Emmanuel Faber, former chairman of Danone, and other experts think coming changes in sustainability data will benefit nearly everyone with clarity and lower costs. Work on new standardization of data is accelerating fast as the finance and insurance sectors are demanding data to assess sustainability and risks; they want it to be as readily standardized and comparable as financial data.
The clarion call for global alignment on sustainability standards is being heard from all sides, from the SASB and ISSB to the SDGs and the World Economic Forum.1 COSA CEO Daniele Giovannucci explains: “This is sorely needed in order to clearly define compliance now that sustainability is increasingly being brought into the policy and regulatory sphere, as it is in Germany, US, Netherlands and France, for instance.” The coming EU Corporate Sustainability Reporting Directive will require better corporate data on business risks to sustainability and BSR recently remarked that this is “nothing short of a revolution.” 2 Sectoral standards such as Bonsucro’s for sugar or the Global Coffee Platform’s Common Data Standard offer valuable approaches but will likely also want to fit into broader global guidelines as these emerge. This bodes well for food and agriculture sustainability. Transparency will increase, and costs of data and traceability decrease as reporting is streamlined. The value of standardization is, more than ever, self-evident.
The problem of diverse supply chain data technologies
The proliferation of digital solutions to address needs in the agriculture value chain is a welcome advance. Unfortunately, the differences in approach have led to a landscape of fragmented, stand-alone solutions and huge inefficiencies and disparities as different systems offer different results.
These systems, such as farm management systems, ERPs, traceability and payments solutions, are continually duplicating efforts as multiple entities collect similar data. Data remains siloed in different platforms, each with proprietary data architectures and vastly different analytical capacities and overall quality.
The result is an excessive reporting burden for all the actors in a supply chain, squandered resources and, most importantly, missed opportunities for shared learning and real usefulness or impact.
Standardizing how we measure the realities of supply chains to the farm level is building a shared understanding of sustainability and risks. It means starting with common indicators to align efforts and reporting. But there is still a notable chasm between the current confusing scenario and the likely standard future scenario we’ll see in less than five years.
Richard Rogers, Managing Director of Rogers MacJohn, offers that “while many companies and organizations believe they have a viable sustainability approach, many simply do not.” Three characteristics have emerged from COSA’s decades of work in this area to define those viable approaches that really make a difference:
Measuring what matters – choosing the right aspects for each topic, from child labor to deforestation
How well they measure sustainability factors – sloppy data protocols commonly masquerade as data, and private or hidden processes are indicators of that
Whether they operationalize and put their findings to use within the company or project
But, whether a current data approach is viable or needs updating, we suggest two perspectives that will align you on how data will be increasingly used in the not-too-distant future.
The first is that to enable good credible information, it is vital to adopt solid protocols for data gathering that use simple and consistent science-based indicators.
In most cases where organizations invest in sustainability programs, too little attention is paid to getting comparable data. This may leave some making misinformed claims of success and others failing to identify poor performance. Having even the most simple science-based comparisons can deliver benefits in terms of lower risks, better performance and conserving resources. There are plenty of opportunities to use this approach.
We have seen it work first-hand. The Inter-American Development Bank’s multi-year investment in the Sustainable Agriculture, Food, and Environment program was able to make some surprising findings from the then-novel ability to have basic comparable indicators for its projects. They showed, for example, where women producers were succeeding more than their male counterparts and where their capabilities were correlating with better access to finance. If we can better measure and compare, we can learn how to create the enabling conditions that accelerate such improvements.
This problem also occurs when donors allow implementers to report using bespoke and unaligned monitoring and evaluation designs. This typically prevents them from benchmarking or comparing results, and they may miss out on vital learning or ways to improve and scale programs. One positive example has been the Ford Foundation, and now the Bill and Melinda Gates Foundation is testing ways for program investments to rapidly secure and use comparable science-based data. Our partnership on Agile Data® approaches will streamline data collection, facilitate analytics, and help drive superior results and scalability.
2. The second perspective worth understanding is a nascent interest in establishing interoperability among varied current standards and the different ways of capturing, organizing, and reporting data.
Given the abundant and growing list of approaches as well as many proprietary technologies available to conduct traceability or measure supply chain sustainability – and the inability to compare between them – the benefit of interoperability for the food and agriculture world is clear.
Wimmer and others (2018) simply define data interoperability as the ability of organizations to interact towards mutually beneficial goals involving the sharing of information and knowledge through the business processes they support by means of the exchange of data between their ICT systems. Of course, for sustainability, that is important, but we would add that interoperability will also require an approach that is both tech neutral and standard-neutral. Then, to be functional and widely accepted, it also needs to be fully transparent and science-based.
The good news is that in food and agriculture systems, we are now closer to making that kind of interoperability a reality. Establishing standardized technical specifications is a big deal and cooperation is key. COSA is working together with GS1, DIN (ISO), GIZ, and others to establish a Sustainability Data Standard and pilot it.3 This first standard will be developed initially to cover Traceability functions, Costs of Production, Living Income, and Deforestation. The Sustainability Data Standard will be designed for extensibility, making adaptations to diverse kinds of data possible.
Lessons on standardization from a surprising source
The food and agriculture sector could take a lesson from another industry, autonomous vehicles. That sector is working hard to erase current consumer perceptions of self-driving cars as unsafe. Standardization of information is one of the keys holding back progress. Proprietary technologies used in autonomous vehicle safety systems have been developed independently by businesses. This lack of standardization in tech solutions has slowed learning and development. “The problem is that as long as industry players compete with different approaches to understanding safety, this will lead to… confusion, unnecessarily complicating how consumers, government agencies, and transportation companies understand [the needs]” says the IEEE Standards Association for the industry. After more than a decade, the IEEE is now proposing a ‘technology-neutral’ standard for safety in order to facilitate progress.
For most businesses and their supply chains, data interoperability will facilitate internal information for mutual benefit and the credibility of their external reporting. It is not just for business; at the policy and governance levels, the benefits include a better understanding of what is working to advance sustainability. The Sustainability Data Standard is expected to allow economies of scale, reduce costs of data, and bring a critical mass of actors together into this digital ecosystem.
Data on farmers in the food and ag sector has come a long way in the last decade. Our ability to gain sustainability knowledge is evolving beyond basic descriptive points. We see the clear path toward having the enormous advantage of both predictive and prescriptive analytics that are facilitated by AI. Getting there will require standardization and interoperability of systems.
1. “The existence of multiple ESG measurement and reporting frameworks and lack of consistency and comparability of metrics were identified as pain points that hinder the ability of companies to meaningfully and credibly demonstrate the progress they are making on sustainability (The Davos Manifesto 2020)
3. GS1 is the world’s leading barcode developer and standards regulator for consumer goods. DIN, the German Institute for Standardization, is a member of the International Organization for Standardization; all are partners with COSA in the Digital Integration of Agricultural Supply Chains Alliance (DIASCA). with the support of GIZ
