Introduction to our new approach to indicator data
Data is the foundation of effective sustainability efforts, and is integral to our approach at the Rainforest Alliance. Reliable data is not only essential for farmers to track sustainability progress, and ensure access to evolving markets, but also for businesses in response to growing pressure to report on their social and environmental impact.
With version 1.4 of the Rainforest Alliance Sustainable Agriculture Standard, we have made important changes to indicators and data points to improve data quality in certification.
In this section we will explain why we have made these improvements, and we will give you a brief overview of the key changes and the benefits for you.
Why did we make the changes?
Data collection is important, but it can be challenging. Complicated collection methods, inconsistent data interpretation, as well as lack of data accuracy, can all undermine the quality and reliability of data.
The changes we adopted were made to reduce administrative work for farmers and better support the collection of reliable and good quality data.
The key changes are:
- New simplified indicator structure
- Fewer, more meaningful data points
- New annex for indicators
- New guidance document for data points and data collection
- Clearer data validation processes
1. New simplified indicator structure
In the standard version 1.3, we had different types of indicators: core indicators, mandatory improvement indicators, smart meters, and self-selected indicators.
In version 1.4, we simplified this structure by now having only a set of core data points. A few of these are linked to continuous improvement requirements in the standard.
2. Fewer, more meaningful data points
We have reduced the number of data points by about 70%.
We have prioritized data points that are the most critical for farmers and companies, aligning well with both market needs and legislative requirements. While some data points remain unchanged, others have been refined for clarity and consistency.
The reduction in data points does not mean that we removed entire topics. Instead, we shifted toward collecting more targeted data. We are focusing on essential data that is needed to drive and demonstrate impact.
In version 1.4 nearly all data points are connected to specific requirements making the data collection process a natural part of certification and compliance. Therefore, it is even more important that the data being collected is accurate and of good quality.
3. New annex for indicators
Indicators or data points are no longer all listed in the standard document itself. They now have their own binding annex, which is linked to requirement 1.7.1.
As per requirement 1.7.1 management is ultimately accountable for accurate data collection and for the reporting of data points via the Rainforest Alliance Certification Platform (RACP).
We will now also collect data at farm level for large farms within a group. On the Rainforest Alliance Certification Platform there will be a separate questionnaire per large farm of a group. The group management is responsible for reporting the data, ensuring it aligns with internal records, and resolving any discrepancies.
4. New guidance document for data points and data collection
We will now provide a new guidance document to support the collection of data points. It explains each data point in detail, with measurement units, a recommended collection method, and frequency of collection. This guidance is not a binding document but aims to serve as a guide for Certificate Holders.
5. Clearer data validation processes
As with previous versions of our standard, farm Certificate Holders will remain responsible for data collection. However, in order to better ensure both the quality and accuracy of the collected data, we are introducing a strengthened data verification processes at the auditing stage. Previously, during audits, independent, third-party Certification Bodies only checked whether data collected by Certificate Holders was complete. Now, these Certification Bodies will verify and validate the data collected. That means that they will check the evidence and approve that the information is relevant, consistent, complete, and accurate. This will better support Certificate Holders in their data reporting practices.