Delta 8.7 Policy Guides and Data Patterns
The purpose of the Delta 8.7 Policy Guide process was to carry out a comprehensive review of evidence on policy and interventions to create Policy Guides on “what works” to achieve Target 8.7 of the UN Sustainable Development Goals in the contexts of Crisis, Justice and Markets.
Subgroups identified the range of claims captured in academic and grey literature, and they reviewed the evidentiary foundations of these claims to conduct mixed-method analyses of strengths, weaknesses and trends related to the evidence base. The database was collated by University of Nottingham, Rights Lab.
|Crisis Policy Guide||Justice Policy Guide||Markets Policy Guide|
|Rights Lab Evidence Review||Rights Lab Evidence Review||Rights Lab Evidence Review|
|Public Database of Evidence||Public Database of Evidence||Public Database of Evidence|
|CRISIS POLICY GUIDE||JUSTICE POLICY GUIDE||MARKETS POLICY GUIDE|
As part of this process, several hypotheses were developed based on the literature available. In the context of Markets, most of the focus was on supply chains of the private sector, corporate responsibility and corporate engagement in achieving Target 8.7. When analysing the literature against the hypotheses, it became clear to reviewers who work with the private sector that there were major gaps in the evidence.
Experts found that their knowledge of past and ongoing efforts to address labour exploitation within the private sector was not reflected in the research base, with an apparent lack of data in the evidence base. Patterns including lack of available data for decision-making, few studies based on quantitative data and lack of prevalence data for Target 8.7 as a whole emerged within the findings. Limited standardization in the data across different geographical locations and supply chains was also identified. Most importantly, a continuum of scarce impact data on “what works” to achieve Target 8.7 became apparent. Studies included sound hypotheses of what “could work” to realize Target 8.7 but experts recorded a significant gap regarding real-life and timely impact data to prove these hypotheses.
The data “problem”
The problem is not the availability of data but instead the accessibility of this data to the research community and public sector. Therefore, this problem of access deceptively appears as a huge gap within the existing data. Public sector and researchers scramble to use statistics and data science to “fill in the gaps” of the data, to varying success.
In lieu of insufficient publicly available prevalence data, decision-makers struggle through making tough choices on how to tackle the root causes of Target 8.7. The public sector and research communities need sound, reliable, timely and disaggregated datasets on Target 8.7 prevalence made publicly available and standardized across industries and locations.
Efforts to ensure that companies are taking effective steps against Target 8.7 within supply chains have significantly increased over the past ten years. For example, as a regular part of meeting compliance requirements, manufacturers use audit companies to uncover indicators of risk. This is done by developing different frameworks to detect, collect and process this information. Once collected, the outcome is only shared with the factory or the organization funding the audit. Thus, there is a vast repository of data that exists but is rarely analysed or used. It tends to be stored by companies and auditors only to surface if there are risks regarding Target 8.7 within the supply chain or to meet compliance demands.
Manufacturing sector auditing data tends to remain private because companies see significant risk and little reward in making it available for public use. Supply chains found to include modern slavery, forced labour, human trafficking or child labour are a source of considerable reputational risk to brands, with a resulting loss of customer loyalty and business. Brand reputation is a vast intangible asset, especially for those brands operating in an already saturated market. The fear of reputational risk is justified, with brands being subjected to negative media and public attention when violations have been found.
As a result, valuable data relating to the prevalence of labour exploitation within a specific factory unit along with the actions taken to address these issues is unavailable to those seeking an empirical foundation for understanding the relationship between markets and achievement of Target 8.7. Without access to this information, it is impossible to cross-reference findings between and among brands, or for the public sector and researchers to draw conclusions on the most effective interventions to address market-driven labour exploitation.
At present, there is a great deal of data that could contribute to our collective understanding of Target 8.7 prevalence, causes, risk indications and solutions. Most of this data is either underutilized or unavailable.
A potential solution is data anonymization. Data could then be made publicly available for analysis, and much could be learned to understand trends to predict risk that would offer transparency and accountability. There have been positive examples of the private sector releasing data for public consumption and receiving beneficial analyses made by the public in return. Experts and researchers, specializing in forms of exploitation described under Target 8.7, can provide invaluable insight to the private sector, but only if they have access to their comprehensive and holistic datasets.
Companies should be encouraged to share data so that they can become more aware of how to respond to areas of high risk of labour exploitation in supply chains which would allow them to make more informed supply chain and purchasing decisions. In return, they could see greater results for their brand reputation, as a meaningful reduction of prevalence in their supply chains would lower risk and exposure to risk.
We know that we need a multi-stakeholder approach to tackle all aspects of Target 8.7 and the private sector has a huge role to play in responding to the everyday challenges of this delicate field. The Markets Policy Guide identified some promising hypotheses, but more data would strengthen its findings and recommendations to policy actors. Moving forward, solid and transparent data partnerships between the private and public sector should be at the heart of efforts to achieve Target 8.7.
This article has been prepared by Eleanor Harry and Matthew Friedman as a contribution to Delta 8.7. As provided for in the Terms and Conditions of Use of Delta 8.7, the opinions expressed in this article are those of the authors and do not necessarily reflect those of UNU or its partners.