Driving oil and gas operations value through a robust data foundation strategy

The key for oil and gas companies to scaling advanced technology is developing an integrated data foundation.

In brief

• Oil and gas companies have plenty of data for scaling tech like AI, but disparate legacy systems pose hurdles to upgrades.
• Four key steps can help companies build an integrated data foundation.

Across the value chain, oil and gas companies aim to increase profitability and productivity of assets and operations via advanced technology, such as artificial intelligence (AI), cloud computing and analytics. But do they have the data foundation necessary to not only fuel proofs of concept but also unlock wide-scale impact?

It’s not that oil and gas companies don’t have enough data.

Their data hurdles are from sharing tremendous amounts of static and dynamic data across disparate legacy systems. Moreover, formatting usable data for integration into advanced technology is a significant obstacle.

This isn’t a one-time process. Since new data is continuously generated across multiple functions — operations, finance, human resources, etc. — it must be continuously managed. For example, optimizing AI models and preventing “model drift” require ongoing oversight.

Remember, your employees won’t trust new technology-driven processes or recommendations if they don’t trust the data because of its lack of quality. The old computer adage “garbage in, garbage out” has never been more accurate.

View data foundation as an asset

It may be difficult to visualize — especially in an industry where a single project can cost billions of dollars — but your company’s data is your most valuable asset when it comes to implementing technology to enhance operations.

Some companies keep this top of mind by organizing critical data streams into separate products, so that everyone involved can think of them as tangible items. This makes it easier to assign value to your data and designate responsibility for caring for it.

EY alliance partners can help companies manage their data assets through its unified data platform, which eliminates data silos, proprietary formats and closed ecosystems to give companies a single architecture for integration, storage, processing, governance, sharing, analytics and AI.

That level of performance helps companies utilize their data assets more effectively, driving innovation and decision-making.

Expand your data foundation universe

Does your organization have a process for utilizing all forms of data?

There is tremendous value in capturing exogenous data, which can strengthen your ability to make informed decisions, especially those that relate to the marketplace. It became clear during the COVID-19 pandemic — and again with the war in Ukraine — that companies with the ability to blend internal and external data were better able to manage disruption.

Other forms of data can be valuable, too. For example, semi-structured data, such as information from the Internet of Things, and unstructured data, like text, voice and images, can give your AI models a more complete picture. Integrating high-quality external data strengthens your AI models’ ability to understand patterns, make predictions and provide decision analytics.

Change the culture around data foundation

The oil and gas industry was built by risk-takers who trusted their gut to make decisions. But the future belongs to companies that rely on data- and technology-driven insights.

The companies that develop a data-centric culture — without losing the focus on humans at the center — will be successful in the years ahead. A data-driven culture is one that demands data as an enabler of decisions across the front, middle and back office.

That doesn’t mean that instincts and experience aren’t useful. But increasingly, they will be used to question data carefully so that technology-supported decisions can be made with confidence. The combination of decision analytics and human ingenuity will be a powerful value driver.

Another critical area of focus is improving data literacy among employees. In an AI-supported world, employees will need to understand how to manage, use and benefit from data.

It’s not enough to just build technology tools. People must adopt them, incorporate them into daily activities and maintain them. Employee education underpins cultural shifts, and companies that dedicate efforts to helping employees understand the benefits of technology will experience more rapid acceptance.

How to make progress now

Building a robust data foundation is critical to your company’s implementation of technology to drive business outcomes. EY teams can help you build and continually evolve your data foundation so that your technology platforms and tools have the right data, in the right format, at the right time, for the right teams.