Step 1. Identifying relevant regions.

We want to represent high market shares of the product considered. Thus, we first identify the most important regions. This step entails the identification of the most important regions according to the purpose of the analysis. Thus, for the analysis of cost of production and competitiveness, the focus is on regional hot spots in terms of agricultural production in each country. In the vast majority of the countries, statistics can be used to perform this step. This way we want to represent high market shares of the product considered. Indicators used for this are livestock numbers and density per region.

Step 2: Identifying Typical (prevailing, most common) Production Systems.

The identification of typical production systems is conducted in close collaboration with local experts who are usually farm advisors, producer organizations or research institutions with close contacts to producers. The main reason for this expert-based approach is the general lack of economic statistics about production systems and their prevalence in most agricultural statistics. Characterization of the farms is made on whole-farm level (specialised vs. mixed farms, labour organisation, land ownership, capital and equipment etc.) and enterprise level (livestock numbers, breeds used, performance and reproductive indicators, feed basis, feed rations etc.).

Step 3: Data collection.

After the identification of typical farms or production systems, the data collection can be done in two ways. The first and preferred way is to conduct focus groups consisting of the research partner, at least one local expert (advisor) and four to six producers. The producers’ farms should come close to the characteristics of the farm identified in Step 2. A standard questionnaire is used and filled-in jointly with the focus group members, using the farm type and production system identified in Step 2 as a basis. The research partners act as moderators and direct the discussion around the typical farming situation in a typical year. The discussion aims at achieving a consensus for each figure, taking out extreme figures or particularities of the individual producers. Instead of calculating an average of the participating producers’ farms, the most frequent or prevailing specification for each variable and indicator is recorded. The second way is to collect the data from an individual producer that comes very close to the typical farm identified in Step 2 and then ‘typify’ this data by replacing the farm particularities by more typical information and data available from expert knowledge, surveys and technical handbooks. In both cases, consistent datasets are obtained.

Step 4: Processing and Validation.

Production and accounting model are used to analyse the data. They enable the calculation of physical (cropping pattern, yields, operations, inputs, animal performance, land use, labor, machinery, equipment, buildings) and economic parameters (prices, financing, overhead costs, variable costs). In recent years, some environmental indicators have been added, for example to calculate greenhouse gas (GHG) emission. The model produces a whole-farm profit and loss account, a balance sheet and a cash flow. At the enterprise-level, a total cost calculation is produced (including cash costs, depreciation and opportunity costs). In an ‘interplay’ procedure, results are reverted to the data providers. Changes in the data are made until an agreement is achieved that the data set is realistic, accurate and consistent.

Step 5: Updating.

The updating of the data takes place annually for all prices. Updates are either done for each farm individually or through national or regional projection data which are applied to the farms in a country. Every three to five years and where relevant, updates of the farm sizes (hectares, animal numbers), performance indicators and their organization (labor, capital) are carried out. All these steps are performed jointly with the research partners and the local experts in the countries.

Step 6: Discussion and Finetuning

The result of the farm analysis and other topics are discussed among network members in an annual conference which takes place in June and rotates around the globe. Here the partners can see “their” farms in the national and international comparison and explain differences within their countries and with other countries. Inconsistent data can also be identified within the scope of the benchmarking. Where necessary, data are corrected in a post-conference process. In September/October of each year, the partners receive a comprehensive result data base with numerous tools and options for selection, ranking and analysing data on enterprise and whole-far level. Additional data and tools on beef and sheep markets, prices, production and trade are available as well. A short summary report with the main findings is published on the agri benchmark website. Partners are encouraged to translate this report into their own language and publish locally.