In 2014, a leading North American exploration and production (E&P) company, set out to make its internal supply chain a centralized driving force in managing supplier agreements and costs within the organization to enable better cost predictability. To accomplish this, the company needed access to its spend data to make smart decisions on purchasing and uncover cost-saving opportunities.
Soon after launching an internal initiative to analyze this data, the company realized the challenges involved in organizing and categorizing invoice data due to the complexity of how categories of goods and services are managed.
“We spent a ton of time doing the heavy lifting to access the right data that wasn’t value-added because it wasn’t repeatable,” said the supply chain analytics manager.
Due to the complexity of the oil and gas supply chain, this is a universal challenge for most operators. Several factors contribute to this complex problem, including:
Even with the ability to extract invoice data, conducting spend analysis in Excel takes too much time. With this lack of resources, supply chain managers often must make quick decisions with little information. The operator engaged with a company specializing in data management and analysis. They decided to categorize the pipes, valves and fittings (PVF) category, as it is the most complex category, with several individual attributes. However, the engagement was unsuccessful as the consulting company had no background in the intricacies of the oil and gas supply chain.
OpenInsights, a spend analytics software solution that normalizes disparate spend data, provides visibility into goods and services spend at a categorized/attributed level.
Because the operator already used OpenInvoice to manage its payables process, it could now leverage the breadth of knowledge contained within. This would eliminate the time-consuming and resource-intensive activities of exporting data from OpenInvoice, then passing it to costly third parties or internal groups to high-grade and analyze. In other words, the previous heavy lifting is removed.
Another critical aspect of the solution is leveraging the entirety of the Enverus product portfolio. The operator was a long-term consumer of the various upstream oil and gas analytics solutions offered by Enverus and envisioned the added value of combining Enverus oil and gas analytics with its spend data for new insights. Such examples include tying rig invoices to rig specifications and GPS locations to optimize spend and tying invoice well locations to Enverus upstream well datasets, like additive summary and North American production.
Categorization and attribution are the two integral parts of the value of OpenInsights. With nearly $200 billion of annual oil and gas spend flowing through the OpenInvoice network each year, Enverus is the only company with the unique opportunity and ability to offer this data to customers. Investing heavily in machine learning techniques, Enverus analysts categorized and attributed hundreds of millions of line items.
Before OpenInsights, operators used accounting-based approaches to attempt to answer spend-centric operational questions.
To answer these questions required incredible efforts to pull data together and parse out specific category-level spend from a dataset that contains large amounts of information not relevant to the question at hand.
With OpenInsights, a supply chain professional can simply filter to valves, labor or OCTG and instantly have all irrelevant spend removed. They can study the historical spend trends by time, by supplier or by region. What used to take weeks – and a back and forth with IT – now takes minutes, with no need for technical support.
Attribution is the second value component. In developing OpenInsights, Enverus interviewed dozens of supply chain teams and found out that unit price analysis is incredibly difficult, time-consuming and, when completed, is often of questionable accuracy and scalability. To solve this complex issue, Enverus analysts developed relevant attributes by category. Each line item is tagged with characteristics, providing the ability to run a unit price analysis.
Now supply chain teams can answer questions such as:
Each of these questions requires filterable attributes to reach the exact good or service desired
Analyses that used to take the company’s supply chain team weeks can now be done within minutes. With a better understanding of spend, a company can save money.
“We save money overall because we become more efficient. It’s not just about saving money. It’s about empowering our people to make better decisions.” said the supply chain analytics manager.
For example, production engineers can request data to help them manage suppliers, understand well cost and approve invoices. The supply chain organization can source buyers and contract specialists can quickly pull data, run analysis and report back on their findings and recommendations.
Operationally, the operator is looking at different individual parts.
For example, the company is examining various scenarios for different valve types like:
Before OpenInsights, analyzing costs between vendors and manufacturers was a particularly challenging area. It would take weeks, if not months, to gain data on this service. With the right information, the operator can work with its suppliers to create agreements that are best for both parties. OpenInsights provides insights to understand pricing in certain market environments, manage rogue spend, reduce cost leakage and improve relationships with suppliers. To demonstrate the impact of the cost savings due to reducing the time it takes to access the data, the supply chain analytics manager provides an example:
“Let’s say an analyst earns $X per month in salary. Before OpenInsights, it would typically take that analyst three to four weeks to pull data for a request, summarize the findings and provide a recommendation. The cost of that effort is essentially equal to that analyst’s monthly salary. With OpenInsights, we can perform this task in one day, reducing the cost of the analysis by essentially the monthly salary and freeing up bandwidth to perform more analysis at scale. Not to mention the opportunities for cost savings discoverable with the solution itself.”
About the solution, the supply chain analytics manager says, “The value goes well beyond dollars and cents. The value of the solution is information and knowledge of what we’ve purchase, what we’ve built, and what we paid for it – we’ve never been able to get our hands on this spend data before. This is why we are so passionate about the idea and pushed hard. We want to equip our people with knowledge so that we make better decisions.”
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