Decarbonization and environmental protection

The first stage involves creating transparency. To do this, the relevant emission categories for your company are determined. It is important to identify the areas and processes that, on one hand, contribute significantly to business success and, on the other hand, cause substantial CO₂e emissions. This can range from production, fleet management, and energy supply to transportation and business travel. To quantify these emissions, we rely on existing data sources, such as internal data on energy consumption, waste volumes, and external data such as emission factors and transport miles from service providers. In cases of missing data, we assist you in measuring or estimating the emissions using alternative approaches. We assess how you can use AI to accelerate data collection and preparation in your organization. For example, AI can automatically extract data from invoices, energy certificates, or other documents and support the calculation of your Corporate Carbon Footprint (CCF).

The supply chain’s share of Scope 3 emissions varies depending on the industry. The biggest challenge in this area is to create complete transparency about the company’s current Scope 3 emissions, as suppliers are often unable to provide these values. We therefore recommend a pragmatic hot-spot analysis, which uses emission factors to estimate the most important sources of emissions and then validates and enriches them step by step with reliable figures. The aim here is not to achieve perfect values immediately, but to start with a solid basis and increase the accuracy of the values over time. In this way, targeted emission reduction measures can be started quickly. By using artificial intelligence, you can also strengthen collaboration with suppliers and partners by simplifying data entry and exchange and identifying data gaps at an early stage.

Further challenges are:

• Necessary investments in technology, artifical intelligence and infrastructure as well as employee know-how
• Compliance with increasing or expanding environmental regulations & standards, e.g. with regard to reporting
• Need for continuous innovation to implement or find environmentally friendly practices
• Need for efficient collaboration with suppliers, partners, etc. to fully decarbonize the supply chain

Following the assessment of the climate balance, the second stage involves the reduction of CO₂e emissions. The transparency created allows for the identification of emission hotspots, which are the areas and processes where the most emissions are generated. Specific measures for emission reduction are then developed for these areas, such as switching to renewable energy sources, improving energy efficiency, and optimizing transport routes.

In evaluating these measures, their ecological and economic impacts are considered, as well as their feasibility within the company. AI can support scenario analysis and the forecasting of emission reductions. With the help of AI-driven models, different scenarios can be analyzed to define a reduction pathway with concrete targets and a clear timeline. Continuous internal validation of this reduction path ensures that the set goals are met, and adjustments are made if necessary. We also offer support for external validation, for example, through the Science-Based Targets initiative, which checks whether the emission reductions meet the demands of the Paris Agreement to limit global warming to well below 1.5°C.

To successfully implement the reduction path and ensure continuous transparency, the final step of transformation requires the long-term integration of sustainability into the company’s strategy and culture. This initially involves the implementation of a governance structure in the form of organizational and structural adjustments to anchor the reduction goals in all areas and levels of the company.

Transparent reporting aids in the monitoring and communication of progress along the reduction path. The transformation is accompanied by change management, which involves informing employees about planned changes, addressing potential concerns, raising awareness of the importance of sustainability, and imparting the necessary knowledge. For a long-term, successful reduction of CO₂e emissions within the company, emissions data collection should be increasingly automated.

By applying valantic’s strategy and utilizing external technologies and software solutions, the collection of emission data can be automated, optimized, and delivered in real time. In addition to monitoring, the data can be used to perform simulations and create forecasts, making it easier to compare different courses of action and their ecological and economic impacts. These results can then be used for operationalization by incorporating sustainability metrics into procurement processes and sales and operations planning (S&OP). Only by doing this can emissions be considered an essential factor in company decision-making alongside time, cost, and quality.