From Data to Sustainability: A Greener Future with Process Mining

Sustainability Process Mining

In today's world, the urgent need to address the climate crisis cannot be ignored. The Synthesis Report on Climate Change has highlighted the undeniable impact of human activity on the environment, leading to a collective call for sustainable practices from consumers, investors, employees and governments alike. In the face of this demand, companies are faced with the challenge of reducing their carbon footprint. One innovative approach to meeting this challenge is through Process Mining, which enables companies to navigate their way to greater environmental sustainability.

The need for change

As with any journey towards optimization, the first step is to identify the areas that need improvement. Armed with this understanding, meaningful action can be taken. Traditionally, these actions have revolved around optimizing key performance indicators (KPIs) through targeted process improvements and automation. For example, reducing cycle times through automated document approval or maximizing cash discounts through timely payment. Our approach to sustainability optimization is similar: rather than minimizing time or maximizing money, we aim to minimize greenhouse gas emissions.

A data-driven approach

The key to successful sustainability optimization is to accurately quantify emissions. Processand has developed innovative methods to objectively quantify emissions in terms of CO2 tons, following internationally recognized standards such as GLEC or DIN EN 16258. This data-driven approach ensures accuracy and credibility in assessing the environmental impact of processes, objects within those processes and activities.

To put this approach into action, Process Mining offers specific use cases tailored for sustainability:

  • Inbound Shipping Emissions
  • Outbound Shipping Emissions
  • Supplier Sustainability
  • Material Sustainability

These use cases allow companies to pinpoint inefficiencies, optimize processes, and minimize carbon footprints across their operations. By leveraging the power of data-driven insights, organizations can navigate towards a greener and more sustainable future.
 

Concrete solutions in action

Concrete success stories underline the effectiveness of this approach. In particular, Processand emerged triumphant from the Celonis Sustainability Hackathon in Munich, where we developed a decision support application for purchasers. This application uses case-specific inbound transport emissions to provide insights beyond monetary considerations. By considering emissions in addition to costs, purchasers can make informed decisions that align with sustainability goals. This ingenious solution not only addresses Scope 3 emissions reporting, but also actively contributes to reducing carbon footprints.

Beyond boundaries with third party collaboration

Processand and Celonis extends its impact by collaborating with industry players, such as:

These companies provide comprehensive databases full of detailed CO2 information that can be seamlessly integrated into existing Process Mining analyses. This synergy not only facilitates emissions reporting, but also lays the groundwork for tangible emissions reduction strategies.


The way forward

The intersection of Process Mining and sustainability provides endless possibilities. To delve deeper into this transformative alliance and gain insight into what the future holds, listen to our insightful podcast - Episode 66: Environmental Sustainability with Process Mining featuring Anton Ehret or contact us directly. We're passionate about fostering a dynamic exchange of ideas and demonstrating first-hand how Process Mining can drive your business towards a greener, more sustainable future.

In a world where every step towards sustainability matters, Processand and Celonis are leading the way by combining innovation and environmental awareness. With quantified insights, tangible solutions and unwavering commitment, we want to support you wherever we can.
 

Learn More About Process Mining.

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