Most Americans who hear the phrase “Hail Mary” (outside of church) think of football. It brings to mind a long pass in the last seconds of the game that scores a victory for the team who would otherwise have lost.
In June, the Vatican had its own pep talk for “Team Earth” with oil and gas executives: quit drilling for fossil fuels that cause harm to the environment and impact the world’s poorest. At the event, the Pope emphasized his interest in the renewables strategy, much like a “Hail Mary” for humanity.
Several major oil companies, including BP PLC and Total SA, have already been at work, shifting investments into renewables. As seen globally, when it comes to renewables, wind and solar investments were almost double those of new nuclear, coal, gas and fuel-oil power plants.
However, experts are quick to point out that while renewables represent the path of least obstacles, the desired outcome is not yet proven.
It may be why other oil companies, like Exxon Mobil, have taken a different strategy. With the intent to do its part in addressing climate change, Exxon has committed to reducing its methane emissions 15% by 2020. It plans to do this by investing in research and new technologies to mitigate the negatives of fossil fuels, while also publicly promoting a U.S. carbon tax.
“While it can be attractive to make big bets in renewables right now, it’s still an uncertain market with a lot of volatility. There’s a lot of risk of making bad bets,” said Bob Sullivan, managing director of consulting firm AlixPartners.
Prescriptive Analytics as QB1
Oil and gas — straddling the goals of meeting operational efficiencies and determining the best long-term strategic win — may find its QB1 in prescriptive analytics technology.
At a tactical level, every play in oil and gas is a blitz. Today’s rally in Brent crude is tomorrow’s flag for OPEC to ease cuts, citing constraints with Venezuela, Iran, and Angola.
In the search for a game plan that will deliver immediate results, analytics as a technology is tiered like a football team:
- Third string: Descriptive and diagnostics analytics tell “what happened” and “why something happened.”
- Second string: Predictive analytics discloses “what might happen given a certain situation.”
- First string: Prescriptive analytics provides the best path forward given the realities and allowing for optimized business objectives.
For example, revitalizing inactive wells, which make up about two-thirds of producing oil wells, could represent an economical way to supply energy demand while minimizing environmental concerns. Prescriptive analytics takes scenarios like these and provides a clear plan that accomplishes multiple objectives. While predictive is great in telling you, for example, when to repair your equipment (i.e., predictive maintenance), it won’t tell you whether it’s even worth it to repair the well, what operations to use in repairing it, what the financial impact would be, and so forth. Prescriptive, on the other hand, can. Further, it assists with things like:
- reducing logistics costs, inventory, and manpower costs
- identifying business unit optimization across the enterprise
- providing holistic opportunities, otherwise fumbled with independent P&L’s
As CGI Director Chris McMananam said in a Q&A with us, “Prescriptive analytics is what we were waiting for to actually be able to make decisions with confidence in this complex market.”
With the renewables strategy, prescriptive analytics outlines investment decisions integrated with the company’s current portfolio; it can also assess the impacts of acquisitions and make fast recommendations on repurposing assets. With the right form of prescriptive analytics, you can literally map out hundreds or thousands of scenarios in no time, all within whatever constraints and objectives you might define, and see the exact financial impact of each scenario.
The demand for energy is a long season with teams looking for wins. When it comes to playing operations with financials, there is only one technology platform that can quarterback complexities like the oil and gas challenges…and that is prescriptive analytics.