By Juliette ALEMANY
30th May 2022
A big shift is currently happening in the environmental and social sustainability landscape. Private companies can’t close their eyes anymore to what is happening in their supply chain. Consumers and laws are evolving and are now holding companies accountable. Therefore, the need to properly assess the level of sustainability is more important than ever.
A metric is a common word used to refer to a system or standard of measurement. Metrics are essential to quantify a situation as objectively as possible, establish a clear baseline of the level of sustainability, and measure improvement. Metrics are used to assess the impact of a project and to effectively communicate about it.
At Fairagora Asia, we might either work with metrics from an existing standard or with our own set of metrics aligned with international standards. We have identified the need to offer alternative frameworks for small farms to start their journey towards sustainability improvement. With this article, we wish to share some key methodology elements of our approach.
A general methodology to build metrics
The first step is obvious but of high importance: analyze the situation. Define clearly the objectives of the metrics, and identify the questions you want to answer. What do you want to measure and why? Where and how will the data be collected? Who will provide the data and how reliable will these be? Which level of verification will the project require? A thoughtful review of the existing standards will be necessary to assess if one of these could meet the project needs and therefore avoid duplicating efforts. It might not be the case, specifically if the supply chain involves small farms or if the project focuses on an unusual commodity.
The second step is to define general categories. This will ensure that your metrics are well organized and will make it easier to benchmark your framework with existing standards. It is always best practice to use as many similar categories as possible from well-recognized international standards.
The third step is to define a set of metrics for each category, with rules to establish when a metric meets the minimum requirements. In some cases, the requirements can be the upload of legal documents, eg. the working contracts of all the workers in a company. In other cases, a set of questions will inform the metric.
There is a wide range of variations in the complexity of the algorithm behind a metric when it comes to analyzing the results of the questions. It can be as simple as a “pass or fail” single question, or it can get more complicated: you can set trigger questions whose answers will determine the following questions, ask similar questions to different actors of the supply chain to cross-check their answers, and set up metric requirements conditional to additional information previously collected. Out of context, this last sentence is hard to understand. The following figure should help you to better apprehend the different complexity levels of the algorithms behind the metrics.
Additional complexity behind social metrics
While some metrics are easy to evaluate (eg. do all workers have a working contract or not), others can be much trickier. This is especially true in the social sustainability area. Some social metrics requirements can be subjective, therefore you need to ensure that your decisions are backed up by expert reviews. Social metrics also require particular attention to question formulation. Often, the surveys must be adapted to take into account information such as the education level, the language, the cultural background, or the social class.
It is also important to test the survey on a small sample of respondents before scaling the roll-out of the project. It is not unusual that the analysis of the answers collected in the testing phase highlights the need for question re-wording. Sometimes several testing phases are required to really optimize the wording, the number of questions, the answer types (eg. multiple choices, free text), and the data collection method (eg. online survey, mobile application, face-to-face interview).
How do social and environmental metrics interact?
It is always interesting and relevant to analyze the interactions between various metrics of your framework. In the long run, it can even help you to build some predictive risk assessment. Sometimes bad environmental practices lead to higher social risks. For example, a farm that uses a lot of chemicals and dangerous products should receive more attention regarding the health and safety of the workers.
In other cases, there can be a counter-intuitive trade-off between environmental and social sustainability. An example in the sugarcane industry is the pre-harvest burning practice. In terms of good environmental practices, the farm should avoid burning. However, when looking at the social-environmental interaction, the farms that suddenly stopped burning and that did not use any harvesting machine might require additional scrutiny on their social metrics. Why? Because the farm would then automatically be in need of extra staff hours to cope with the extra working time required to cut fresh sugarcane. Did the farm hire extra staff? If not, did any children help? Did the workers work overtime? Did they get paid for it?
How does Fairagora Asia work with metrics?
At Fairagora Asia, we work with metrics every day. Any new sustainability project that we undertake usually requires reviewing the metrics we will use to measure sustainability and impact. We might use an existing standard and adapt our questions to inform each category of the standard. We might also work with small farms that are not ready yet for any certification and audit process. When this is the case, we design intermediary steps and milestones. Small farms can easily get discouraged if the gap between the initial sustainability assessment and the next improvement milestone is too big. Therefore, the objective is often to work on a ladder of improvement and to give the producers a measure of their progress and achievements.