This study aims to establish the current status of farms in regards to BPS payments, performance and resilience; and understand how farmers feel about the future of farming; identify future action plans to be implemented. The project analyses quantitative and qualitative data collected from up to 2000 farmers in England represenative all major farming sectors and will present a typology of farmers for targeted communication and support. The free-text action plans will be analysed using IBM AI Text Analytics using bespoke local library co-developed between the partners.
Direct payments under the Basic Payment Scheme (BPS) will be phased out in England by 2027, with some 38% of farm businesses having costs that exceed revenue when direct payments are excluded (AHDB, 2021). Furthermore, 48% of farmers indicate that the loss of BPS will have biggest impact on business going forwards (DEFRA, 2021). Studies have indicated that 76% of beef and sheep and 67% of cereal farmers are either not planning on making changes to their businesses or are adopting a wait and see approach to current policy changes (AHDB, 2021)
Defra provided funding for business support, through the Future Farming Resilience Fund (FFRF) for organisations to bid into and provide support to farmers to help adapt to the policy changes. AHDB won a bid in July 2021 to provide such support, which was delivered through the AHDB Farm Business Review (FBR) service Project. This project analyses three sets of data based on the resilience survey, KPI survey and individual action plans conducted during September 2021 to May 2022 with farmers in England.
The analysis aims to answer the following key questions:
Methodology - Participation in the project was voluntary and eligible farmers included those in the beef, sheep, cereals and dairy sectors. Data collected from farmers in England included farm attributes, farmer attributes, farm business review items (outputs from the BPS calculator, Resilience Survey/self-assessment, and KPI identification) and a personalised agreed action plan written by the visiting consultant (free text). The quantitative data analysis provided descriptives of attributes and farm business resilience self-assessment results and farm business key performance indicators (KPIs), farmer’s feelings about the future of farming, their action plans and their current and future use of business management tools. Comparisons and associations were analysed using paired samples t test, correlation, ANOVA test and linear regression. A typology of farmers was identified using two-step cluster analysis. Qualitative thematic content analysis was used to analyse the free text of personalised action plans. Using IBM SPSS Modeler Text Analytics, a supervised text mining approach was applied. The accuracy and coverage of the text mining was incrementally improved through the co-development of a project-specific language library within categories (themes) and subcategories agreed between the HAU and AHDB research teams.
Agriculture and Horticulture Development Board (AHDB)
91Pro
Sarah Hurford, Steve Dunkley and Sarah Baker (AHDB)
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