Serena Grace, head of sustainability, Owen Mumford, and Marina Dumont, sector lead medical & pharma, PRé Sustainability (SimaPro B.V.), explore how real-time life cycle assessment can close the gap between the operational data manufacturers already hold and the environmental insight they need.
Until now, the pharmaceutical industry has largely managed sustainability as a series of parallel projects introduced
Owen Mumford
over time: a waste reduction initiative here, a carbon footprinting exercise there. Each of these activities generates valuable environmental data, yet they are rarely designed to operate as part of a cohesive system, and the insight they produce therefore remains fragmented.
Mandatory climate disclosure, tightening procurement criteria, and investor-driven ESG scrutiny are now converging on the industry, heightening the need to rethink how sustainability data is managed not just at a department level, but company-wide. The question facing manufacturers is no longer whether to act, but how to develop the organisational infrastructure they need to act effectively.
For most manufacturers, that architecture is still in development. Not because the ambition is absent (indeed, many organisations are investing substantial resources into sustainability reporting), but because the underlying data systems were never designed to support environmental decision-making at the speed and granularity current pressures demand. Real-time life cycle assessment (LCA) is the framework that could change this, operationalising a proven methodology to make sustainability insights available when and where they are needed most.
“Data-rich, insight-poor”
It is no secret that pharmaceutical manufacturing generates extraordinary volumes of sustainability-related data. Supplier questionnaires, ethical sourcing assessments, energy consumption and waste tracking, Carbon Disclosure Project (CDP), Science Based Targets initiative (SBTi) or B Corp certification disclosures all capture aspects of a product’s inputs and outputs on an almost-continuous basis. In theory, everything needed to understand an organisation’s environmental performance is already there.
But in practice, this data exists in silos. Each organisational function develops its own methodologies, system boundaries, data formats and reporting cycles, resulting in multiple, disconnected ‘versions’ of sustainability performance across the organisation.
Moreover, evolving reporting requirements mean that new processes are layered onto existing ones, with no overarching rationalisation or integration. Fragmentation thus becomes structurally embedded, obstructing the effective flow of data at an organisational scale and limiting sustainability reporting to a retrospective exercise that does not fuel decision-making: the very definition of ‘data-rich, insight-poor’.
Other industries, notably the technology sector, have already made efforts to replace these multiple, conflicting data sources with a ‘single source of truth’: a unified data architecture in which critical datasets are standardised, centrally governed and immediately accessible.
While this approach requires a significant shift in how sustainability is conceptualised within organisations, there is clear evidence that data-driven operating models bring superior performance outcomes by increasing data consistency, transparency, accessibility and agility. As sustainability reporting increasingly moves from largely voluntary disclosure towards a more enforcement-driven landscape, the need for high-quality, verifiable sustainability data grows too. Fragmented, manually assembled datasets simply will not meet that bar.
A tightening landscape
Large organisations across Europe now face mandatory, externally assured climate disclosure under the EU's Corporate Sustainability Reporting Directive, which goes significantly further in scope, depth and assurance requirements than previous legislation. At the same time, the Empowering Consumers for the Green Transition (ECGT) Directive is introducing stricter requirements for substantiating product-level environmental claims, raising the evidentiary standard for sustainability communications.
Commercial pressure is moving in parallel. Environmental performance criteria are appearing in NHS procurement frameworks and being written into supplier agreements across European healthcare markets. As a result, the ability to provide verified environmental data at product level is shifting from differentiator to baseline expectation.
LCA: proven methodology, untapped potential
Life cycle assessment is increasingly recognised as the pharmaceutical industry’s ‘gold standard’ for environmental evaluation, and for good reason. Governed by internationally recognised standards (ISO 14040 and ISO 14044), LCA provides a comprehensive, scientifically robust framework that captures the product carbon footprint across the full life cycle, from raw material sourcing to manufacturing, distribution, use and disposal.
Industry-specific initiatives like PAS 2090 go further still, defining system boundaries, data quality requirements and allocation methodologies to further support standardisation. These frameworks help level the playing field across the sector, strengthening credibility and reducing the risk of misrepresented environmental claims.
The next step is to take this established methodology and connect it to real-time operational data, shifting from static point-in-time studies to models that run continuously and reflect current conditions.
Three pillars of operational LCA
Capitalising on this opportunity requires three elements working together.
The first is data infrastructure. In order to extract strategic insight from the data they already hold, organisations must first map out the data they collect, clarify ownership and accountability, identify the relevant datasets and assess how information should be presented and integrated. By replacing fragmented systems with ones that are intentionally designed at a strategic level, sustainability is reframed as core business data, rather than an ‘add-on’ reporting exercise.
For example, a manufacturer assessing a packaging change could connect supplier material data, production volumes and validated LCA assumptions within a single model. Instead of waiting for a separate study, teams could see how that change affects product carbon footprint and compare options before decisions are locked in.
The second is a rigorous LCA methodology. Models must apply consistent methodological choices, and be parameterised so that environmental outputs update automatically as operational inputs change. This approach balances scientific robustness with scalability, ensuring that LCA results are consistent and comparable, forming a solid foundation for operational and strategic decision-making.
The third is the user interface: the layer that turns expert-owned analysis into shared operational understanding. If organisations want data to drive concerted, cohesive action, employees across relevant functions need to access the information, understand what it means and see how it affects the decisions in front of them.
The future of sustainability reporting?
Owen Mumford is currently exploring how to take this model from framework to practice, with scope to involve partners who bring specialist expertise in LCA as the approach matures. Over the next few years, sustainability data will need to become as reliable, accessible and actionable as the financial or operational data that already informs strategic decisions.
The methodology is established. The operational data exists. What real-time LCA provides is the architecture to connect them. The organisations that build it first will find themselves ahead of requirements, rather than racing to keep up.