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Data value extraction

Data value extraction

How oil and gas companies can use data analytics to improve performance.

  • min read


Data value extraction

This article originally appeared on CEO Forum.

Big Data and analytics may be new to some industries, but the oil and gas industry has long dealt with large quantities of data to make technical decisions. In their quest to learn what lies below the surface and how to bring it out, energy companies have, for many years, invested in seismic software, visualisation tools and other digital technologies.

Now, the rise of pervasive computing devices—affordable sensors that collect and transmit data—as well as new analytic tools and advanced storage capabilities are opening more possibilities every year. Oil producers can capture more detailed data in real time at lower costs and from previously inaccessible areas, to improve oilfield and plant performance. For example, they can pair real-time down-hole drilling data with production data of nearby wells to help adapt their drilling strategy, especially in unconventional fields.

These analytic advantages could help oil and gas companies improve production by 6% to 8%. Bain finds that these advantages are typical of those found for companies across industries. Our survey of more than 400 executives in many sectors revealed that companies with better analytics capabilities were twice as likely to be in the top quartile of financial performance in their industry, five times more likely to make decisions faster than their peers and three times more likely to execute decisions as planned.

Analytical leaders, however, are still the exception. Our survey showed that only about 4% of companies across industries have the capabilities to use advanced data analytics to deliver tangible business value. While some oil and gas companies have invested in their analytics capabilities, many struggle to get their arms around this powerful new opportunity.

We often find that senior executives understand the concepts around Big Data and advanced analytics, but their teams have difficulty defining the path to value creation and the implications for technology strategy, operating model and organisation. Too often, companies delegate the task of capturing value from better analytics to the IT department, as a technology project.

In practice, a business unit should lead the effort because it requires cross-functional ownership and participation. Some companies commit to ambitious technology transformations in search of analytic nirvana, but these transformations may feel like a 10-year march and often fail to generate enough value along the way.

Our experience shows that developing the capability to produce value from advanced data analytics is a C-level agenda item, requiring the sustained focus of the senior management team—not just the CIO or CTO. Three critical questions should form the basis of an effective advanced-data analytics strategy.

Read the full article at CEO Forum


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