From plant floor to carbon footprint: How manufacturing can finally get ESG right

Most manufacturers can estimate their total energy use, but when customers ask for the carbon footprint of specific parts with defensible methodology, that's where the real challenge begins. Accurate carbon accounting at the product level requires rethinking how we measure, monitor, and report emissions. The answer isn't in corporate sustainability platforms alone. It starts on the plant floor. ei³ CEO Spencer Cramer details his approach to solving this challenge.

Sustainability isn't new to me. Long before ESG became a boardroom buzzword, I was wrestling with a fundamental tension that I suspect many engineers share: a deep love for the natural world paired with the pragmatic understanding that maintaining our quality of life requires consuming resources. We can't wish away manufacturing, but we can make it dramatically smarter.

This tension was a driving force behind my founding ei³ more than 25 years ago. Our mission from the start has been to help manufacturers reach peak efficiency: economic prosperity, environmental stewardship, and social responsibility working together rather than in opposition. Today, that mission is more relevant than ever as organizations face mounting pressure to quantify and report their environmental impact.

The reporting challenge nobody warned you about

Here's the uncomfortable truth facing manufacturers today: your customers increasingly want to know the carbon footprint of what they're buying from you. And not in vague, hand-wavy terms. They want real numbers, defensible data, and traceable methodology.

To understand why this has become so complex, we need to talk about how emissions are categorized. The Greenhouse Gas Protocol divides emissions into three scopes:

Scope 1 covers direct emissions from sources you own or control: the natural gas burned in your furnaces, the diesel in your forklifts, the refrigerants leaking from your HVAC systems.

Scope 2 addresses indirect emissions from the energy you purchase. When you buy electricity from the grid, you're inheriting the emissions from however that electricity was generated. Your Scope 2 footprint depends heavily on where you're located and who supplies your power.

Scope 3 encompasses everything else in your value chain, both upstream (your suppliers) and downstream (your customers' use of your products).

Here's where it gets interesting for manufacturers: what's your Scope 1 is your customer's Scope 3. Consider a Tier 2 automotive parts supplier. When Ford or Toyota asks about the carbon footprint of the components they're purchasing, they're asking about Scope 3 emissions. But for the parts manufacturer, that same data represents their Scope 1 operational footprint. The same numbers serve different purposes depending on where you sit in the supply chain.

Why this is harder than it looks

You might think calculating manufacturing emissions is straightforward: measure your energy consumption, apply some conversion factors, and you're done. In practice, it's far more nuanced.

Modern manufacturing involves multiple energy sources with different emission profiles:

• Electricity
• Natural gas
• Compressed air
• Steam
• Chilled water

A single production line might draw from several of these simultaneously. And the emissions associated with your purchased electricity vary dramatically based on your geographic location and even the time of day, as grid mix shifts between baseload and peak generation.

Then there's allocation. How do you attribute energy consumption to individual products when a single machine produces multiple SKUs? What about scrap and rework? These aren't just accounting questions. They're fundamental to whether your emissions data means anything.

Bringing clarity to the plant floor

This is precisely the challenge our SUSTAIN application was designed to address. The approach starts with a simple premise: you can't manage what you can't measure, and you can't measure what you're not monitoring.

The first step is ensuring every machine has the ability to sense and communicate its key energy inputs. For some equipment, this capability already exists in the control system. For others, we add sensors:

• Electricity meters
• Gas flow monitors
• Compressed air consumption trackers

The goal is comprehensive visibility into where energy is actually going.

Next, we connect these sensors through IoT monitoring, capturing not just energy consumption but also production data: units produced, cycle times, and critically, the distinction between good parts and scrap.

Knowing that a machine consumed 500 kWh yesterday is far less useful than knowing it consumed 2.3 kWh per good part produced on Job #4472.

The computation of actual CO2 impact is where significant complexity lies. ei³ maintains a comprehensive database of emissions factors for energy suppliers and energy types around the world. When you're running a plant in Germany, the carbon intensity of your grid electricity is quite different from a plant in Texas or one in Quebec. Time-of-use variations, renewable energy certificates, and supplier-specific data all factor into the calculations. We handle this complexity so that plant engineers don't have to become emissions accounting experts.

The output is emissions data tied to actual production: CO2 per good part, typically aggregated by job or production run. This is the data that feeds corporate sustainability reporting, responds to customer inquiries about Scope 3 emissions, and supports the detailed environmental product declarations that major brands increasingly require from their supply chains.

From monitoring to enterprise reporting

Data only matters if it reaches the people who need it. SUSTAIN provides visualization tools for plant engineers to confirm that monitoring is functioning correctly and to understand the energy efficiency of their equipment at a granular level. But the greater value often lies in the data pipelines that feed enterprise systems.

Through API integrations, emissions data flows into:

• Corporate sustainability platforms
• ERP systems
• Specialized ESG reporting tools

This isn't about creating another dashboard for someone to check. It's about embedding emissions data into the business processes where decisions get made.

An unexpected benefit: Predictive insight

Here's something we didn't fully anticipate when we began this work: energy consumption patterns turn out to be remarkably useful for detecting equipment problems before they cause failures.

Machines that aren't running to specification often consume energy differently:

• A motor drawing more current as bearings wear
• A heating system working harder to compensate for degraded insulation
• A hydraulic pump cycling more frequently as seals begin to leak

By establishing baseline energy-per-part metrics and continuously comparing actual performance, we can detect anomalies that signal developing problems.

This capability connects directly to our LIFECYCLE application, which focuses on predictive maintenance and remaining useful life estimation. The energy data captured for sustainability purposes becomes another input for keeping equipment running reliably. It's a virtuous cycle: the same infrastructure that supports environmental responsibility also drives operational excellence.

Why this matters now

The regulatory environment around sustainability disclosure is tightening globally. The EU's Corporate Sustainability Reporting Directive, California's climate disclosure laws, and SEC proposed rules are creating new compliance obligations. But beyond compliance, there's a competitive dimension: manufacturers who can credibly document their environmental performance will have advantages in markets where sustainability matters to buyers.

For us at ei³, seeing organizations deploy SUSTAIN alongside our other applications brings genuine satisfaction. We're helping manufacturers optimize production while minimizing environmental impact, exactly the balance I was reaching for when we started this company. The triple bottom line isn't just a nice concept. With the right data infrastructure, it's achievable.