Partner Spotlight: Interview on LCA with Robert Pell of Minviro

Minviro helps global manufacturers and resource companies measure, verify, and reduce environmental impact across complex supply chains using primary and secondary data. Their XYCLE platform delivers auditable life cycle insights that stand up to regulatory and investor scrutiny.

With deep expertise in batteries, mining, automotive, and electronics, Minviro supports some of the world’s largest enterprises in turning sustainability into a competitive advantage.

In this interview, Robert Pell shares his vision to scale high-quality sustainability analysis to drive measurable impact reduction, the limitations of black box data, and how life cycle assessment (LCA) delivery has changed.

Read on to discover where Minviro meets ecoinvent.

Introducing Robert Pell, Founder and CEO of Minviro

Robert Pell founded Minviro during his PhD to ensure that the energy transition doesn’t simply shift impacts upstream, but is instead grounded in transparent, data-driven decision-making from materials to market.

As CEO, Robert’s role is to ensure the product is scientifically rigorous and commercially relevant. He safeguards that XYCLE is built on robust LCA methodology, while also functioning inside real businesses, supporting decision-making, enabling ecodesign, strengthening governance, and meeting tightening regulatory requirements.

He leads the product vision and long-term direction of the company, defining how life cycle intelligence becomes core infrastructure for global supply chains. To achieve this, he works closely with product, engineering, and modeling teams to ensure methodological integrity. He also communicates with clients, regulators, and industry stakeholders to anticipate where market and policy pressures are heading.

1. Please describe Minviro’s core activities and offerings, including your LCA tool “XYCLE”.

Minviro provides the scientific and digital infrastructure required to operationalize LCA across complex industrial supply chains. We deliver this through three integrated solutions: consultancy, software, and data.

We started as an LCA consultancy focused on complex industrial supply chains, particularly in sectors such as battery materials, mining, chemicals, and advanced manufacturing. Through this work, we developed deep expertise in modeling raw materials and industrial production routes. That hands-on experience with enterprise clients exposed the limitations of traditional LCA tools and directly shaped the development of our software.

XYCLE is our LCA software, built by practitioners to embed LCA across organizations. It enables companies to build transparent, ISO-aligned, and regulatory-ready LCA models at scale by combining primary supplier data with high-quality secondary databases such as ecoinvent. ecoinvent data forms a structured backbone of our background modelling environment, ensuring consistency, methodological integrity, and global comparability across complex supply chains.

XYCLE is designed to support ISO-compliant modeling, product carbon footprint requirements, and evolving regulations like the EU Battery Regulation, while remaining practical for enterprise use.

2. What makes LCA such a powerful tool for understanding environmental impacts, and how have you seen the field evolve during your career?

At a high level, LCA is a structured approach to better decision-making across complex systems. It helps businesses understand the environmental consequences of choices that span multiple processes, suppliers, and regions. That ability to make informed decisions is what industry and policymakers increasingly need.

What has changed significantly is how LCA is delivered. It used to be largely one-off, static studies conducted in isolation. Today, it is moving toward live, connected ecosystems where suppliers are integrated, primary data flows directly into models, and results update dynamically. That shift enables faster, more consistent decision-making and embeds LCA in operations rather than treating it as a standalone report.

We are entering a phase where environmental impact data becomes a dynamic operating layer within organizations, shaping strategy and supply chain choices rather than merely recording them.

3. The LCA data landscape ranges from simple emission factor databases to full unit process inventories. How do you see these different sources serving different purposes? Where does ecoinvent fit in that ecosystem?

Different data sources serve different levels of decision-making.

Simple emission factor databases are useful for rapid screening, early-stage estimates, or high-level reporting. They provide speed and simplicity, which can be appropriate when the goal is directional insight.

Full unit process inventories serve a different purpose. They provide transparency, technological detail, and geographic specificity. That level of granularity is essential when modeling complex supply chains, conducting scenario analysis, or meeting regulatory requirements that demand traceability.

Within XYCLE, this is combined with proprietary datasets and primary supplier data to improve representativeness and decision relevance.

4. When your clients need to make high-stakes decisions or defend their environmental impact assessments to investors and regulators, what role does data quality play?

As sustainability claims move from voluntary reporting into regulated disclosure, the cost of weak data increases dramatically. Data quality directly affects strategy, capital allocation, and the ability to defend results to investors and regulators.

Many companies set decarbonization targets based on the data available at the time. As modeling improves—becomes more dynamic and more representative—LCA is moving from one-off reports to live, connected systems embedded in operations, and results can change accordingly. In many cases, that fluctuation reflects better science and a more accurate understanding of impacts. However, organizations often see these changes as a risk because they may affect when targets are achieved or how past decisions are perceived.

Without a clear understanding of data quality, representativeness, and methodological assumptions, decisions can be misinformed. High-quality, transparent data allows companies to explain why numbers evolve over time and ensures that strategy is based on robust evidence rather than unstable assumptions.

