Beyond Audits: Building an Early Warning System for Supply Chain Risk

When it comes to navigating the emerging social, political and regulatory landscape surrounding human rights and supply chain due diligence, audits alone have reached the limits of their usefulness. Supplementary data, tools and procedures - alongside audits - are now paramount to successful risk management.  

Chief Impact Officer for Diginex Archana Kotecha is exploring what it takes for a business to build an effective strategy to address supply chain risk in an era characterised by uncertainty. Last week Archana hosted a masterclass in conversation with Human Rights Executive, Hayley Whatarau. The discussion focused on building the foundations of an early warning system that moves beyond reactivity and identifies emerging risks before they escalate. Below are our key takeaways.  

Prevention starts with intentional data

Organisations that are successfully preventing harm tend to do these three things very well:  

• intentional data collection  

• continuous monitoring  

• clear internal escalation pathways

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Most organisations will have no shortage of ESG, human rights and supplier data, but collecting more information is not the same as collecting useful information.

It is crucial to know how the data will be used. Clarity on what data will be collected, why that data in particular, and how the information will be applied prevents inaction and waste.  

Continuous monitoring is equally important. Unlike periodic audits, ongoing worker feedback allows businesses to observe changes over time, identify pressure points as they develop and intervene in a timely manner.  

Finally, monitoring only creates value if organisations have clear internal escalation pathways across sustainability, procurement, legal and operational teams.  

Businesses with the strongest risk management protocols have all three of these points covered.  

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Worker Voice – Deployment determines success

Poor deployment creates poor data. Organisations often invest heavily in worker voice platforms but spend little time explaining why workers are being asked to participate, how their information will be used, or what protections exist against retaliation.  

Trust is an integral part of the data collection process. That means explaining confidentiality, making non-retaliation protocols explicit, using trusted local intermediaries where appropriate and, crucially, demonstrating that feedback results in action. If workers have invested time in understanding and responding to surveys, businesses should likewise invest time in communicating how their input has been used.  Closing the feedback loop is essential to maintaining the trust that businesses have worked to build and demonstrating that workers' voices are valued.  

If workers repeatedly provide information but never hear what the outcome of the data collection is, businesses shouldn't expect meaningful engagement the next time they ask. Responding to workers, even if only to explain what has been investigated or what action is being taken, is essential to building confidence in the process.

Consider third parties to support deployment. NGOs, worker representatives and local organisations often understand cultural norms, language and workplace dynamics far better than external teams. Involving them can help overcome distrust and improve both participation and data quality.

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Pay attention to patterns

Collecting continuous worker data allows organisations to distinguish isolated issues from systemic failures.  A single worker reporting illegal recruitment fees may appear to be an individual grievance. But when similar reports emerge across several factories or reveal that multiple suppliers are using the same labour broker, the issue changes completely. The problem is no longer one supplier failing to follow policy, but a recruitment system creating forced labour risks.

The same principle applies to other indicators of forced labour. Looking at them collectively enables prevention.

This is where curiosity becomes an essential capability. Businesses should be asking whether complaints are clustered around particular suppliers, concentrated in one geography, affecting one demographic group, or appearing during particular stages of production. Disaggregating data – for example by gender - can reveal barriers that would otherwise remain hidden, such as women being less likely to access grievance mechanisms.

That said, the problem isn't always the supplier.

Worker voice data can reveal problems created by the buying organisation itself.

Excessive overtime provides a good example. Viewed in isolation, overtime complaints may suggest poor management at a factory. But overlay those complaints with production schedules, purchasing data and lead times, and a different picture can emerge. Peaks in overtime often coincide with spikes in orders, compressed delivery schedules or commercial pressure placed on suppliers.

It is important to interrogate if your business practices are creating the conditions for policy violations.  

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Collaboration is key

Engaging suppliers by introducing worker voice and other data collection tools as a collaborative improvement exercise, rather than an attempt to catch anyone out, is more likely to gain supplier buy-in and better-quality information. That partnership approach becomes even more effective when accompanied by responsible purchasing practices and investment in supplier capability, recognising that resilience is built across the relationship.

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Better decisions depend on connected data

Human rights, procurement and environmental teams tend to work with different data sets. Without a holistic view, organisations often end up addressing symptoms rather than identifying root causes. Having conversations across functions and departments is key.  

This works on a macro-level as well. Overlaying worker feedback with broader datasets, including environmental indicators, production information and macro-level country risks, allows for the identification of issues at their root. Existing intelligence around governance, labour rights, migration patterns or weak enforcement can help businesses determine where deeper worker engagement is most needed and where emerging risks are most likely to surface.

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The future of due diligence is evidence

The regulatory landscape is moving decisively towards meaningful stakeholder engagement, continuous monitoring and evidence-based reporting. Businesses are increasingly expected not only to identify risks, but to demonstrate that their due diligence processes are effective and that remediation is delivering tangible outcomes.

That makes worker voice strategically important. It provides organisations with a direct means of validating whether interventions are working, whether grievance mechanisms are trusted, and whether public commitments are reflected in workers' lived experiences.

Perhaps the biggest mindset shift is recognising that worker voice and real-time monitoring, used well, are strategic business assets that can help organisations detect risk earlier and address it before it escalates.

In an environment where scrutiny is increasing on all fronts, the organisations best positioned to respond will be those that stop treating data as evidence and start using it as intelligence.

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