In our last newsletter, we mentioned that we’d be taking a closer look at some of the themes that emerged from our recent annual reflection on our progress, and our learnings on those themes thus far. We’re starting with transparency and risk assessment tools, which play a large role in our theory of change.

We invest in tools that can be used by companies, suppliers, governments, NGOs, trade unions and advocates to improve conditions for workers and increase respect for labor rights in global supply chains.

What function do transparency and risk assessment tools play in this work? How can they be compared to one another? And, most importantly, how can the use of transparency and risk assessment tools improve the lives of workers? Here’s how we’re currently thinking about these tools.

TRANSPARENCY

Transparency schemes start from the premise that entities within a supply chain frequently do not know each other’s identities beyond immediate relationships. An apparel retailer likely knows from which factory a finished garment came from, but may not know which suppliers provided the fabric or buttons, much less where the cotton came from. Similarly, a smallholder farmer is unlikely to know what happens to her cotton harvest after it leaves her farm, which is an obstacle as she tries to derive more value from her harvest. There is value to be gained for businesses (buyers and suppliers), farmers, and workers by illuminating the full scope of a supply chain.

Traceability and transparency schemes deliver differing value to different stakeholders, based on the ways in which they are designed and used. Design considerations relate to the categories, depth, and derivation of the information captured and presented within the scheme. Use considerations relate to the way in which the scheme and the information that it presents enable decisions to be made.

Design: While there is some benefit to simply identifying lower-tier supply chain actors, greater potential impact results if the social/labor characteristics of those actors are also presented. More impactful transparency schemes present information about working conditions:

  • That is generated by rights-holders like vulnerable workers;
  • That is externally verified (certifications, credible third-parties) as opposed to self-disclosed by businesses;
  • In a way that is available to a wider range of actors (including publicly) rather than a tighter, narrower (private) distribution;
  • Is differentiated on the basis of the strength of an intervention or characteristic (e.g. GoodWeave certification is more rigorous than a standard social audit regime);
  • That can be correlated or linked with other risk factors (like counterfeiting or illegal activity like corruption).

Schemes can be differentiated by the usefulness of the information they gather and provide. Depending on the content they present, schemes can:

  • Disclose the location and identity of a lower-tier supply chain actor (even linking with verified external ‘identities’ like those which will be presented in the Open Apparel Registry);
  • Enable the identification of shared suppliers for multiple buyers, facilitating shared remediation (an example is SupplyShift, in which the Fund has invested);
  • Enable the identification of risky suppliers, either due to sharing across supply chains (as with Verité’s Cumulus) or through an overlay of information (like the Global Slavery Index);
  • Enable information to be shared with producers and less powerful actors, and be designed and used in a way that facilitates and enables less powerful actors to exert influence over business decision-making in the supply chain.

Use: Impact emerges from the use of a transparency scheme if the information generated by the scheme becomes the basis for an action. The strength of the actions taken will generally be functions of the commitment (including voluntary will and regulatory or ethical obligation) of the supply chain owners.

The Fund’s theory of change holds that impact will be achieved when the scheme is used to make a decision that promotes good working conditions. These might be ‘positive’ decisions, such as when a buyer provides support for improved supplier performance through capacity building, or when a buyer applies preferences to the high-performing supplier in the form of (for example) more orders or preferential payment terms. These might be ‘negative’ decisions like cutting a poor-performing supplier after engagement. We accept that here is a possibility that the transparency or traceability information provided in the scheme might be ignored by the client or user, in which case the opportunity for impact might be lost.

RISK ASSESSMENT

Corporations dedicate resources to social auditing in their supply chains, avowedly to identify and remedy instances of labor exploitation. However, social audits are often ineffective, lack credibility, and frequently do not lead to changes in procurement or remediation decisions. Multinational buyers need information about working conditions that is more accurate, more timely, more granular, and more scaled than that which social audits generally provide, and ideally that information is available before or during a procurement decision. Risk assessment tools available today, either commercially or for free, are often too high level to provide corporate buyers an adequate understanding of where they are exposed to labor exploitation.

The Fund has identified four main types of tools:

  • Tools that scrape publicly-available information on the internet (government documents, social media, public reports, etc.) and produce some level of assessment, often at a country level;
  • Tools that scrape difficult-to-reach publicly-available information, and may integrate this with private company ERP information – and then utilize machine learning and artificial intelligence (AI) technology to produce analytical, actionable assessments (these include Altana Trade, in which the Fund has invested);
  • Tools that provide deep insight into supplier risk by relying on confidential company information, and high touch, manual, expert involvement to gather and produce insights on data (Verité’s Cumulus, C4ADS);
  • Hybrids of these first three categories, which includes supply chain mapping tools that use their questionnaires to provide risk assessments through supplier benchmarking.

Risk assessment tools are useful in as much as they can provide actionable information that enables corporations to deploy additional resources to validate and address risk. The most impactful tools:

  • Provide data that is deep and specific enough to provide meaningful predictions or be actionable by a corporation, and should connect risk down to the workplace level.
  • Include a “data moat” or other barrier of entry for competitors that makes the analysis generated more effective and the company’s assets unique.
  • Are consistently refreshed, and digest different types of data sources, both structured and unstructured data (SMS, voice, video, PDFs), then cleanse and scrub the data (through natural language processors) and reformat it for analysis.
  • Integrate with other tools, including worker voice, supply chain mapping, sourcing, ERP, and auditing tools, and sufficiently automate data to identify where a human should intervene in the processing and/or analyzing of information. The team that intervenes should include data scientists and subject matter experts, but the tool should have an intuitive interface without too steep of a learning curve.
  • Provide a list of recommended actions for each risk and learn from user interactions.
  • Offer a flexible data stack and dynamic database architecture.

The Fund continues to apply these questions and screens to companies in the pipeline.

Tools can be distinguished from one another by design and use characteristics. Tools that incorporate more granular and more credible information will more effectively deliver impact for their users. But ultimately the level of their success will be determined by users of these tools – multinational buyers, employers and others – as they use this new information to make decisions that disrupt business as usual and lead to improved lives and livelihoods for vulnerable and disadvantaged workers.