Corporate executives are inundated with so much information in the digital age that leveraging it fully has become a major challenge. This is especially the case when profitable growth opportunities veer onto a collision course with profitable growth risk, a team of energy business management experts said during a recent webinar.

“From the shale revolution to operating model changes to product demand and price volatility, these factors really have a significant impact on every one of the industry segments—upstream, midstream, downstream and oil field services,” said Glenn Babich, New York-based director in PriceWaterhouseCooper’s (PwC’s) energy advisory services.

“Given the pricing dynamics, you need to be more sophisticated, more targeted to ensure you’re making the right investments, structuring the cost models properly and making sure all your commercial activities are really drawn to the highest potential market opportunities,” he said. “Across the board, understanding and having a transparent view of the costs associated with supporting the wells, the distribution of NGLs, delivering products and pricing them to the rack, along with delivering and servicing oil-service application, are very critical.”

“In our philosophy,” Babich said, “if you can’t measure it, it’s very difficult to manage it.”

Measuring requires getting a handle on what you already have.

“We see that many companies are not making full use of the data that already exists within their organizations and they’re not getting it into the hands of decision makers to maximize the value that’s created,” said Mike Scheller, Chicago-based director for PwC’s energy advisory services and moderator for the session.

Michelle Turner, Houston-based PwC manager, offered a case study of effective analysis of midstream data. In it, two wellheads, A and B, had similar gross margins. However the company experienced an EBITDA loss with Wellhead B.

The mystery of the disappearing earnings was solved by digging deeper into the data and breaking down the process.

“Profitability modeling can ultimately provide EBITDA down to the individual wellhead level, pulling in wellhead gross margin data, flow data and breaking down or allocating costs down to the individual networking component—gathering lines, compressor stations and processing plants—and then gain visibility to profitability at various points within the network,” Turner said.

Examining the data closely revealed that compression costs were much higher at Wellhead B than at Wellhead A, shedding light on how profits were being drained.

“This visibility, in combination with a structured performance improvement process, can then support and drive more consistent data-driven decisions for operations and commercial folks in the field,” Turner said.

PwC found that its clients were typically unhappy with their existing data because the level of detail did not explain bottom line incongruities, such as why one wellhead would outperform another even though both had similar gross margins.

“Once you have that foundational data that people have confidence in, that provides the level of detail and transparency—so that you truly can understand the economics and impact of all the operational decisions that are made every second of every hour of every day—how do we use that to support decision-making processes in terms of tools that we get to look at, what is the process to set daily rack or street prices?” Babich asked.

It’s a matter of developing policies and processes from the hard numbers to guide key players in the organization who make decisions, he said. By making that information transparent to all involved, the company will ultimately gain advantages not just in its operational and strategic spheres, but on the financial side.