Sustainability isn’t a side project — it’s the new way to do business

I recently had the opportunity to participate in a masterclass on sustainability in manufacturing, hosted by the Manufacturing Leadership Council. The conversation covered topics such as digital twins, supply chain optimization and the importance of embedding sustainability into core business practices.

After the discussion, several ideas resonated with me that I’d like to share. These ideas will be helpful for any organization that wants to become more resilient and efficient.

Obligation has become opportunity

Sustainability was once seen as a check box to tick for regulators and stakeholders, but that view has shifted. It is now recognized as a significant driver of both bottom-line efficiency and top-line growth.

According to NTT DATA’s Global GenAI Report, nearly two-thirds of organizations plan to make significant investments in emerging technologies such as GenAI in 2025–26, with C-suite executives ranking sustainability among the top three motivators for these investments.

Manufacturers in particular are realizing that pragmatic sustainability, anchored in ROI and resilience, delivers tangible benefits. Reduced waste, optimized energy use and smarter supply chains are simply good business.

Embedding sustainability from the outset

A key theme in our masterclass was that sustainability can no longer sit on the sidelines. It must be woven into the very fabric of how organizations operate — much as quality and safety functions have become universal in recent decades. This means shifting from isolated “green projects” to embedding sustainability practices throughout an organization.

It also means executive leadership needs to set the tone. Without clear commitment from the top, sustainability efforts risk becoming fragmented or deprioritized.

Just as Six Sigma — a disciplined, data-driven methodology for improving processes and reducing defects — once demanded organization-wide engagement, sustainability now calls for the same level of participation through training, performance metrics and clear accountability.

Real-time data is the game changer

Perhaps the most exciting development is the role of real-time data in making sustainability actionable. Traditional annual reporting offers only a rearview mirror, but real-time insights allow us to intervene, optimize and innovate in the moment.

Take the example of digital twins. By creating a digital replica of a manufacturing facility or supply chain, organizations can monitor energy consumption, predict equipment failures and test sustainability improvements before making capital investments.

In fact, NTT DATA’s research shows that 96% of organizations agree that combining digital twins with AI can optimize physical asset performance and supply chain resilience. Real-time logistics data can streamline transportation routes, reduce carbon emissions and improve delivery efficiency while saving money.

Rethinking the value chain

During the discussion, my colleagues emphasized that sustainability is both about reducing environmental impact and about reimagining entire business processes. Procurement, product design, aftermarket services — every stage offers opportunities to reduce emissions and costs.

Consider the seemingly simple case of providing laptops and devices for employees.

Traditionally, devices were shipped multiple times, configured manually and replaced outright when they failed. By rethinking this process — for example, by automating provisioning at the factory, consolidating shipments and refurbishing rather than replacing devices — organizations can slash both costs and emissions. In addition, real-time device telemetry enables proactive device monitoring and condition-based maintenance.

It’s a small example of how operational redesign aligned with sustainability creates measurable value.

Choosing the right metrics

Metrics matter. Too often, organizations measure sustainability in broad totals, such as their overall emissions. While useful for reporting, these measures don’t incentivize smarter practices.

A better approach is to use intensity metrics such as emissions per unit of output, or per employee served. These metrics, which are within managers’ control, align sustainability with business growth. After all, we don’t want organizations to reduce their environmental impact only by shrinking; we want them to do so while growing.

Data quality — without perfection

Of course, data quality is a perennial challenge. Perfect datasets are rare, yet waiting for flawless numbers only delays progress. A more practical approach is to establish a baseline and measure improvements over time. This allows organizations to act today rather than wait endlessly for the “perfect” system.

As with AI adoption, sustainability requires iteration: Start with what you have, improve continuously and build trust in your data over time.

The role of AI and emerging technologies

AI adds another layer of opportunity and responsibility. On the one hand, AI itself consumes significant energy, raising concerns about its carbon footprint. On the other hand, it can drive sustainability by enabling predictive maintenance, optimizing supply chains and monitoring compliance with regulations such as Europe’s new deforestation rules.

Notably, according to NTT DATA’s GenAI report, 94% of organizations are already implementing energy-efficient data management practices to reduce storage and processing needs, and 91% now require new AI vendors to meet sustainability standards.

AI also enhances tools like carbon calculators by turning raw data into actionable insights. The combination of AI and human expertise enables organizations to model scenarios, test strategies and anticipate risks far more effectively than with traditional methods.

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Moving forward: Practical steps

So, what does this mean for leaders looking to advance sustainability in their organizations?

1. Make it core, not peripheral: Treat sustainability like quality or safety, integrated across the organization.
2. Invest in real-time data: Use digital twins, IoT and advanced analytics to act on insights as they happen.
3. Focus on intensity metrics: Incentivize smarter practices in addition to lower totals.
4. Balance progress with pragmatism: Don’t wait for perfect data; start today and improve over time.
5. Leverage AI responsibly: Use AI both to reduce your footprint and to amplify your decision-making.

The time to act is now

The masterclass was a reminder that sustainability is both an innovation challenge and a value opportunity. Organizations that embrace sustainability as part of their DNA will future-proof their operations and create a lasting competitive advantage.

As we move into an AI-driven economy, sustainability is increasingly defining agility, resilience, trust and growth. Those that recognize this shift and act now will lead the way.

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