Sustainability reporting at Pico
Sustainability reporting at Pico is about making ESG data, documentation, and reporting requirements an integrated part of a company's overall data foundation. Rather than managing sustainability in separate tools or processes, we work to anchor data in the systems and workflows that companies already use for product data, master data, and business-critical information.
For us, sustainability reporting is first and foremost a question of data, structure, and governance. When data is organised correctly, reporting becomes a natural part of daily operations rather than a recurring, manual task.
Why is sustainability reporting relevant?
The requirements for documentation and transparency are becoming increasingly extensive. Legislation, customers, investors, and partners increasingly expect insight into companies' sustainability work and the data behind it.
This means companies must be able to document:
which data is used
where data originates
how data is calculated
how results can be explained and verified
Many organisations find that relevant ESG data is spread across spreadsheets, local databases, and specialist systems. This makes reporting time-consuming and increases the risk of errors, duplication, and lack of traceability.
That is why sustainability reporting is not just about delivering a report. It is about creating a data foundation that can support documentation, decision-making, and continuous improvement.
How does Pico work with sustainability data?
Pico helps companies structure and integrate ESG data as part of their existing data models and governance setup.
This can include data at:
product level
supplier level
material type level
company and group level
The starting point is always the same: what data already exists, where does it originate, and how can it be reused across processes and reporting needs?
By linking ESG attributes and documentation to existing business data, maintenance becomes part of normal operations. At the same time, a more consistent and scalable approach to reporting is established.
Governance as a foundation
The quality of sustainability reporting depends on the quality of the data it is built on.
That is why Pico works with clear structures for ownership, responsibility, and data quality. ESG data should be managed according to the same principles as other business-critical data.
This means, among other things, that a company can document:
who owns the individual data points
which sources the data is based on
how data is validated and updated
how data is used in reporting and decision-making processes
A strong governance model makes it easier to handle both internal requirements and external enquiries, where companies are expected to be able to explain and document their data foundation.
The connection between sustainability data and AI
When ESG data is structured, documented, and accessible, it can also be used more actively in analysis and decision-making processes.
Pico works with AI solutions built on known data sources and clear business rules. This makes it possible to support sustainability work without compromising traceability or the responsible use of data.
AI can, for example, contribute to:
identifying missing or incomplete data
supporting quality control and validation
analysing connections across products, suppliers, and business areas
creating a better basis for reporting and follow-up
What value does an integrated approach create?
When sustainability reporting is built on a company's existing data and processes, the work becomes both more efficient and more robust.
Reporting requires less manual handling, data quality improves, and documentation becomes easier to maintain. At the same time, the company gains a complete overview of the data that supports reporting, compliance, and strategic decisions.
The result is not just better reporting, but a stronger foundation for working systematically with sustainability in practice.
Related areas at Pico
Sustainability reporting is closely connected to our work within PIM, data modelling, governance, integrations, and AI.
The common thread is a solid data foundation, where information can be maintained in one place, reused across processes, and applied with confidence. This creates better conditions for operations, documentation, and long-term development.