Fortive is strengthening its environmental, social and governance governance by embedding AI-driven ESG intelligence into core enterprise processes, moving beyond periodic assessments toward a more continuous, data-led approach. By adopting the platform developed by Datamaran, Fortive is standardising how ESG risks, regulatory change and stakeholder expectations are identified and managed across its global portfolio.

The shift reflects growing pressure on diversified industrial groups to treat ESG not as a reporting exercise, but as an integrated element of enterprise risk management and governance.

From Manual Materiality to Scalable Governance

Fortive first began formal materiality assessments in 2018. At the time, these exercises were largely manual and centrally managed, offering a useful baseline but limited ability to capture dynamic risk signals or broad stakeholder input across its expanding group of operating companies. As regulatory requirements intensified and ESG expectations diversified across markets, the company recognised the limits of one-off assessments.

The challenge was not only compliance, but consistency. With multiple inventor-led brands operating across industrial and healthcare technologies, Fortive needed a governance model that could scale while remaining auditable and decision-useful.

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Embedding Real-Time ESG Intelligence

The introduction of Datamaran’s ESG intelligence platform marked a structural change. Rather than relying on static datasets, Fortive now draws on real-time monitoring of ESG issues, regulatory developments and peer activity. This allows sustainability, legal and risk teams to work from a shared evidence base when assessing emerging risks and prioritising action.

Materiality analysis is now supported by AI-driven insights that enable structured stakeholder engagement at scale. Outputs are fed directly into Fortive’s annual enterprise risk assessment, ensuring that ESG considerations influence legal oversight, compliance planning and strategic decision-making, rather than sitting in parallel sustainability workflows.

Linking ESG to Enterprise Risk Management

A key outcome of the platform’s adoption has been tighter integration between sustainability and core governance functions. Legal and compliance teams use Datamaran to track and benchmark ESG-related risks across jurisdictions, while risk management teams embed materiality outputs into broader enterprise risk frameworks.

This integration reflects a broader shift in corporate ESG practice, where climate, workforce safety, governance and regulatory risks are increasingly assessed alongside financial and operational exposures.

Fortive’s sustainability leadership has emphasised that automation has freed teams to focus less on process administration and more on interpreting insights and shaping strategic responses.

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Efficiency Gains and Disclosure Quality

The move to a standardised, technology-enabled approach has delivered measurable efficiency gains. Fortive reports that the time required to complete materiality assessment projects has been reduced by more than 40 percent, while the quality and depth of analysis has improved.

Cross-functional input has become more systematic, strengthening insight into issues such as workplace safety, long-term performance risks and regulatory exposure. Real-time tracking of global ESG developments has also improved the company’s ability to respond to regulatory change without relying on periodic, resource-intensive reviews.

A Model for ESG Governance at Scale

Fortive’s experience highlights how large, diversified companies are rethinking ESG governance in response to regulatory complexity and investor scrutiny. By treating ESG intelligence as a continuous input into enterprise decision-making, rather than a reporting obligation, the company is aligning sustainability more closely with risk management and long-term value creation.

As ESG regulation becomes more granular and expectations around auditability increase, technology-led approaches such as this are likely to become a standard feature of governance models for global industrial groups.

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