Why DSO Matters for Better Cash Flow Management-Metrics for Oilfield Services


As the oil & gas industry reels from historically low prices, standard operating procedures no longer apply. With a global pandemic and uncertainty around the ability of the global oil industry to manage supply, the industry is between a rock and a hard place. Oilfield services (OFS) is the sub-segment in the industry most sensitive to market downturns—and revenue forecast revisions and mass layoffs are the unfortunate reality. In response, some OFS companies are adjusting their strategy to respond to the downturn with the same strategy that successful operators implemented to survive the 2014 oil crash—one that is defensively opportunistic.

Lessons from the past influence the current reality lessons

Terms like consolidating acreage positions, contiguous acreage, and core vs. non-core development are strategic concepts known in the industry today but were only widely adopted by operators in 2015-2017. By focusing on cash flow, shedding non-core positions, identifying their strengths, and investing in growth in core areas, oil & gas operators evolved into more efficient and responsible organizations. Investment in technology—including automation, digitalization, and data analytics—allowed operators to make data-driven decisions. This led to cost-effective, higher-performing wells and increased process efficiency.

Some defensively opportunistic OFS companies are following suit. While success is measured differently for service companies, the guiding principle remains the same: focus on strengths, streamline operations, manage cash flow, and be aggressively opportunistic for the opportunities still available.

To implement a defensively opportunistic strategy, you need insight into certain metrics of your business. To demonstrate key performance indicators (KPIs) that can help OFS companies deploy this approach in their operations, we’ve divided this topic into two articles. In this article, we show how days sales outstanding (DSO) impacts the financial health of a supplier and can be used as a barometer for the health of current customer relationships. The second article demonstrates how detailed market data can be used to identify growth opportunities and optimize the use of business development resources.

Why DSO matters for OFS

First, it is important to streamline efforts and processes to increase efficiency. DSO is traditionally the average number of days it takes for a company to get paid after an invoice is submitted. For OFS service companies, there is often a significant lag time between service completion and invoice submission, so the effective DSO is extended even further. Shortening DSO is critical for two reasons: faster access to working capital and investor confidence.

As part of our OpenInsights initiative, we work with service companies to analyze their revenue data to provide critical insights into their processes and business. OpenInsights combines the complete range of Enverus analysis and market data to create and deliver insight on OFS companies’ revenue sources, market trends, and operational efficiencies to help drive growth and get paid faster. By incorporating data variance arising from geographical and operational differences with time-to-payment analyses for a DSO perspective, we get a view of inefficiencies and opportunities and can recommend best practices to tackle them.

To understand why this metric has significant impact on a service company’s performance and stability, it helps to understand the components of a company’s DSO. OpenInsights allows us to look at DSO from five key components:

  1. Service Duration: The average time for service performance.
  2. Submit Duration: The average time for invoice submission after service completion.
  3. Approval Duration: The average time for buyer (typically E&P company) approval of the invoice.
  4. Payment Duration: The average time for payment of the invoice.
  5. Dispute Duration: The average time lost settling invoice disputes due to errors or pricing discrepancies

These components provide a better understanding of DSO and highlight inefficiencies in the process for remediation.

Why DSO Matters for Better Cash Flow Management-Metrics for Oilfield Services

By understanding DSO, you can uncover inefficiencies in your billing process for remediation.

The example above groups DSO information from a buyer perspective. While the overall DSO of these four buyers seems relatively similar, the differences in the distribution of the five components impact how each of these challenges should be addressed.

Buyer A: Invoices are approved quickly, with a low number of disputes. The problem areas are the submit duration and time-to-payment. These issues can be solved by automating processes to accelerate faster ticket and invoice processing. Another option for the company could be to leverage A/R financing to negotiate payment terms and expectations and further de-risk the revenue stream.

Buyer B: The problems are with invoice approval and dispute duration. These issues can be solved with improved data reporting practices and price book or catalog implementation with the buyer.

Improving DSO saves time, increases availability of working capital, and reduces cost of capital by spending less money on inefficient efforts. OpenInsights helps suppliers establish best practices that fit the needs of their businesses.

Correlating revenue generated with DSO

While DSO segmentation can drive the strategy to streamline business processes and save money, correlating DSO to revenue generated is crucial to properly adjusting your strategy. The chart below brings DSO and revenue information together. Each datapoint on the chart represents a buyer for the service company. The data points in this example are sized by dispute duration. The chart has been split into quadrants that show the following use cases:

  • Use Case 1: Quickly identify ideal/preferred customer list. Customers in green have high revenue and low DSO. Use this knowledge during contract and preferred pricing negotiations.
  • Use Case 2: Review problematic customers. Customers in red have low revenue and high DSO. This list should be a high priority for review. If a tier one operator is in this list, identify opportunities to grow your business and streamline the DSO process. A cost-benefit analysis should be conducted for other customers.
  • Use Case 3: Identify growth opportunities with other two segments.
    • Companies in blue have high DSO and high revenue. These customers provide a lot of business, so focus on streamlining processes and identify inefficiencies to provide more value.
    • Companies marked in orange have low DSO and low revenue. They don’t generate a lot of business but are also not inefficient or costly on the processing side. Additional datasets discussed below can be brought in to identify growth opportunities.
Why DSO Matters for Better Cash Flow Management-Metrics for Oilfield Services

Correlating DSO to revenue generated is crucial to properly adjusting your strategy.

Looking into detailed revenue information can add a lot of value and start generating cost savings and market share growth opportunities for the business. OpenInsights has enabled growth and cost savings initiatives for service companies by streamlining and identifying hidden opportunities.

Read Article Two to learn about the next steps of this analysis—bringing in critical OFS KPIs and datasets from across the Enverus data ecosystem and blending it all together for a one-stop answer.

Learn more about OpenInsights for Suppliers at https://www.enverus.com/products/openinsights-for-suppliers/ or email us at [email protected].

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Akash Sharma
Sr. Analyst & Consultant, Analytics & Product (OFS). Akash works with multiple teams across the Enverus Product organization, providing subject matter expertise on the energy industry for various product innovation and consulting efforts. His expertise lies in unconventional shale reservoirs focusing on reservoir engineering, reserves estimation, production analysis, data-driven modeling, and cross-platform analytics. He has worked on advocacy for data-driven decision making and implementing transformational changes across the energy value chain. Before joining Enverus, he worked as a researcher at the University of Houston, developing workflows for improved EUR estimation using deterministic and probabilistic methodologies and providing valuable inputs to energy investment groups and technical advisory groups. He has been published multiple times with SPE and AAPG in the past and presented at multiple industry and academic conferences. Akash holds an M.S. in Petroleum Engineering from the University of Houston and a B.E. in Petroleum Engineering from the UPES, India.