IBM Acquires Envizi to Help Organizations Accelerate Sustainability Initiatives and Achieve Environmental Goals

ARMONK, N.Y., Jan. 11, 2022 /PRNewswire/ -- IBM (NYSE: IBM) today announced it has acquired Envizi, a leading data and analytics software provider for environmental performance management. This acquisition builds on IBM's growing investments in AI-powered software, including IBM Maximo asset management solutions, IBM Sterling supply chain solutions and IBM Environmental Intelligence Suite, to help organizations create more resilient and sustainable operations and supply chains. This acquisition closed on January 11, 2022. Financial details were not disclosed.

IBM today announced it has acquired Envizi, a leading data and analytics software provider for environmental performance management.

IBM is already using Envizi to help streamline tracking and reporting of its progress against the company's own goals in renewable electricity procurement and greenhouse gas (GHG) emissions reduction.

Companies are under mounting pressure from regulators, investors, and consumers to progress toward more sustainable and socially responsible business operations – and to demonstrate these measures in a robust and verifiable way. In fact, corporate social responsibility and environmental sustainability risks tied as the third highest concerns for organizations, as ranked by large corporations in a 2021 Forrester report.¹ However, the various types of data companies need to understand and report on sustainability initiatives remains highly fragmented and difficult for all relevant parties to access.

Envizi's software automates the collection and consolidation of more than 500 data types and supports major sustainability reporting frameworks. Its user-friendly and easily customized dashboards enable companies to analyze, manage and report on environmental goals, identify efficiency opportunities and assess sustainability risk. Envizi's solutions help streamline the management of these tasks as part of broader Environmental, Social and Governance (ESG) reporting initiatives, while also providing users with valuable sustainability insights to inform business strategy.

By using Envizi with IBM's broader AI-powered software, companies will now be able to automate the feedback generated between their corporate environmental initiatives and the operational endpoints being used in daily business operations – a crucial step in making sustainability efforts more scalable. For instance, Envizi will integrate with:

• IBM Maximo asset management solutions, which help companies extend the life of their critical assets, reduce environmental impact by providing intelligent asset management, monitoring, predictive maintenance and reliability in a single platform.
• IBM Sterling supply chain solutions, which help companies gain supply chain visibility, cut waste by right-sizing inventory, reduce the carbon footprint of shipment and logistics, and ensure responsible sourcing with blockchain-based technology for traceability.
• IBM Environmental Intelligence Suite (EIS), which helps companies increase resiliency by assessing and planning for the impact of environmental conditions on their operations, assets, and supply chains. EIS uses advanced AI and weather technology from IBM, the most accurate forecasting provider globally.²
• IBM Turbonomic and Red Hat OpenShift capabilities, which help companies automate decision making when considering where to run enterprise workloads based on optimization of performance, cost and GHG emissions.

Envizi will also help expand IBM Consulting's growing sustainability practice, which is designed to help clients accelerate progress toward their sustainability commitments.

"To drive real progress toward sustainability, companies need the ability to transform data into predictive insights that help them make more intelligent, actionable decisions every day," said Kareem Yusuf, PhD, General Manager, IBM AI Applications. "Envizi's software provides companies with a single source of truth for analyzing and understanding emissions data across the full landscape of their business operations and dramatically accelerates IBM's growing arsenal of AI technologies for helping businesses create more sustainable operations and supply chains."

Available as a SaaS solution and running in multi-cloud environments, Envizi serves leading brands such as Microsoft, Qantas, CBRE, Uber, abrdn and Celestica, and its software can be applied to activities across a variety of industries.

"As a leader and innovator in AI for business, IBM has decades of experience helping organizations around the world harness the power of their data and act on it," said David Solsky, CEO and Co-Founder, Envizi. "IBM's global reach, depth of resources and breadth of expertise will help us to scale at an unprecedented pace. As part of IBM, we feel more confident than ever that we can achieve our goal of providing clients and partners with the world class tools they need to reduce their operational impacts and optimize for the low carbon future." 

Beyond its ongoing investments in providing clients the most comprehensive AI software to help them accelerate their sustainability initiatives and support their environmental goals, IBM is also using its software to improve its own operational efficiencies, manage energy consumption and drive GHG emissions reduction.  These activities support IBM's commitment to reach net zero GHG emissions by 2030.

For more information, visit  https://www.ibm.com/sustainability/solutions.

Media Contacts:
Faye Abloeser
IBM Communications
abloeser@us.ibm.com

Cassy Lalan
IBM Communications
cllalan@us.ibm.com

¹ Forrester, "The State of Environmental Sustainability in the Fortune Global 200," January 2021

² Source: Forecast Watch, "Global and Regional Weather Forecast Accuracy Overview," issued July 2021; p.2,14

Envizi also offers user-friendly and easily customized dashboards that allow companies to analyze, manage and report on environmental goals.

Envizi’s software automates the collection and consolidation of more than 500 data types.