Bennett Wetch

We are still very much in the innovation and early adoption phases of leveraging technology to drive impactful sustainability practices across the agriculture and manufacturing sectors. While the technology to collect, manage, and communicate sustainability data has become much more accessible for companies of all sizes, the impact of these technologies is still nascent for three primary reasons:

1. Much of the commonly used technology relies on descriptive data for retrospective reporting, which is inherently limited in its ability to influence business transformation and product innovation. As sustainability data technologies become more predictive and prescriptive, they will empower organizations across supply chains to better evolve their business model with people and the planet in mind.

2. Data interoperability is limited, and therefore leveraging standard frameworks for scale is not yet a reality. While common structures have begun to form around emissions reporting and operational health/safety, many facets of socioeconomic and environmental sustainability reporting lack commonality, which creates an undue burden on those who seek to measure or report on these essential topics across complex supplier ecosystems.

3. The financial models of sustainability technologies are inconsistent and difficult to navigate. In some supply chains and sustainability programs, the producer organizations are financially responsible for the technology costs, which creates internal debate on the solution’s intrinsic value versus simply enduring the price to meet buyer demands. In other contexts, it is common for a buyer to pay the bill for technology deployment amongst a supplier or group of suppliers. In this case, the buyer who is subsidizing the technology often has free-rider concerns as their supplier’s other customers will be in a position to benefit from the technology solution without bearing the expense.

To accomplish greater scale, the companies building sustainability technologies need to better embrace pre-competitive collaboration to reduce the reporting burden on producers. The industry can solve this by improving: 1) data interoperability, 2) data propagation, and 3) data ownership.

1. It is far too common for well-meaning brands and retailers to source from a shared set of producers yet have varying sustainability reporting requirements amongst them. The data points requested of producers across various environmental and social compliance systems often have quite similar intent but are framed just differently enough that the producer is essentially answering the same question in multiple different ways. As supply chains continue to become more matrixed and complex, the sustainability data sector needs to recognize the reality of how inconsistent data definitions negatively impact producers.

2. In addition to a lack of data interoperability, even when data points are similar, producers must endure redundant data entry across the various systems preferred by the buyers and retailers in their supply chain, requiring the supplier to navigate a myriad of similar yet different data technologies. Sustainability technology providers need to incorporate the idea of producers being able to enter data once into their preferred system and then propagate those data sets across buyers’ preferred systems. This will require collaboration amongst competitors, but it will ultimately enable the field to scale in ways it currently cannot. We can see examples of this being done successfully in the financial services software sector.

3. We must do a better job of ensuring that the market for sustainability solutions does not result in a future where data has become the next extractive commodity in agricultural and manufacturing sectors. The future of sustainability technologies should include creating data economies in which producers receive direct financial compensation for making their socioeconomic and environmental metrics available to buyers, governments, and consumers. Data collection efforts will exacerbate the lopsided power balance between suppliers and buyers until these technologies regularly produce a direct financial or operational benefit to producer organizations.

Sustainability data in agricultural settings is most commonly used for descriptive and retrospective reporting purposes, and often the requirements are defined at the behest of buyers or certifiers while the burden of reporting is on the producers. As a result, data technology implementation is often burdensome for farmers or FPOs in developing economies while also lacking an immediate and direct benefit.

We have begun to notice a few agricultural data products targeting non-industrialized farm settings that are predictive in nature and therefore directly benefit the farmers themselves, but these are still exceptions rather than the rule. Although when available, many of these solutions require extensive onboarding and user-interface training, which is an unacceptable opportunity cost for busy farmers who may be unexposed or raw to incorporating technology into their agricultural practices.

In my opinion, to overcome these challenges, technology providers need to ensure they place farmers at the center of their user experience research and design the UI based on their needs. They must then leverage those findings to design systems that accommodate the fact that farmers in developing economies have different connectivity and technical literacy baselines than their counterparts in more developed economies.

Visibility into the provenance and lifecycle of a product has become even more critical as the pandemic has profoundly disrupted global trade. Buyer trips, production inspections, and other in-person supply chain interactions came to an unprecedented halt in 2020. Undoubtedly, the changing dynamics of international supply chains have magnified the importance of detailed information about product specifications, production capacity, compliance adherence, impact outcomes, and other attributes being easily accessible to buyers along the supply chain. Many forward-thinking organizations have championed traceability efforts to improve supply chain security, enhance impact reporting, and mitigate reputational risks. Hereafter, traceability backed by data will be a fundamental necessity for successful supply chain management as global travel becomes less of an implicit assumption in trade relationships.

I believe the following will be relevant regardless of what 2021 throws at us:

1. Product-level traceability will become a trade expectation rather than a surprising revelation occasionally offered by innovative brands. Over the past several years, various companies have led the way in releasing detailed maps of the supply chains behind specific products, but in 2021 I expect this type of transparency to become more commonplace.

2. Sustainability data strategies will become more forward-looking and less retrospective. The current annual cadence of sustainability and impact reports helps fulfill compliance and governance requirements, but its backward-looking nature makes it ill-suited for driving business transformation. In 2021 we expect to see more organizations applying data science capabilities towards building models that can predict various environmental and socioeconomic outcomes based on potential changes in product composition or supply chain design.

3. The intersection of socioeconomic and environmental sustainability will continue to gain traction with local, regional, and national governments. While we have seen many examples of positive progress with requirements related to emissions and trafficking, we will see regulators paying added attention to topics such as living wages, water usage, waste, and more in 2021.

There are many other exciting trends in sustainability that I look forward to supporting in 2021, and I’ll be sure to check back at the end of the year and see whether the above predictions came true and to what extent.