How To Select The Best EHS Software For Your Business In An Age Of ESG

  • Webinar
  • Environment, Health & Safety

How To Select The Best EHS Software For Your Business In An Age Of ESG

In a landscape where the ESG and EHS software landscape is converging, how can organisations and EHS professionals navigate this and ensure the most efficient and effective best fit software solution is selected for their business?

Join this complimentary webinar when our expert advisory team will outline a best-practice approach on how to navigate the selection process and create a tailored shortlist of suitable health, safety, environment, and sustainability management software solutions.

  • Learn how to save months of effort in your vendor selection shortlisting process
  • Leverage our competitive green quadrant report to align your requirements to the capabilities of the different software vendors
  • Generate a customized benchmark that helps to isolate the best fit firms for your specific business needs

On this webinar

Stuart Neumann

VP of Advisory Services

Stuart Neumann is VP of Advisory Services and leads Verdantix advisory services globally, delivering high impact projects for C-Level executives seeking help with challenges in the EHS, Climate, Sustainability and Asset Management markets. His project experience spans go to market strategy, acquisition scans, commercial due diligence, digital strategy and software selection. Stuart joined Verdantix in 2010 and prior to his career at Verdantix, Stuart was a technology consultant at Accenture.

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.