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The data initiative aimed to integrate OT data, business data, and other siloed data sources into a single location to allow for easier access and interaction internally and externally with government agencies and other partners. With the improvements made using the software, the company was able to reduce the time to deployment by 12 to 18 months, which can change the future of data intelligence at Phillips 66.
To address business challenges effectively, data must be available, secure, and accessible. However, many companies make data available locally to the plant only and store OT data in silos behind firewalls for security. This can hinder data access and cause difficulties in solving bigger problems that could lead to larger savings.
Because data is needed to solve complex business challenges, Phillips 66 needed to move the data and break down the data silos to improve accessibility. To achieve this, Phillips 66 aimed to move the data to the cloud, but the sheer volume of data, which can reach many terabytes a day, presented a significant challenge in both storage and the ability to move the data to another location.
Because “Phillips 66 OT data is in multiple sites worldwide, located in various refineries, midstream and at different plants around the world, the company needed to break down the data silos by connecting the data, storing it in one location and accessing the data securely. Breaking down these data silos is essential for improving accessibility and making the data more meaningful in context,” according to Mr. Glenn. He emphasized that “data means nothing without context.”
To enable digital transformation, Phillips 66 recognized the need to connect and secure OT data from various refineries, midstream operations, and plant sites across the globe. However, breaking down data silos and accessing the data securely required addressing several concerns such as one data context, accessibility, security, scalability, and movement. The company handles enormous amounts of OT data, which includes storing 6,000 bits of information per second or 500 billion events per year. Moving this data to the cloud would take years without the right technology. Phillips 66 decided that the data should be located in the cloud because of its ability to handle such massive amounts of OT data.
Phillips 66 collaborated closely with its business and engineering groups to move their data to the cloud for their digital transformation journey. To obtain funding for their digital transformation, the team focused on adopting a business mindset and global enterprise rollout plan rather than to just implement projects on case-by-case data initiatives. Mr. Glenn mentioned that the enterprise approach was required to substantially increase the ROI and business value. Mr. Glenn stated, “to get the most value, we need to put the individual initiatives together and rollout across the enterprise.”
Phillips 66 needed to make the data easily accessible and available for internal use and for external use including interactions with government agencies for compliance and permits and external partners. Phillips 66 integrates with a lot of different upstream and downstream partners externally, so they wanted to have OT, Business (e.g., ERP, IT), and other data sources in a single location. This would make the data more accessible globally and easier for workers to use the self-service analytics and reporting software.
The data extraction and data ingestion from historians and other OT databases and sensors needed to be as automated as possible for storage and support to have a successful enterprise rollout, including the automation of troubleshooting of historical data. The software needed to enable the contextualization and aggregation of the data and provide tools that help with problem solving. The software is needed to accelerate the knowledge transfer from the systems and minds of engineers, data scientists, and other workers so they can make fast, data-based decisions. Phillips 66 also needed digital dashboards based on specific personas to monitor their processes. They also wanted to use advanced analytics including machine learning (ML) and artificial intelligence (AI) software on the data to help solve their problems quickly and in real time.
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Keywords: Operational Technology (OT) Data, Information Technology (IT) Data, Uptake Fusion, Azure Data Explorer (ADE), AVEVA PI System; Data Movement, Cloud, Phillips 66, ARC Advisory Group.