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There are more than 200 environmental labels active in the EU, and more than 450 active worldwide. Many believe that sustainability will be just as regulated as financial reporting in a near future, and most companies and nations have already set up precise targets for carbon emissions for the upcoming years. And what about EU’s Sustainability Initiative on Digital Product Passports in 2025? With Footprint Data Management you can manage the product’s life cycle data and the different Category Impacts included in EU’s PEF methodology such as water, carbon and/or land use.
Many types and categories of data, usually scattered in different systems, with many attributes, formats, in need of syndication, centralisation, quality assurance and compilation. Using an MDM platform for sustainability data with its standard functionality and preconfigured features makes the implementation time relative short and the team can focus on designing a data model and solution that can deliver immediate value. Footprint Data Management is not just a data-driven approach to manage and control your footprint and sustainability data, it is also a sustainable solution through its stability, flexibility, and scalability. Being in control of your footprint means being prepared for any future demands or needs as well as starting to act on lowering your impact.
The market demand for environmentally responsible companies and more sustainable commerce and products is intensifying. Working strategically with master data, including sustainability data on an MDM platform creates the data transparency necessary for an organisation to access and share the data needed to make better analysis and data driven decisions. This increase in business agility will make it easier to scale and comply to new regulations as well as report progress to owners, investors and consumers but also an opportunity to develop more circular and sustainable business models, solution and products.
With Nexer’s Footprint Data Management, we help you to include sustainability data, carbon footprint data, and your product and supplier master data in your data management strategy. This enables you to collect, centralise, calculate, analyse, measure, and share your sustainability data and numbers on a multi-domain MDM platform. Managing your footprint data means more efficient sustainability reporting, and it could even turn compliance into business opportunities.
Footprint Data management is a data driven approach to sustainability work. By automating the processes to compile as well as syndicate actual footprint data from external sources and by integrating necessary internal systems, you’ll free up operative time to harness the real strategic value of the data.
MDM platforms have built-in functionalities for data quality management and ensure that updates and changes are performed everywhere simultaneously. You need both access as well as actual data to analyse where and how you can possibly decrease the total impact.
The availability of more and higher-quality data to analyse where, and how you can decrease the total impact can ultimately create a better world.
Oatly wanted a scalable and capable platform to:
• calculate, measure and manage their products’ footprints
• utilise the same platform for PLM processes
• sustainability reporting
• show their products’ actual PCF numbers on the consumer packages
Oatly not only wanted a sustainable solution that could scale, but early on they adopted a “know your numbers to show your numbers” data management strategy.
Listen to Oatly’s testimonial by clicking the image to the left.
Together with Sustainability and Future Strategist Consultants at Kairos Future we have developed a model for helping companies go from vision to continuous process development and to deliver on their sustainability goals. Kairos Future can help you to identify your focus areas, ambition level and what to measure. When you are ready, we will quantify the data you need to collect and calculate, what your data streams and workflows look like, and identify all data sources and parties.
We do this together in a Think phase, a process analysis, to really understand what the current situation looks like and as a starting point for an implementation analysis which focuses on building the optimal data model for you as well as discovering what integrations will be needed.