From Compliance To Competitive Advantage: Emissions Management Software Trends In 2023

  • Webinar
  • Environment, Health & Safety

From Compliance To Competitive Advantage: Emissions Management Software Trends In 2023

In light of increasingly stringent emissions regulations and growing investor and reputational pressure, the scrutiny surrounding emissions data has reached unprecedented levels. To effectively address this challenge, businesses require robust commercial software for managing greenhouse gas (GHG) and air emissions. Such software plays a vital role in enabling companies to maintain strict oversight over their emissions, mitigate the risk of non-compliance, and adhere to mandatory reporting frameworks.

Nevertheless, buyers face the daunting task of navigating a highly fragmented vendor landscape within a rapidly evolving market. Based on the 2023 GHG And Air Emissions Management Software Buyer’s Guide, attendees of this webinar can expect to gain a comprehensive understanding of various emission management solution types, obtain valuable insights into key functional developments, and receive expert recommendations for identifying the most suitable solutions for their specific needs.

Key discussion points:

  • Gain insights into the current landscape of the GHG and air emissions software market
  • Discover strategies for corporations to navigate the complexities of the market more effectively
  • Explore the latest areas of innovation in the industry

On this webinar

Senior Analyst

Chris is a Senior Analyst in the Verdantix EHS practice. His current research agenda focuses on EHS software, product compliance software and digital mental health and wellbeing solutions. He was also the lead author of the most recent Verdantix EHS Software Green Quadrant benchmarking study. Chris joined Verdantix in 2020 and has previous experience at EY, where he specialized in robotic process automation (RPA). He holds an MEng in Engineering Science from the University of Oxford, with a concentration on machine learning and machine vision.