Have you ever read Moneyball: The Art of Winning an Unfair Game or watched the movie Moneyball? Both are based on the true story of how the Oakland Athletics baseball team’s general manager, Billy Beane, successfully rewrote the baseball playbook. Instead of the traditional tried and tested approach to player selection that was based on the collective wisdom of baseball insiders, Beane set out to win by introducing a new analytical approach for which he coined the name Sabermetrics. It was a true game-changer. So what do Moneyball, Sabermetrics, and energy businesses have in common? They have all needed to go through a fundamental shift in how they leverage data to make critical business decisions in order to optimize performance. Here’s why.
Outsmarting the competition
Beane’s goal was to outsmart and better compete against much wealthier Major League Baseball teams within his very limited player budget. Using Beane’s groundbreaking Sabermetrics strategy, the A’s learned that statistics like stolen bases, runs batted in, and batting averages that were typically used to gauge players were relics of an antiquated view of the game.
Rigorous statistical analyses showed that on-base and slugging percentages are better indicators of potential offensive game success. And, crucially, it was cheaper to acquire players with these qualities on the open market compared to traditional approaches. By reevaluating its player strategy, the 2002 Athletics—with an undersized $44 million payroll—were competitive against much larger market teams like the New York Yankees, who spent over $125 million on player salaries that same year. The A’s went on to finish first in the American League West with a record 103-59, winning 20 consecutive games, a modern baseball-era record that still stands today.
Playing a new, data-based energy game
Here’s the key point: the goal—to win games and, eventually, the World Series—didn’t change. But there was a fundamental change in what it took to win. Anecdotal scouting reports and subjective decision-making were replaced by real-time performance data and evidence-based decision-making. With this new playbook in hand, team managers could make smarter decisions about which players they drafted, and achieve outsized improvements in team performance relative to spend.
The energy marketplace has changed in a similarly fundamental way. The goal—running a profitable business—hasn’t changed. But the way in which success is achieved has changed tremendously. Instead of a race for land and top-line growth, it’s now about optimizing commercial performance by understanding how energy assets—like oil and gas reserves—are performing in terms of cash flow both today and in the future. Energy leadership teams that use data to quantify current production and accurately forecast future performance can make smarter decisions that result in a powerful competitive advantage much like Beane achieved by measuring and strategically acquiring the players who could best contribute to a World Series run.
Business data is much harder to get than player data
The issue for energy leadership teams is getting the right business data when they need it. Player data is public and easy to find. In contrast, critical energy business data is often trapped in silos across a patchwork of point solutions, both inside the business functions, and outside in archaic public data sources. Stitching this information together—and making sense of it—has been just about impossible. Until now.
The traditional approach to making sense of data has been to try to develop a master data management plan and attempt to bring the data together into a single, central, monolithic data warehouse with strict controls. But this approach is incredibly time-consuming, expensive, and often fails to deliver the data that the business needs. For example, it isn’t uncommon for energy businesses to have as many as 12 different source files and formats for well headers alone. The alternative is to continue to export data from the point solutions and stitch it together in Excel worksheets as best as possible. While that seems much cheaper, in theory, it has led finance and functional teams to waste hundreds, even thousands of hours trying to reconcile their numbers, combine them into cohesive analysis, and derive agreed-upon insights. At this point these businesses run the very real risk of people giving up and taking SWAGs—Sophisticated Wild-Ass Guesses. Or, even more dangerously, assuming they understand the numbers, using egregious data points to make misinformed decisions that can adversely impact the business in a big way.
Changing the game: The new way to unlock business data
Energy leadership teams need a better way to get at the right numbers, when they need them, in a way that helps them understand their particular business’s key drivers. Unearthing, analyzing and correlating data is exactly how Beane and his team came to understand that on-base and slugging percentages are the key drivers for offensive performance in baseball.
Instead of trying to bring all the data together in one place in a monolithic data warehouse, the new, smarter way to unlock this much-needed information is to use APIs to create the ‘connective data tissue’ between the different point solutions. A composite rule-set sits above the connective tissue, acting to blend the data together in the right way, and recognizing which data point to focus on based on a specific set of circumstances, delivering a rationalized view of the data. Finally, the information is made actionable by presenting key data points through a simple UI that makes it easy to understand, collaborate, and act based on the right data.
Unlocking your data means more than numbers
The core benefit of a connected architecture approach compared to a monolithic architecture is that it’s much faster, cheaper, and simpler to implement. But that’s just the start. Businesses that can truly unlock their data achieve three additional, highly valuable benefits:
- Always know their numbers. See and understand key business data—like cash flow—on demand.
- The ability to test, and retest assumptions. Quickly see and test assumptions, like market pricing, to understand how they affect the business.
- They know their core drivers. Just like Beane’s Sabermetrics, understand what the core drivers are that affect your business and see how a small input adjustment can lead to a bigger return.
Like Beane and the Oakland A’s, businesses that adopt this modern data strategy are in a much better position than their competition to truly understand their business performance, test sensitivities, and focus on the key drivers that deliver outsized returns for a similar or smaller level of investment compared to their peers.
Zeno’s Energy Operating System was built from the ground up to connect the entire business through data, surfacing key insights for smarter, faster decision-making.
Our data 101 series is specifically designed to help you better understand why data is the energy industry’s “new” oil, and how to exploit it in your business to build an outsized competitive advantage.