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Industry veterans share secrets to scaling digitalization efforts

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The energy industry is at an inflection point, and the race is on to reduce emissions and meet net-zero goals by 2050. To succeed, energy companies need technology that helps them build and scale solutions quickly. Two industry veterans explain why Industrial DataOps can help.

Susan Peterson Sturm has led energy companies through transformation for the past two decades. She knows firsthand how to unlock the power of data and drive real change and create value in the industry.

“The pace of change can be daunting,” Peterson Sturm said. “The only way we can move forward is through the extreme empowerment of our colleagues so that they can leverage work processes, technology, and operational models that allow them to meet new challenges head-on.”

Johann Pleininger, the OMV executive with 43 years of experience in the energy industry, is on a similar mission. The Austrian integrated oil and gas company with more than 25,000 employees worldwide is on a mission to digitalize its operations until all data is one click away.

“By sharing data and using OMV’s own data in a smart way, we’ll make better decisions for the company and its people,” Pleininger said. 02_JohanPhoto: Johann Pleininger, Deputy CEO and Executive Board Member, OMV.

This is a gigantic task for Pleininger and OMV. The company has more than 400,000 sensors that can stream data to engineers’ desks, and more than one petabyte of data available that it needs to take into account when developing and operating fields around the world.

More and more industrial companies are recognizing the value of industrial data, liberated and contextualized by a new generation of software solutions. What’s required now, and at scale, are the know-how, the technology, and the tools to do the actual transformation work. One absolutely essential tool is the rapidly growing discipline of industrial data operations or Industrial DataOps.

Why Industrial DataOps?

Industrial companies need software that solves the data problem—collecting and connecting all the data they generate, contextualizing it with other existing data from IT, OT, and ET systems, and making the data available and understandable to all data consumers, from control room operators and field workers to data scientists and solution engineers.

“It can’t be one special group of people doing the transformation,” Peterson Sturm said. “We need to blow the top off and make it accessible to everyone. Mass adoption.”02_SusanPhoto: Susan Peterson Sturm, IIOT Transformation Leader and Cognite partner

This is where Industrial DataOps comes in. This new software category aims for predictable data delivery and change management, using technology to automate, orchestrate, and operationalize data use and value dynamically.

With the right Industrial DataOps solution, business users can browse all available data and use it in their visualization software of choice. Thanks to data management and data quality tooling, users can easily set up data lineage and quality monitoring. This ensures the visualization is actionable at any given time and ripe for operational decision-making. 

For enterprises, Industrial DataOps means becoming more data-driven without the need for complex IT infrastructure projects and time-consuming, expensive training programs.

Scaling with Industrial DataOps

“What the oil and gas industry needs now is fast value creation and for leaders to be willing to invest when we see the value,” Pleininger said.

One area where OMV is investing—and seeing results—is Industrial DataOps. 

Here’s one example: In 2020, OMV used Cognite Data Fusion®, the leading Industrial DataOps platform, to co-develop and deploy BestDay, an interactive platform for data-driven production optimization. 

BestDay uses data-driven AI modeling to calculate what its name suggests: the best possible production day. Instead of physical simulations, BestDay automatically evaluates a field’s production performance based on the best historical production days, custom boundary conditions, and production criteria to produce a maximum capacity algorithm that updates daily.

OMV tested BestDay at the oldest oil giant of Austria: the Matzen oil field. While it can be difficult to wring production gains from fields that have been in operation for decades, BestDay was shown to increase production at the field by an estimated 0.3-0.5% per year above the current production profile and save OMV an estimated 10,000 hours per year in engineering time by eliminating manual calculations. 

Powered by Industrial DataOps, BestDay’s full potential is estimated to drive production efficiency gains of up to 1.5%, meaning millions of dollars a year in value generated for the average production hub.

After the successful deployment in Austria, OMV plans to use the scaling capabilities of Cognite Data Fusion® to expand the use of BestDay across its international portfolio, which includes upstream operations in Eastern Europe, the Middle East, and Africa, the North Sea, Russia, and the Asia-Pacific region. This global rollout will multiply the value generated by the application many times over.

“Cognite enables a new way of working at OMV and in the entire upstream industry,” Pleininger said. “By collaborating with them, we have been able to transform the way we respond to challenges. Cognite combines its technology platform with a dynamic and innovative delivery team. This is exactly what we needed.” 

Industrial DataOps: What you can do now

“When selecting a transformation partner, it’s key to find one that has experience scaling their solutions across a company,” Peterson Sturm said. “Cognite did that for us. Secondly, it’s important to have solutions that can mature along with our internal customers, which Cognite delivers.”

Implementing and scaling Industrial DataOps solutions won’t happen overnight. It requires agreement and unity among all data stakeholders in your organization. Here are three important steps to get started:

  1. Make your data available by identifying where it is, how to get at it, and how to store it for later use.
  2. Make your data useful, freeing it from silos and making it speak “human,” so that its value can be released across operations. Contextualize it and design homes for it so that all of the minds and functions in your organization can actually understand it, use it, and innovate on top of it.
  3. Make your data valuable. Extracting maximum value depends on being able to obtain insights that inform better decisions, and enabling all business users to become solution creators. Scaling these benefits brings data value to the whole organization.

Pleininger has one piece of advice for energy companies that want to transform the way they work:

“I recommend that you remain curious and flexible, and to always strive to incorporate the latest technologies,” Pleininger said. “This constant aim for improvement will ensure that we continue to produce oil and gas safely and efficiently.”

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