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Did you know that you’re likely overpaying pipeline tariffs?
For an energy company, tariff data are like the lemons in a cooks’ kitchen—to get the juice, you need to squeeze them.
As a home cooking enthusiast, I have a ready stock of lemons on hand to dress up a dish. A little juice goes a long way to brighten up a nicely seared salmon flank, perk up a salad dressing, and add depth to berries. I rely on a simple lemon corer and a strainer to express the juice minus the pulp and seeds when I need a lot, but slicing from the side of the lemon rather than to the core is best for a single quick squeeze. Rolling the lemon on the countertop or warming it in the microwave for a few seconds helps soften up the lemon for maximum impact.
Pro tip: trim off a lemon twist as you would for an adult beverage and pour a shot of espresso over it.
Tariffs are like lemons — a bit sour, tough on the outside, easy to forget, but you are well rewarded if you give them a squeeze.
Why Tariffs?
Tariffs for the use of network assets have evolved as a nifty solution to a number of economic and commercial problems associated with networks.
Managing Monopoly Effects
Physical network assets often turn into natural monopolies as they are hard to permit and costly to build in terms of time and money, particularly in the OECD. As monopolies, network assets can often lose motivation to run competitively, or can engage in anti-competitive behavior, which over time has motivated markets, via regulators, to set agreed prices for the use of these assets along with rules that serve to constrain their behavior. Network monopolies are not confined to the physical world—we can also see this play out in the digital world, particularly in the EU over Google’s dominance in search and Meta’s position in advertising.
Of course, owners of network assets wish to be fairly compensated for the use of their networks, but how exactly is fair defined? Compensation should include the costs to construct a network asset like a pipeline or a transmission line, which can take years and are heavily impacted by interest rates and commodity prices. Recoveries should also include the actual costs to ship their customers’ commodities from point A to B, which is a function of the weight of the commodity, the distance it must travel and the energy inputs required for carriage, plus a return for the investors.
Operationally, owners want their assets to be highly utilized as possible, since adding capacity is problematic, and raising the prices to use their networks gives rise to charges of predatory pricing. Pricing should reflect that ambition.
Competing for Access
The numbers of competitors wishing access to a given network asset can vary seasonally for certain commodities. In the case of gas, demand is higher in winter than in summer. For renewables, access to a transmission network varies daily with the amount of sunshine and wind conditions. Without a set pricing structure, each competitor will bid for access to clear their inventory, which means high pricing volatility, deeper pockets prevailing, and large firms dominating access. Small businesses can be priced out of the network, unable to match the pricing power of large firms.
Dealing with Commercial Uncertainty
Absent agreed pricing and terms structures, markets that are dependent on monopolies lack commercial certainty. Owners, shippers, and customers all prefer the commercial certainty that comes from predictable pricing, volumes, and returns. Transacting is faster, simpler and cleaner. Budgets and forecasts are more reliable. Ultimate consumers such as home owners and businesses value the predictability of their energy costs.
Tariff structures and agreements, supervised by a regulator and set with an agreed process, correct for these issues and are now fundamental to the running of network assets, such as power lines, oil and gas pipelines, water systems, rail access, and in some locations, telecommunications. Market participants, business systems and solutions have themselves evolved reflective of the stable and predictable environment within which commodity movements on networks exist.
But that certainty can also breed complacency. Agreed tariffs might simply be part of a formula on a contract and, being small relative to the value of the commodity being shipped, not receive much management attention. Discounts might be offered by the owner so as to motivate greater volume by shippers, but are not being actively captured. Alternative lower cost routes for moving a commodity might have been constructed, and because of conditions, have capacity at an attractive price.
There’s juice in the lemon.
Squeezing the Tariff Lemon is Harder than it Seems
Squeezing a lemon is much easier than optimizing tariffs.
There are no universal standards for tariff structures as the underlying assets on which the tariffs apply vary dramatically. Terms vary in meaning. The inputs into the structures depend on the nature of the commodity being shipped (oil varies dramatically in mass and viscosity), the distances involved, the cost of energy used to move the commodities, the rates of return required to motivate investors to invest, inflation, the cost of the asset, and other factors that can vary by jurisdiction and regulator.
Tariff data is highly fragmented and distributed to any number of regulatory and market entities. The data changes over time, at least as frequently as the tariff review cycle. Tariffs are tied to specific segments of specific assets, across vast networks that in total are in the millions of miles. Contracts are themselves complex, lengthy documents, with large numbers of variables. The volume of transactions is considerable—the US moves at least 15m barrels of oil each day, in cargo units of up to 50,000 barrels.
In the case of oil and gas pipelines, determining if your tariffs are optimal is based on what your peers are paying or offering, and in such a context that is a very challenging calculation to undertake if you don’t have the resources, the expertise, the analytics and the time. Even identifying relevant peers is tricky as you’ll need to know many details about their pipeline infrastructure, commodity mix, routing, customer segments, and ideally you’ll have a clue into their capacity and utilization. Get it wrong and you’re comparing apples and lemons.
Why Squeeze Now?
In my view, there are good reasons to go after tariff data now.
Interest rates have been elevated for many months, and are likely to be high for some time as central bankers work to bring inflation under control. Tariff rates rising. The North American economy has boomeranged from the pandemic, increasing competition for access. The energy mix is changing, and energy is the biggest variable cost for shipping commodities including oil and gas. Passing on costs to end consumers is harder now because wages are struggling to keep up with inflation. Any mechanism available to capture margin should be taken.
There’s no practical way to determine what the size of the prize is, but one company who recently put its tariff data through the wringer found several hundred thousand dollars of margin they could realize with a slight change to a single incentive rate.
How to Squeeze the Tariff Lemon
There is a repeatable process you can follow to squeeze the tariff lemon, provided you have the time, the technical expertise, and the tools.
- Identify and benchmark a relevant peer set for a specific competitive situation.
- Assemble the relevant published data from across the distributed source entities pertaining to the tariffs under review, and rationalize the data to a common set of terms and meanings.
- Select from among the huge data sets the specific and relevant set of transactions and tariffs that compare correctly to your situation.
- Model the tariff structures for a given context and determine if there are exploitable gaps between contracted tariffs, actual tariffs, optimal tariffs and peer group performance.,
- Assess if the gaps are systemic, context sensitive, or random.
- Deploy any changes to trading and commercial teams and structures so as to capture the margin.
This process is something you might only execute occasionally, making it an ideal candidate to collaborate with a specialist in these analytics. I know of only one company in that regard—Arbo specializes in tariff value capture in North America, and has assembled the tariff expertise, the data collection routines, the analytics and the models to squeeze the tariff lemon.
Conclusions
Squeezing tariff data is a triple T problem — most companies do not have the time, the tools, or the technical expertise to optimize their tariff position. Instead, the best turn to Arbo.
Artwork is by Geoffrey Cann, and cranked out on an iPad using Procreate.
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