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Ocean Winds

Ocean Winds (OW) is a 50:50 joint venture created in 2019 by EDP renewables (EDPR) and ENGIE. Both companies share a vision of offshore wind playing a key role in the global energy transition and future industry growth. EDPR and ENGIE have combined all their offshore wind assets and project pipelines under OW. OW’s primary target markets are Europe, the United States, and selected Asian countries, where most industry growth is expected to occur.

As a new company, OW was looking for a solution to automate their recently established processes and rapidly build applications to support their vision.

Ocean Winds: Preparing for the Future of Energy with Low-Code Automation

Business Problem

OW needed simple, dynamic, agile tools that would allow their processes to be rapidly implemented.

To this end, OW needed a solution that could ensure quality implementation of automation logic. OW chose to partner with Appian, whose Low-Code Automation Platform was expected to improve operational excellence in process management, facilitate business decision-making across all global business units, and offer process monitoring efficiency. Appian automation would also meet OW’s need for increased implementation speed by freeing people from repetitive or patterned work, such as generating warnings, alerts, documentation, or reports.

 

Appian Solution

Appian provided an end-to-end business process hyperautomation model and low-code platform to deliver new applications and processes. OW used the Appian Low-Code Automation Platform to develop applications such as “OWorld,” a single digital environment that brings together all other automations and applications.

Appian has become more than just a process tool for OW; certain features, like the internal job site, make it an effective tool for consultation and communication. Appian also provides an improved user experience—90% of OW staff have used at least one of the applications developed by Appian. The organization has also seen 75% cost savings and a 25% reduction in the time it takes to execute digitized processes.