For decades, executives asked “What is the value of automation?” in areas like remote tank farms and manifolds. To many, making those investments was a leap of faith, a belief in keeping up with best practice more than justifying the expenditures through an ROI calculation. Recently, similar questions have often been raised about investments in big data management and advanced analytics. The most cynical have been heard to quip that, so far, the only people who have made money with big data are consultants.
It is safe to say that the pipeline segment of the oil & gas industry is feeling greater pressure than ever before. And while the nature of tariffs and use-or-pay-based shipper contracts provide some buffering against some elements of a precarious business environment, they in no way shield the pipelines from current – and especially, future – challenges. Guaranteed returns on investment are a thing of the past. As pipeline monitoring technology advances along with increasing capabilities in data management and analytics, energy company CIOs will have a growing and critical role in pipeline security and environmental, safety, and regulatory compliance. Moreover, in their roles as stewards of the enterprise’s IT strategy, they have the responsibility to pressure test with each functional area whether its approach to the use of analytics has remained fit for purpose over the years. Here are two areas where a current examination are likely in order.
Let’s first take a look at capital investment. The rapid shifting of the sources of supply continues to alter traditional pipeline flows. The impact to pipeline companies is compounded by low commodity prices, which have resulted in reduced production from the more costly supply areas. The industry is responding by reconfiguring assets to accommodate reversals in traditional flows and constructing infrastructure to meet growing demand from LNG exports by ship, growth in pipeline gas exports to Mexico, and increased power sector consumption. Scenario analysis of investment options powered by robust North American gas system modeling is the current leading practice, but this is rapidly becoming “necessary, but not sufficient”. With more than 50 LNG export facilities either proposed or under construction in Canada and the United States, plus a large and growing pipeline gas export from the US to Mexico, actual flow patterns could vary wildly in the future depending on which assets actually get built. In the future, successful domestic gas pipeline businesses will need to advance their analytical approaches to utilize global gas models – not just regional – to fully understand the possible scenarios their proposed assets could face over their 40+ year operating lives. Not only will the models themselves be different, but the user skills and business processes in which they are utilized need to be advanced to take full advantage of their potential.
"The impact to pipeline companies is compounded by low commodity prices, which have resulted in reduced production from the more costly supply areas"
Many opportunities to improve the use of analytics exist at the operating level of a pipeline company as well. The cost of compliance is an area of increasing concern. New U.S. PHMSA regulation is forthcoming that will greatly expand the extent of pipeline environmental and safety compliance requirements. Similar regulatory policies have emerged in Canada. This has the potential to add both enormous cost and complexity to an industry that is already seeing growing public attentiveness to environmental stewardship and resistance to pipeline expansions. Our view is that while every company is clearly focused on being compliant (effectiveness), few (if any) have focused on also optimizing the cost of compliance (efficiency). One pipeline COO told us he believes most of his peers likely don’t even know the true cost of compliance.
Going forward, we see the most successful companies applying operational effectiveness techniques to reduce complexity, eliminate waste, and reduce variability of operating performance. Doing so begins with analytics – analyzing data in a cross-functional way, across business units to fully understand the current cost of compliance. Improvement can come by applying the robust set of analytical tools that are part of the Lean Six Sigma toolkit – approaches such as Cycle Time Analysis and Process Cycle Efficiency that help reveal the insights necessary to change behaviors, processes, and structures in the most productive way. Pipelines should be addressing this area with a sense of urgency as the new compliance requirements will only amplify inefficiencies of current approaches if not addressed in the immediate term.
When applied pragmatically, new analytical approaches can deliver new insights, leading to greater business value and perhaps even differentiated performance versus competitors. Done right, those advancements can even be self-funding, leaving no doubt as to whether they were good investments. They don’t need to be massively expensive or enterprise-wide, but they do need to be built into the standard business processes of the organization. But often, the organization is so busy executing in the same way it has for so many years, no one pauses to question whether there is a better mousetrap out there. Enter the pragmatic CIO.