • The simplest things generally work best, and the simpler the better. • The easier a decision support tool is to use and support. • More complex >> less transparent. • Active demonstrations are most effective learning tools.
- 11. Who says farming is complex? • Increased complexity is a common pathway for scientists. • What challenge farm decision making though is uncertainty. • There is a view that many models should be used in an “instructive” mode.
- 12. Acknowledge stakeholders as experts • Remember who has the greatest vested interest in problem solving. • The farmer is clearly the best expert, and expert farmers often use a range of other experts to support them. • Being useful to decision makers requires getting into their shoes.
- 13. Modesty and limitations • Acknowledge external “experts” have small roles to play
- 14. Tactical decision making - where is the niche for improved information? •System status -history (weather, previous crops) -monitoring (soil water, weeds, disease) •Weather futures - based on history - forecasts Decision •Market futures point •Fit in the system •Personal preferences
- 15. Tactical decision making - how do farmers view this? •System status -history (weather, previous crops) -monitoring (soil water, weeds, disease) •Weather futures - based on history - forecasts Decision •Market futures point •Fit in the system •Personal preferences
- 16. Importance of various elements in decision making – e.g. planting 8% 20% Disease 8% risk Starting soil water Gut feeling 8% Weeds Climate 15% forecast adjustment Soil N Note: 8% Use this figure to focus discussion on what are Seed the issues and their Price relative importance availability (no correct answers) 8% 30%
- 17. Estimating soil moisture - the simple “push” probe “2 feet of moisture”
- 18. Simple vs. less simple Fallow efficiency -20% fallow rainfall HOWWET? -daily model 300 R2 = 0.72 1:1 Line 250 RMSD = 28 mm Predicted (mm) 200 y = 0.82x + 29.6 150 Acland 100 Capella Greenmount 50 Wallumbilla Warra 0 0 50 100 150 200 250 300 Observed (mm)
- 19. Influence of stubble cover on soil erosion Average annual soil loss (t/ha) 50 Bare fallow 40 30 20 Stubble incorporated 10 Stubble mulch Zero-till Pasture 0 0 20 40 60 80 100 Soil cover (%) Greenmount (Qld) 1978-88
- 21. Some issues Queensland farmers consider • What are the chances of a planting rain? • What are current moisture, nitrogen conditions? • What are implications for yields? • Input needs?
- 22. Component questions for simple models • What are current conditions (e.g. moisture heat sum)? • What are the chances of a future event (e.g. planting rain, frost, wet harvest)? • What is skill in a forecast? • What are the implications of above, and what management options are there to adjust?
- 23. Linking conditions NOW and Future probabilities Recent Now Future History (the decision point) outcome Rainfall Current Expected drivers Temperature conditions •Rainfall •Temperature Range of Soil water Options Previous crop Nutrition Based on and Soil type Disease •History outcomes Management Weeds •Persistence •forecasts -supported by new observation Time line
- 24. What are the chances of getting … Rainfall 50 mm Temperature > 30 OC Temperature < 3 oC Heat sum 200 oC days In 10 days, between Occurs in 54 % of years between 1912-2010 Maximum in each year Previous analysis
- 25. How is the season progressing? Rainfall Max. temp. stress days Min. temp days Heat sum oC days Between Season to date rainfall from dd/mm/yyyy to dd/mm/yyyy 9th , 5th and 1st decile Previous analysis
- 27. Enlightened DSS design • Question focused, client focused • Easy to use and ready access • Multiple access points • Transparency • Information, not advice • Efficient • Recognise life cycle
- 28. How do we ensure we move 1, 2, 4?
- 29. Thankyou