Deep Dive: 7th Edition of The Chocolate Scorecard | #PSC 201

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Episode 201 Overview

In this episode: a deep dive into the 7th edition (2026) of the Be Slavery Free (Australia) Chocolate Scorecard.

Chocolate Scorecard

Chocolate Scorecard is coordinated by Be Slavery Free, with universities, consultants and civil society groups engaging in transforming the chocolate industry.

TL;DR Historical Context

First published in 2020, the Chocolate Scorecard is an attempt by civil society actors to report on the efforts of companies involved in chocolate and cocoa – traders, processors, manufacturers (large and small), and retailers – with respect to several “key sustainability” and “ethical” metrics.

“Mighty Earth, Be Slavery Free, and Green America surveyed the world’s biggest chocolate companies to find out! … This guide breaks down company commitments and policies. It does not assess effectiveness or implementation.”  

In this episode, I will focus a critical, skeptical lens on the claims being made in this and prior editions.

Issue: Framing.

• The choice of categories assumes and projects a particular theory of change.
• Question: Does this theory, when implemented in this way, result in meaningful change?

Issue: $$. There is NO reporting on BSF funding.

• There is a complete lack of visibility regarding the cost of producing the Scorecard and the people and entities footing the bill.

Issue: Why is there so little visibility about the members of the various teams?

• NO current reporting on institutional affiliations. Why not? (Interestingly, this information was published in the 2022 Scorecard.)

Issue: There is NO analysis of impact.

• The 2020 report specifically declares there is no intent to assess the effectiveness or implementation of the policy positions the Scorecard reports on.
• Does the Scorecard motivate changes in consumer behavior?

Issue: Clear lack of traceable history

• The Scorecard represents the category structure as being consistent from the 3rd edition to the 7th. This is not the case.
• Changes in the scoring categories must be reflected in changes in the methodology, and there is no obvious way to retrieve the methodology from anything other than the current year. (For example, weights for category scoring in the 2023 edition, but the categories have changed since then, and there does not appear to be a public update to the weighting system.)
• The detailed results for the 2024 and 2025 Scorecards are not retrievable, as the pages from 2024 forward are rendered using JavaScript.

TL;DR Concluding Question

Is it unreasonable to demand that BSF be transparent and traceable in their reporting? What can we reasonably infer from the lack of transparency that is plainly evident in what is reported, and how it is presented? Does the Chocolate Scorecard – ultimately – serve to greenwash greenwashing?

Other Coverage

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Updated: Grading the 2022 Easter Chocolate Scorecard

Part of my responses to “ethical chocolate ‘white’ lists” – what careful observation can tell us.

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Chocolate Scorecard 2022

Chocolate Scorecard 2022

The Team

What’s missing from the following table?

There are the same data quality issues (that is, the lack of data) with the NGO and other partners.

Examining the Methodology

The methodology formalizes a huge amount of work.

Despite that fact, it is still just an NGO‑designed rating system with substantial self-reported subjectivity baked in. The structure is clear enough for advocacy and company engagement, yet too loose and opaque to treat as a robust, externally verifiable benchmark of “who is sustainable.”

1. Sample and participation: Naming and shaming
   Non‑participants are simply classified as “Not willing to be assessed; indicates a lack of transparency”. That is a normative judgment about motives, not a statement of fact about their performance or data quality.
2. Data source: entirely participant company self‑reporting.
   There is no independent data collection at the farmer, cooperative, or national system level, and no explicit use of third‑party datasets.
3. Question design: mixing genuine impact indicators with policy theater.
   Because the Insights page then interprets these scores as evidence of substantive leadership or laggard status, you get a tilt toward companies that are fluent in ESG signaling.
4. Scoring architecture: expert‑driven, but still quite subjective.
   • No published scoring rubric; you cannot see, for example, how much more credit a company gets for 80% vs 40% CLMRS coverage, or what exactly differentiates a 6/10 from an 8/10 wildcard answer.
   • Wildcard questions are 20% of each category; every major category has a free‑form “showcase” question worth one-fifth of the section score.
   • Category weights and aggregation are opaque; it is not clear whether, say, Child Labor and Living Income carry equal weight in the overall grade.
5. Category structure: normative choices baked into the framing.
   The choice of categories itself embeds a particular theory of change. The architecture centers on what buyer companies can commit to and measure from their desks: certifications, programs, traceability, premiums, and policies. 
6. Retailer vs manufacturer scoring: uneven data expectations.
   Retailers are not held to the same granularity of impact data. Instead, they are judged more on whether they demand things from suppliers and on the extent of program coverage.
7. Farmer Health: important, but quietly sidelined.
   Health is treated as important enough to ask about, but not important enough to influence the public grade. It also means there is no public accountability for health claims, since no score is visible and the underlying data are not provided.

• Methodology Pros and Cons Shortlist:
  • PRO: Comparing how a participating group of big buyers has improved (or not) in specific operational areas like traceability, CLMRS coverage, and deforestation monitoring.
  • PRO: Identifying which companies are engaging and answering questions.
  • PRO: Seeing where corporate ESG energy is concentrated: which topics are over‑supplied with policies and pilots, and which are chronically thin.
  •• CON: Treating color scores as precise indicators of real‑world impact on forests, incomes, or child labor, especially across years.
  •• CON: Inferring anything concrete about non‑participants; the label “not willing to be assessed” is not an empirical finding.
  •• CON: Serious econometric or policy analysis without going back to primary sources like NORC, satellite deforestation studies, and national pricing data.

Summary

The methodology is a carefully‑constructed mirror of how the coordinators believe companies should behave and communicate, evaluated through industry experts’ judgment on self‑reported data. It is not a neutral instrument for measuring the cocoa sector as a whole.

Examining the Scorecards

Exploring some Insights

Summary

The Insights page does reflect progress on traceability and deforestation‑free sourcing. (However, this is a direct result of the EUDR forcing companies’ hands.) It also underscores, rightly, that living income and child labor remain stubborn failures after decades of promises. At the same time, it:
• Treats non‑participation in the Scorecard as a moral failure rather than a limitation of the Scorecard’s own sample and method.
• Puts most of the responsibility on brands and traders and far less on governments, marketing boards, and macro‑level trade and fiscal structures.
• Blurs the line between “what we can say with high confidence from sector‑wide evidence” and “what our particular scoring system wants to reward.”

Exploring the State of Cocoa

Future Episodes

Episode Hashtags

#cocoa #cacao #cacau
#chocolate #chocolat #craftchocolate
#PodSaveChoc #PSC
#LaVidaCocoa #TheChocolateLife

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