Rewiring Sustainability: Why Technological and Connectedness Matter Most

By ImpactMatrix Team
Ask a sustainability consultant or a chief sustainability officer to name the dimensions/pillars of sustainable development and sustainability (SDS) performance and the answer comes back instantly: Environmental, Social, Governance. Ask the same question about an organization's technological capacity or the strength of its cross-sector partnerships, and the answer is usually a pause, followed by "that's probably covered somewhere in Governance." It isn't, not in any of the frameworks that consultants and executives report under today, and that gap is not a cosmetic omission either. It is a structural blind spot in how SDS performance is measured, and it is why ESGETC (Environmental, Social, Governance, Economic, Technological, and Connectedness) treats Technological and Connectedness as two of its six core dimensions rather than as footnotes to Governance.This post makes the narrower, more specific case for those two dimensions: why Technological capacity and Connectedness are not optional add-ons to SDS performance measurement, but structural prerequisites for it, grounded in the UN's own framing of the Sustainable Development Goals, in published literature on digital development and network theory, and in what the dominant ESG reporting standards actually do and do not measure.

The UN Already Treats Both as Core, Not Peripheral

It is best to start from the source document, because it settles an argument before it begins. The 2030 Agenda for Sustainable Development, adopted by the UN General Assembly in 2015, does not bury technology and partnerships inside other goals, it gives each its own standalone Goal. SDG 9, "Build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation," is explicitly about Technological capacity: infrastructure, industrialization, and innovation [1]. SDG 17, "Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development," is explicitly about Connectedness: partnerships between governments, the private sector, civil society, and multilateral institutions as the mechanism through which the other 16 goals actually get delivered [1]. The UN's own architecture treats technological capacity and partnership density as enabling conditions for every other goal, not as a subsection of governance or an afterthought to environmental or social performance.

Why Technological Capacity Is Not Optional

The World Bank's World Development Report 2016: Digital Dividends [2] made a finding that is easy to summarize and hard to unsee: digital technologies had spread rapidly across much of the world, but the broader development benefits, growth, opportunity, better service delivery, had lagged behind and remained unevenly distributed, precisely because countries and organizations differed enormously in the "analog complements" needed to convert digital adoption into real dividends: regulation, skills, and accountable institutions. That is a direct empirical demonstration that technological capacity is not a proxy for anything else, it is its own axis of performance, with its own gap between adoption and realized benefit.The United Nations took the same view at the global-policy level four years later. The Secretary-General's Roadmap for Digital Cooperation set an explicit target of achieving universal, safe, and affordable internet connectivity by 2030, alongside dedicated action areas for digital public goods, digital inclusion, and digital capacity-building [3]. A roadmap built around closing specific, measurable digital gaps is only necessary if those gaps are real and currently invisible to existing measurement systems, which is exactly the position SDS reporting is in today. Manuel Castells' 1996 account of the network society [4] argued that by the late twentieth century, economic and social value was increasingly organized around and produced through information networks rather than isolated production units, which is precisely why an organization's digitalization, data systems maturity, and innovation capacity now function as production infrastructure in their own right, not as a Governance footnote.And yet none of the four frameworks that dominate current SDS reporting practice, GRI, SASB, ISSB/IFRS, or TCFD, contains a dimension for it. GRI's Universal Standards, most recently revised in 2021, have no standard for technology governance or innovation capacity [5]. SASB Standards, now governed by the IFRS Foundation following its 2022 consolidation with the Value Reporting Foundation, measure technology only inside narrow, industry-specific contexts such as cybersecurity disclosures for technology-sector companies, not as a universal, cross-industry dimension [6]. IFRS S1's general sustainability-disclosure requirements, issued in 2023, apply a financial-materiality lens to risks and opportunities, not a structural measure of technological capacity [7]. IFRS S2 and the TCFD recommendations it absorbed are scoped to climate, full stop [8, 9, 10]. The gap World Bank [2] and the UN Secretary-General [3] describe at the policy level has no corresponding line item in any major organizational reporting standard.

Why Connectedness Is Not Optional

The case for Connectedness rests on a different but equally well-established body of evidence: the structure of an organization's relationships is not a soft, reputational matter, it is a measurable determinant of how information, capital, and innovation actually move. Mark Granovetter's (1973) foundational analysis of social networks [11] found that weak ties, looser connections outside an organization's immediate circle, are disproportionately responsible for the flow of new information and opportunity, precisely because they bridge otherwise disconnected clusters. Applied to organizations rather than individuals, the same logic holds: an organization's network of external partnerships determines what it can learn and access that its internal structure alone cannot provide.Innovation theory makes the same point from a different angle. Etzkowitz's (2008) triple helix model [12] describes how university, industry, and government interactions jointly produce innovation outcomes that no single sector produces alone. Carayannis and Campbell [13] extended that into a quadruple helix by adding civil society and the media, and extended it again into a quintuple helix by adding the natural environment as a fifth interacting sphere specifically because sustainable development and the knowledge economy cannot be modeled without it [14]. Across four decades of this literature, the consistent finding is that the density and quality of cross-sector partnership, not any single actor's internal capability, is what drives innovation and systemic outcomes. That is Connectedness, named and measured directly, and it is exactly the capacity SDG 17 identifies as the global partnership "means of implementation" for the other 16 goals [1].As with Technological, none of the four dominant frameworks measures it as a dimension. GRI's economic-disclosure series addresses procurement relationships, not partnership density or consortium participation [5]. SASB/ISSB captures supply-chain-management metrics in some industry-specific standards, but nothing resembles a universal measure of cross-sector collaboration. TCFD and IFRS S2 are climate-scoped and say nothing about partnership structure at all [8, 9, 10].

