Why Downstream Energy Needs Operational Intelligence

If one thing is certain in the downstream oil and gas industry, it is volatility. Within the last year, geopolitical conflicts, supply disruptions, and presidential mandates to secure supply while transitioning to cleaner energy have clashed with softer-than-expected demand, the fallout from sanctions on Russian energy exports, and OPEC+ decisions to take prices that were near $140/bbl tumbling to nearly half at $72bbl. Companies that can quickly access the latest insights into these shifting variables and confidently act on opportunities are the ones that are more likely to reduce risk and improve profit margins. Operational Intelligence provides this competitive edge with insights that accelerate the speed of confident decision-making.

Operational Intelligence is the next evolution in big data analytics. It delivers real-time data and analytics to improve situational awareness and support critical business decisions as conditions change. Compared to Business Intelligence, which focuses on historical data and trends analysis, Operational Intelligence integrates industry-relevant data streams to deliver timely insights at the moment they are needed. Here is why the downstream energy industry needs Operational Intelligence.


Faster insights on volatile market data

Good decisions require good data. Agile, confident decisions require insights delivered in near real time. Consider the current timeframes for information used for making oil and gas demand and volume decisions. Traditionally, this industry leveraged year-over-year and past performance data as benchmarks for predicting demand. In addition, the U.S. Energy Information Administration provides weekly refined fuel sales data reporting at the national level and every two months for state-level sales data. Imagine basing decisions on refiner demand data from a week ago when daily demand numbers often fluctuate as much as 10,000 gallons due to unpredicted influences.


This chart shows the impact of Hurricane Ian and mandatory evacuation orders by state and local governments on local demand.


The same challenges exist for fuel buyers. Prices often change multiple times a day due to supply variances, changes to supplier policies, or even the operating status of terminals. Fuel buyers and sellers relying on outdated information will be caught off guard. Those that have access to real-time insights will be able to adjust their strategies.


Contextualized data for improved situational awareness

Data without context is informative but not powerful. For example, knowing internal metrics about supply is essential — but what if that information was benchmarked and updated in real time against total market supply? The increased value of using Operational Intelligence is not only the ability to deliver real-time analytics, but also the reliance on integrated data streams that are relevant to the company and provide contextual data for improved situational awareness.

Data without context is informative but not powerful.

For example, an energy supplier aggressively reduces pricing to shed excess product, yielding a 4% increase in gasoline volumes over four days. However, contextual insights indicate that total market volume increased by 6.4% over the same period. This clearly indicates demand was greater than expected, meaning the supplier could have reduced the financial risk, possibly maintaining margins. With day-to-day visibility into actual demand, your market becomes less opaque. Instead of guessing what might work, you can make quick, confident decisions.

Daily market-level demand numbers offer insights to many players in the downstream market with the right context. Wholesalers can enhance decision-making when timing product availability for export or going in and out of storage. Operations managers can use the same data to better manage the timing and placement of products during seasonal spec changes. Some energy companies have reported that having real-time rack-rate data provided better insights into competitor positions.

Some energy companies have reported that having real-time rack-rate data provided better insights into competitor positions.

Using an Operational Intelligence platform, like Refined Fuels Demand, delivers contextual insights relevant to the downstream oil and gas industry. It integrates demand data with other data points, such as near real-time view of market conditions and transactions, down to grade and city-level demand data. This allows companies to uncover and capitalize on opportunities — not just by the day but often by the hour.


Optimizes action for real-time triggers

Downstream oil and gas buyers constantly look to identify and expand their supply options. In much the same way, sellers are seeking optimal market moments to make a move. Each end of every transaction simultaneously considers numerous factors related to supply, location, price, and product quality.

Using an online, streamlined marketplace puts the right data in the right place at the right time. Fuel sellers and suppliers can set pricing or selling triggers that automatically adjust with market fluctuations. Automatic uploads of sales orders directly into ETRM create additional time to pursue spot deals and arbitrage.

Using an online, streamlined marketplace puts the right data in the right place at the right time.

Using Operational Intelligence with integrated data feeds that can automate on pricing parameters for specific customers increases transactional velocity and reduces risk from sudden market shifts caused by factors beyond the buyer or seller’s control; e.g., a refinery shut-in or pipeline cybersecurity threat.


Enables advanced digitalization

While digital modernization is a top business goal for the downstream oil and gas industry — rivaling revenue growth according to this Forrester study — only 43% reported investing in digital infrastructure. Many companies cite not having the right skills or right tools in place to implement digital modernization.

Operational Intelligence supports digitalization with solutions that often deliver advanced insights without requiring large data science teams. This is due to the heavy technical lifting needed to generate real-time insights. For example, constantly collecting, synthesizing, and modeling numerous complex data sets requires cloud-based computing.

The amount of data analyzed requires advanced algorithms, such as machine learning. Developers must build dashboards and visualization tools so the end user can quickly access and act upon the information. These robust processes are already completed and delivered to the company through interface programs (APIs) that easily integrate with a company’s existing system or are delivered through a software platform. This means that an energy company doesn’t have to design, build, and maintain data operation hubs to advance its digitalization journey.

Operational Intelligence offers multiple advantages for downstream oil and gas companies, including better data and contextual analytics, broader market insights, and faster problem-solving. For those companies that have already integrated Operational Intelligence into their daily decision-making, they report improved analytics of market dynamics, useful insights for identifying emerging supply trends, and improved operational efficiencies.

Learn more about how Operational Intelligence can benefit the downstream oil and gas industry.