Mars Reports 98% Responsibly Sourced Cocoa Milestone in 2025 Progress Report

Mars has released its Cocoa for Generations 2025 Progress Report, stating its suppliers sourced an annual volume of cocoa under the company's Responsibly Sourced Cocoa Program equivalent to 98 percent of its 2025 cocoa volume, with that same volume also deforestation- and conversion-free after relevant cut-off dates. The report marks a milestone within Mars's 10-year, $1 billion Cocoa for Generations commitment running from 2018 to 2028.

 

Why the Gap Between 98% and Full Completion Matters for Assessing the Programme's Endpoint

 

The report specifically states 98 percent of Mars's 2025 cocoa volume was sourced under the RSC Program and was deforestation- and conversion-free, a figure representing substantial but not complete coverage of the company's total cocoa sourcing. That remaining 2 percent gap matters for understanding what this milestone actually represents: rather than claiming full, complete transformation of its entire cocoa supply chain, Mars is reporting near-complete but not total coverage, a distinction worth noting given cocoa supply chains typically involve sourcing through complex, multi-tier networks spanning numerous smallholder farmers across different countries and regions, where achieving literally 100 percent traceability and verification across every single volume unit can present genuine practical challenges even with sustained, multi-year investment.

The report doesn't specify what accounts for the remaining 2 percent specifically, whether this reflects genuinely untraceable volume, sourcing relationships still transitioning into the programme, or some other specific factor, a detail that would be useful for assessing how close Mars genuinely is to eventual full completion of this particular sourcing target.

 

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Why the Child Labour Monitoring Figure Requires Distinguishing Coverage From Elimination

 

The report states "100% of cocoa volume produced and purchased in 2025 from farmers participating in the RSC Program in West Africa had Child Labor Monitoring & Remediation Systems (CLMRS) in place." That figure specifically measures the presence of a monitoring and remediation system across participating farms, not the elimination of child labour itself, a distinction that matters considerably for accurately interpreting what this statistic actually demonstrates.

A Child Labor Monitoring and Remediation System functions by identifying instances of child labour when they occur and then working to remediate that specific situation, meaning the existence of such systems across 100 percent of participating farms indicates comprehensive monitoring infrastructure coverage, but doesn't itself indicate that child labour has been eliminated across those farms, since the entire purpose of such a monitoring system is to detect and address ongoing instances of child labour that the system's existence alone doesn't prevent from occurring in the first place. That distinction is worth maintaining precisely rather than conflating monitoring system coverage with a claim about actual child labour prevalence or elimination.

 

Why the Women for Change Savings-to-Loans Ratio Reveals How the Microfinance Mechanism Functioned

 

The report states the decade-long Women for Change programme with CARE reached 106,239 Village Savings and Loan Association members, 77 percent of whom are women, generating $26.56 million in savings and $17.68 million in loans. That specific breakdown, savings exceeding loans by a meaningful margin rather than the two figures being roughly equivalent, provides useful insight into how this particular microfinance mechanism actually functioned for participants: a VSLA model typically allows members to pool individual savings contributions, which then become available for members to borrow against, meaning the total savings figure represents cumulative deposits while the loans figure represents how much of that pooled capital was actually borrowed and utilised by members.

The savings figure exceeding total loans by roughly $9 million suggests a meaningful share of pooled savings remained available within these associations rather than being fully utilised through borrowing, which could reflect either genuine financial security building among participants who chose to save rather than borrow, or alternatively could indicate some portion of pooled capital wasn't fully deployed toward loans that could have supported additional economic activity among members, a nuance the report's stated figures don't fully resolve on their own.

 

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Why the Journey to Thrive Programme's Household Count Provides a Useful Scale Comparison Point

 

The report states the newer Journey to Thrive programme, established in late 2024, had "impacted 9,334+ cocoa farmer households by the end of 2025" in Côte d'Ivoire specifically. That figure, while representing genuine reach for a programme still in its early implementation phase, is considerably smaller in scale than the Women for Change programme's reported 106,239 VSLA members accumulated over its full decade of operation, a comparison that provides useful context for understanding Journey to Thrive's current stage of development, a newer initiative still building toward whatever eventual scale it may achieve over its own multi-year implementation period, rather than a programme that has already reached comparable maturity and reach to Women for Change's decade-long operational history.

 

Why the AI Tool Descriptions Reveal Distinct Technical Applications Within the Supply Chain

 

The report describes two specific AI-powered tools serving genuinely different functions: Cocoascan, described as helping "Latin American farmers detect potential visual indicators of three infectious diseases," and Cocoa Fresh AI, "a mobile app that helps modernize wet and dry bean supply chains from a slow, manual process." Those two tools address distinct points within the cocoa production and supply chain, Cocoascan targeting early-stage crop health and disease detection directly at the farm level, while Cocoa Fresh AI targets a later-stage supply chain logistics and processing function specifically, illustrating how AI-driven tools are being deployed across multiple distinct stages of the cocoa value chain rather than concentrated within a single application area.

 

Source: Mars