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Agricultural policies can only be successful if their objectives are achievable and the sector constituents (farmers) wish to achieve the stated objectives. To ensure that objectives are achievable decisions need to be based on evidence on what can be achieved by reviewing current practice. Therefore the way to garher this information or evidence requires an identification of:
  • objectives
  • appropriate analytical method/s
  • target data sets
The objective might be the collection and review of data on the existing ranges of production unit performance such as crop or animal production yields. The anlytical method applied is to compare existing data on low, average and high yields based on surveys that involve farm visits to collect the data.

Reliable procedures that can contribute to policy diagnostics and design to secure traction can use DRMs (Data Reference Models) to define the analytical procedures and then use a 4P type system (Policy Procedure Prototyping Platform) to create a decision analysis model and simulate, test and refine it.
McNeill, H. W., "A simple benchmarking model", SEEL, DAI 2010-2015, London (2012).


Policies for the agricultural sectors need to have effective traction. Traction is the achievement of pre-defined objectives within the desired time frame.

Good policy design should not only secure traction but it should also be designed to achieve this involving the lowest administrative outlays in terms of human resources deployed and the funds allocated.

The topic of traction inplies that policy-makers and the agricultural sector have an expectation as to the time it will take to achieve a specific objective. It is self-evident that for this to be possible, the decision analysis procedures applied to identify the best policy options need to be based on:
  • an appropriate decision analysis model defined in collaboration with the main stakeholders
  • good quality data
  • sound estimates of the probability of events that can affect outcomes
For further information on model design and cycle, select the appropriate menu items above.



The range of traction capabilities can be determined on the basis of diagnostics. This needs to be based on realistic data on what is achievable in the field, that is, based on precise survey data collected on farms of the range of practice in terms of low, average and high yields for each enterprise1. It is also necessary to obtain the combinations of the variable inputs2 associated with each yield. This combination is referred to as a technical package and this would normally be the content of communications between extension services and farmers. All technical packages can benefit from adjustments relatedto eh specific conditions on each farm such as drainage, soil structure, altitude-temperature relationships and the like.

The average yields associated with low, average and high outputs are reference yields of benchmarks that mark out the range of achievable yields for each crop or animal production enterprise.



This information needs to be complemented by transition delay estimate. These are the time it takes for a farm to improve performance by moving from a lower benchmark to a higher benchmark. This information needs to be assessed in collaboration with farmers and extension agents since they can very according to specific farm priorities, investmenrt cycle, farm sizes and income levels and other factors.



In order to simulate the above in the form of a decision analysis model use can be made using 4P-type modelling, see the menu item PPPP for further information.

1  An enterprise is a specific production activity on a farm such as soybeans, corn, alfalfa, beef or milk.
2 variable inputs incluse such inputs as seed, fertilizer, labour hours, fuel, pesticides and machine time. These varu with scale of production (area of production or number of animals)

The Decision Analysis Initiative 2015-2020
George Boole Foundation