Enabling Dimensions, Not Parallel Ones

Here is the distinction that matters for consultants advising clients and executives setting strategy: Technological and Connectedness are not simply two more categories to tally alongside Environmental, Social, Governance, and Economic performance. They are enabling dimensions, the capacity and the network through which performance in the other four actually gets produced and scaled. An organization with strong environmental intentions but no data systems to measure emissions, or strong social commitments but no partnership network to deliver them at-scale, will underperform regardless of how its other scores look. Measuring Technological and Connectedness separately is what makes that underperformance visible instead of hidden inside a composite Governance score.

Validating the Case Through the Market

We are not asking anyone to take this argument on faith alone. We plan to validate ESGETC through an academic Delphi panel, the structured expert-consensus method Dalkey and Helmer [15] developed at RAND for exactly this class of measurement problem; but that process is intentionally slow, and we do not think organizations making reporting decisions this year should have to wait for it to be the only signal available. Karl Popper's standard for a sound empirical [16] claim is that it be falsifiable: testable against evidence, capable of failing the test. A deterministic, reproducible comparison of an organization's own measured performance against the frameworks it already reports under is exactly that kind of testable claim. It is also a direct response to a documented problem in the existing ESG measurement ecosystem: Berg, Koelbel, and Rigobon [17] found substantial divergence across major commercial ESG rating providers scoring the same companies, evidence that adding a dimension by argument alone, without a way to check it against an organization's own data, would just add a fifth opinion to an already crowded field.That is why we are inviting sustainability consultants and senior executives to run their own organization's data through ImpactMatrix, ESGETC's operationalizingplatform, and see exactly where Technological and Connectedness performance currently sits, visible for the first time, not folded into Governance. ESGETC also ships with a pricing model none of the legacy frameworks have an equivalent to: Freemium-to-Reward, where higher-capacity, paying organizations cross-subsidize free Community-tier access for lower-scoring organizations, who graduate to paid tiers as their measured performance improves.CTA: If you are a sustainability consultant or senior executive and would like to contribute to the market validation of the ESGETC framework, visit: https://app.impactmatrix.io/programs/framework-validation-cohort 

References

  1. United Nations General Assembly. (2015). Transforming our world: The 2030 Agenda for Sustainable Development (A/RES/70/1). United Nations. https://sdgs.un.org/2030agenda
  2. World Bank. (2016). World development report 2016: Digital dividends. https://www.worldbank.org/en/publication/wdr2016
  3. United Nations Secretary-General. (2020). Secretary-General's roadmap for digital cooperation (A/74/821). United Nations. https://undocs.org/A/74/821
  4. Castells, M. (1996). The rise of the network society. Blackwell Publishers.
  5. Global Reporting Initiative. (2021). GRI 1: Foundation 2021 (Universal Standards). https://www.globalreporting.org/standards/standards-development/universal-standards/
  6. IFRS Foundation. (2022, August 1). IFRS Foundation completes consolidation with Value Reporting Foundation [Press release]. https://www.ifrs.org/news-and-events/news/2022/08/ifrs-foundation-completes-consolidation-with-value-reporting-foundation/
  7. IFRS Foundation. (2023a). IFRS S1 General Requirements for Disclosure of Sustainability-related Financial Information. https://www.ifrs.org/issued-standards/ifrs-sustainability-standards-navigator/ifrs-s1-general-requirements/
  8. IFRS Foundation. (2023b). IFRS S2 Climate-related Disclosures. https://www.ifrs.org/issued-standards/ifrs-sustainability-standards-navigator/ifrs-s2-climate-related-disclosures/
  9. Task Force on Climate-related Financial Disclosures. (2017). Final report: Recommendations of the Task Force on Climate-related Financial Disclosures. Financial Stability Board. https://www.fsb-tcfd.org/
  10. Task Force on Climate-related Financial Disclosures. (2023). 2023 status report. Financial Stability Board. https://www.fsb-tcfd.org/
  11. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360–1380. https://doi.org/10.1086/225469
  12. Etzkowitz, H. (2008). The triple helix: University-industry-government innovation in action. Routledge.
  13. Carayannis, E. G., & Campbell, D. F. J. (2009). 'Mode 3' and 'Quadruple Helix': Toward a 21st century fractal innovation ecosystem. International Journal of Technology Management, 46(3/4), 201–234. https://doi.org/10.1504/IJTM.2009.023374
  14. Carayannis, E. G., Barth, T. D., & Campbell, D. F. J. (2012). The Quintuple Helix innovation model: Global warming as a challenge and driver for innovation. Journal of Innovation and Entrepreneurship, 1(1), Article 2. https://doi.org/10.1186/2192-5372-1-2
  15. Dalkey, N., & Helmer, O. (1963). An experimental application of the Delphi method to the use of experts. Management Science, 9(3), 458–467. https://doi.org/10.1287/mnsc.9.3.458
  16. Popper, K. (1959). The logic of scientific discovery. Hutchinson.
  17. Berg, F., Koelbel, J. F., & Rigobon, R. (2022). Aggregate confusion: The divergence of ESG ratings. Review of Finance, 26(6), 1315–1344. https://doi.org/10.1093/rof/rfac033