The data standard for coffee sustainability indicators allows all actors along the coffee supply chain to compare, aggregate and exchange coffee sustainability data without having to clean and reorganize data manually. This enables the sector stakeholders to:
- align and streamline sustainability measurement
- reduce (data) production & transaction efforts and cost
- prepare for SDG and sustainability reporting requirements (e.g. EU legislation)
- publish comparable sustainability data
The data standard can be applied independent of any specific technology solution or reporting engine. Anyone working with data and sustainability measurement will be able to implement the results into any technology solution.
In terms of data exchange between commercial supply chain actors (farmers, cooperatives, traders, agents, roasters, retailers), there are two major use cases, vertical and horizontal exchange.
On the one hand, the standard might be used to facilitate data flow within one vertical and private supply chain between two or more actors, e.g. from the cooperative to a trader or from the trader to a roaster. I.e. a cooperative might pass on sustainability information attributed to the produce to a trader, who in turn might pass it on to its customer.
On the other hand, the standard might be used to facilitate horizontal exchange and aggregation between peers, e.g. to support joint sustainability reporting for a specific region or country. This might be especially relevant for the implementation of a sustainable region or a jurisdictional approach to sustainability, also known as verified sourcing area.
More specific use cases of the data standard include:
Narrative 1: Demonstrating impact¶
Standards & companies are better enabled to demonstrate impact in a comparable manner and their contribution to collective impact with minimal additional effort. The Global Coffee Data Standard creates a baseline of data elements which can be used for the purposes of international reporting. When these indicators are implemented by mapping internal data to the Global Coffee Data Standard, reports and even comparisons between organisations are easily made. The indicators in the Global Coffee Data Standard are aligned with the Sustainable Development Goals, the ISEAL Common Core Indicators as well as other relevant publicly referenced indicator sets.
Narrative 2: Improving data quality¶
When the Global Coffee Data standard is widely implemented, datasets can easily be exchanged between organisations. This enables certification standards, companies and public institutions to cross-validate data, leading to a significant data quality improvement.
Narrative 3: The development of farmer services¶
Standardized data make it easier to develop targeted farmer services. E.g. if farm-level data are available in a standardized format, a bank can develop protocols to use this data to determine his or her bankability. Equally, other service providers, such as extension services, logistics or an input provider, will be enabled to operate more efficiently with better information available. Better comparable data can as well lead to better targeted agricultural policies by local and national governments.
Narrative 3: Reducing the effort of data collection¶
Data collection in the field is a demanding task, both for the farmer as well as for the data collector. Availability and exchange of farm data may reduce the need for additional data collection, for at least for the standard indicators. The existing data (of another organisation) may even be used for data analytics, for example to determine which area these problems are most likely to occur.
Narrative 4: Supporting traceability¶
Consumers more and more want to know where the product the buy comes from and how sustainably it is produced. When coffee data is globally standardized, this information can be provided to consumers about all coffee producing areas in the world in a standardized way, tapping into a global data resource.
Narrative 5: Supporting the development of sector-specific information technology¶
Currently every company, standard, public institute is developing its own technical infrastructure to manage or monitor the coffee sector. If these actors are more aligned in which data is collected, how data is collected and how data is stored, it will become easier to develop the specific digital tools. This applies to data collection tools, management information systems, data analytics, visualization and data exchange via an API.
Narrative 6: Facilitating certification audits¶
The role of a control body is to inspect if all practices at a farm or farmers group are being performed conform certification requirements and to inform the voluntary standards system about the results of the inspection. If the auditor, the person who actually performs the inspection, could receive farm data in advance, he could make a pre analysis which farms he likes to visit and can use this information as a guidance in the field to focus on specific farmers or topics. The data can also be helpful to validate some audit points in advance before the field visit or to pre fill some of the data points that need to be collected in the field, for example it is less work to check a field boundary then to measure it, saving time and money. The reuses of existing data will be facilitated if all organisation use more or less the same data formats, can map their data on an exchange format and use the same data collection methods.