According to the MIT Center for Transportation and Logistics, digitally transforming the supply chain can lead to a 50% reduction in process costs and increase revenue by 20%. While many industries have reaped these benefits, the oil and gas industry is early in the journey of adopting digital technologies such as cloud computing, advanced analytics and artificial intelligence (AI) that can drive similar results.
Consider an e-commerce example as a proxy for today’s oil and gas supply chain. Imagine that you wanted to buy a specific golf club, a 7-iron, for instance, and you went online to order one. Multiple vendors are amenable to taking your order, but they all state that the product shipped will fall somewhere between a 3-iron and a 9-iron.
So, what would result from this lack of transparency of the actual inventory? You still might place the order but pay a discount to the true value of a 7-iron because of the risk of not getting the exact item you want. If you get an actual 7-iron, you are happy, but the seller did not get the full value of the sale. If you get a 6-iron, you are likely not thrilled, but a 6-iron is relatively close to the functionality of a 7-iron so that you can live with it. If you receive a 3-iron, you would likely initiate a custody transfer dispute and return the item. If today’s e-commerce market operated with that lack of inventory transparency and level of friction, it would be a fraction of the $9 trillion it is today.
But, for the oil and gas supply chain, this is close to today’s reality.
A data gap
The lack of transparency is rooted in two characteristics of the oil and gas industry. While there are some dominant players, the reality is that the industry comprises thousands of smaller players. They either drill oil and gas from wells (producers), transport the commodities from far-flung places via pipelines to market hubs and refineries (mid-streamers) or refine crude oil into petroleum products for use as fuels and feedstocks for making chemicals (refiners). As a result, commodities can change hands up to 11 times as they progress through the supply chain from the wellhead to the refinery.
The more significant challenge is the usability of the existing inventory data. Energy companies take numerous measurements of the quality and volume of the commodities at various points in the supply chain. However, the data has traditionally been siloed at remote production sites because of the cost of data transmission. The data is also “messy,” more so than with other industries. It usually contains errors because of fouled or uncalibrated sensors that result from measurements taken with sophisticated scientific equipment far from scientists. Lastly, while it may be technically possible to measure some inventory properties, it may not be practical. Either the equipment is too expensive to deploy widely or is not feasible because of the lack of qualified field personnel to maintain the equipment. The result is gaps in inventory data.
In a nutshell, no system of record for the inventory of this complex supply chain exists that is complete, accurate and auditable.
A universal data layer for the industry
To modernize the management of the oil and gas supply chain, companies can leverage technologies and approaches that have transformed other industries. For example, most warehouses and distribution centers continuously transmit the latest inventory data to a central repository. Similarly, oil and gas companies can now leverage high-speed 5G broadband to inexpensively connect remote facilities that previously would have had to depend on expensive, slow satellite data connections. In addition, data can now be consolidated into a single repository in the cloud for easier access. The first step to monetizing it.
But, the unique challenges to oil and gas inventory data require four specific steps to make the data useful. First, organizations should collect data directly from native data sources that include unstructured data in paper formats, spreadsheets, databases and data formats from Supervisory Control and Data Acquisition (SCADA) systems. Forcing energy companies to do the data engineering to convert their bespoke data into a standardized format introduces a significant friction point. Second, they should validate the data to address incorrect sensor reading or manual entry errors. Third, the data likely needs to be augmented to address gaps. Users also add third-party data like market pricing added to enable the discovery of additional insights. Lastly, the data structure needs to be auditable so external parties such as customers, partners, investors and regulatory bodies can trust it.
To achieve these four steps, energy companies need to combine data engineering, data science and physical sciences expertise to address the unique challenges to oil and gas inventory data.
The output of these four steps is a universal data layer that can serve as a single source of truth for the various business functions to develop the highest priority insights and recommended actions.
A more efficient supply chain
A complete, accurate and auditable data repository of a company’s commodities inventory can yield operations’ commercial and environmental benefits.
Commercial teams within energy companies can now market the full value of their products’ attributes and transact transparently and efficiently. Producers that leverage analytics to identify idea buyers for their crude oil and natural gas composition can receive higher prices. Based on market demand, buyers can now dynamically mix raw commodities to produce blends that yield the highest margins.
Operations teams can improve the efficiency and effectiveness of the processing and transporting of commodities to fulfill transactions. With greater clarity on the inventory volumes and attributes, facilities can run at higher throughputs and produce higher yields consistently. In addition, off-specification products, a traditional source of hidden margin loss, can now be rejected before a company takes custody.
Lastly, energy companies also can reduce their environmental impact during the production, transportation and processing of oil and gas. By understanding the source and location of “product loss” in the form of greenhouse gas emissions (e.g., methane and carbon dioxide) along the supply chain, companies can mitigate those fugitive emissions. The demand for “green” energy commodities is growing, so energy companies can capture new revenue for responsibly sourced products.
As they navigate the energy transition, oil and gas companies need to be more operationally and environmentally efficient. The energy industry has the opportunity to adopt modern, yet proven, digital technologies and techniques that can bring greater visibility to its supply chain and unlock new sources of financial and environmental, social, governance (ESG) value.
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