5. Transparency and traceability are often cited as critical in LCA. How do your clients benefit from being able to trace results back to underlying process data?

Being able to trace impacts back to the underlying process or inventory is fundamental. It allows companies to see exactly where impacts arise at a specific production step, technology, region, or supplier rather than relying on a single aggregated result.

When traceability is combined with scenario analysis and deeper interpretation, it becomes a powerful decision tool. Clients can test alternative sourcing routes, production technologies, or energy mixes and understand how those changes influence the overall footprint. That moves LCA from static reporting to informed strategy.

Black box solutions do not provide that level of insight. If you cannot see how a result was built, you cannot properly audit it, and trust is reduced. As automation increases, maintaining methodological transparency becomes even more critical. For regulatory reporting and investor scrutiny, organizations need to demonstrate how results were constructed.

In XYCLE, traceability is embedded in the architecture rather than added as a reporting feature. Every process link, background dataset, and primary supplier input remains visible and traceable within the modeling environment. Users can follow data flows through the system, review assumptions and data quality indicators, and export structured outputs that retain this traceability.

Importantly, this transparency is paired with structured access controls. Different user roles, such as model owners, contributors, and viewers, allow organizations to involve suppliers, internal teams, and stakeholders in a controlled way. Contributors can upload and verify primary data without altering model structure, while decision makers can review validated results with full traceability. This ensures both collaboration and governance.

6. XYCLE works with full unit process and LCI data rather than aggregated emission factors. What does that unlock for your users that simpler tools can’t deliver?

Working with full unit process and LCI data removes the black box element. Instead of relying on a single aggregated emission factor, users can review the underlying inventory, understand how each process contributes to impact, and customize datasets to reflect specific suppliers, technologies, geographies, or forward-looking assumptions. That level of methodological visibility is not possible with simplified, factor-based tools.

What this unlocks is increased control and stronger auditability. Companies can clearly demonstrate how results were built, document assumptions, and justify changes over time. It also allows them to plan with confidence, including testing alternative sourcing routes, energy mixes, or production pathways while maintaining a clear, defensible link between data, methodology, and outcome.

For enterprise users, this means moving from estimated averages to a supplier-specific strategy. Environmental performance becomes something they can engineer and optimize rather than approximate.

7. Many companies start with simple carbon calculators that give them a number but not much else. Can you share an example where a client needed to go deeper to trace impacts through their supply chain, and what that enabled?

Most companies start with a simple carbon calculator because it’s quick. You get a number, you can report it, and you can say you’ve measured your footprint. The problem is that the number doesn’t tell you much about what the confidence is, whether it reflects reality, or where to act.

We worked with a large original equipment manufacturer (OEM) whose footprint was dominated by supply chain impacts. On paper, they had the data covered. In reality, most of it was based on spend averages and generic emission factors. That was fine for disclosure. It wasn’t useful for decision-making.

They had hundreds of tier 1 suppliers, and the real impact wasn’t neatly confined to that level. The hotspots were further upstream, in specific metal refining routes, precursor chemistries, and energy mixes tied to certain regions. “Purchased goods and services” as a line item told them nothing about which material, which process, or which supplier relationship actually mattered.

We rebuilt the model properly. That meant disaggregating components to the process level using established LCA methodology and good background data, then prioritizing where primary supplier data would genuinely change the result. Instead of asking 500 suppliers for everything, we identified the 20–30 suppliers that were driving most of the impact.

That changed the conversation internally. Procurement could identify which suppliers were structurally higher carbon. Engineering could see where design changes would reduce impact. Sustainability could move from broad Scope 3 targets to specific reduction pathways grounded in actual production routes.

It wasn’t about producing a more sophisticated footprint for the sake of it. It was about operationalizing supplier data. Once you can trace impact through the value chain with sufficient scientific depth, you can prioritize properly and engage suppliers on concrete targets rather than abstract ones.

8. Looking at how your most sophisticated clients use XYCLE, what becomes possible when teams move beyond surface-level sustainability metrics?

When teams move beyond headline metrics, sustainability stops being retrospective and becomes strategic. The most advanced organizations use XYCLE to model entire product portfolios at once, running mass bill of materials (BOM) LCAs in seconds to see where real risks and opportunities lie. They connect suppliers directly into the ecosystem, extending traceability beyond tier 1 and addressing hotspots that may sit two or three tiers upstream.

Most importantly, they use LCA before decisions are locked in. Procurement, engineering, and sustainability teams test sourcing routes, production pathways, and future scenarios dynamically, understanding trade-offs before capital is committed or contracts are signed. At that point, environmental impact becomes something you design for and not something you report on after the fact.

Environmental performance will increasingly be treated with the same rigor as cost, quality, and engineering specifications. Organizations that embed it into decision systems now are not only improving compliance, but they are building a structural competitive advantage.

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