How Can the Social Sustainability of Family Farms Be Measured?

Previous criteria used to measure social sustainability have their limits in the case of family farms. We propose focusing on workload. Initial results show that this is an easy-to-use and meaningful indicator.

Social sustainability is one of the three pillars of sustainability, along with economic and environmental sustainability. But how can it be measured in agriculture?

Focusing on employees in family farms is unhelpful

Previous criteria for social sustainability were based on aspects relevant for employees, such as the possibility of organising in trade unions. On family farms, however, family members do most of the work and there are often no employees. Such indicators are unhelpful here. We therefore aimed to develop an easy-to-use, automated indicator to enable family farms to assess their own social sustainability.

The main problem in Swiss agriculture with regard to social sustainability is workload. Depending on the calculation method, farmers work an average of 60 or more hours per week. As labour overload can have significant health impacts, including burnout, it is a plausible indicator of social sustainability.

Ratio between labour resources and required effort

As a first step, we developed an indicator that captures the ratio between available labour resources and required labour resources based on working time requirements. In a pilot study, we then calculated the indicator for 60 dairy farms, divided equally between lowlands and mountains. Dairy farms are both the dominant farm type in Switzerland and the type most affected by overwork. In a second step, we compared the results with a more elaborate calculation method. This confirmed that key workload trends can be identified using the simpler indicator.

Overwork is more prevalent in lowlands than in mountains

Both studies found that around a third of all farms suffer from potential overwork. The pilot study also showed that the simple indicator can be used to identify differences between groups, for example between lowlands and mountains. The indicator shows that overwork is more prevalent in the lowlands. However, the degree of mechanisation and the outsourcing of work to contractors probably play a role as well, and these are more developed in the lowlands than in the mountains. These factors would need to be taken into account when calculating the indicator in future.

Automated calculation in farm management systems is possible

The indicator was calculated for farms drawn at random from the AGIS database from the 2013 survey year, whose data were then anonymised. Working time requirements were calculated using the Global Work Budget (GWB) software application also used in Agroscope’s online tool LabourScope. In future, the indicator could be integrated into farm management information systems such as Barto and calculated automatically.

A further step might be to provide a benchmarking system allowing farmers to check how the workload on their farm compares to previous years or to other farms. Comparing their own farm’s indicator with other farms in the same region or category could initiate improvements in labour organisation by changing production system or hiring employees.