This article first appeared on Industrial Supply.
As COVID-19 economic pressures dominate the economic and political discussion, the U.S. government discussed potential plans to delay the collection of payments of some import tariffs for 90 days.i The executive order for a 90-day grace period on paying tariffs (not signed at the time of this article being written) would reportedly not include goods from China, such as imported steel and aluminum. While providing some temporary financial relief, a potential pause on tariffs means companies would still be liable for the tariff payments later.
Whether now or in the future, reacting to shifts in trade policy, particularly when those shifts are volatile due to trade wars or other unexpected global events, is not a zero-sum game. Often, the losers in these scenarios will either be the companies who must decide between their market share or profit margin, and the end-use customers who ultimately absorb the cost impact.
While many businesses are impacted by tariffs in some form or fashion, for industrial B2B companies whose supply chains, go-to-market structures, and pricing models are especially complex, reacting to swings in trade and tariff policies can be cumbersome and costly. The traditional approach of updating prices reflects a system not designed to react to the significant variation in cost environments and market conditions. The use of multiple spreadsheets involving numerous stakeholders can take two to three months, making it difficult to be nimble in an environment where tariff negotiations are in flux or markets are dynamically reacting to trade policy changes.
Further, the administrative burden of keeping up with monthly changes to tariff exclusions, filling out mounds of paperwork, and avoiding potentially steep penalties for underpayment or nonpayment can bring an unforeseen curveball. From a financial perspective, tariff considerations must also be incorporated into inventory decisions, cost analyses and pricing model updates.
However, industrial B2B companies need not be without a plan. By leveraging the latest in software tools and data science, including artificial intelligence (AI), to identify and quickly adjust prices in real-time, industrial companies can effectively mitigate the downsides of tariff uncertainties and position themselves to maintain acceptable profit margins and protect market share in any tariff scenario, while also remaining compliant with audit requirements.
The Current Tariff Environment and the Impact on the Industrial Sector
The past five years have shown a significant shift in international trade policy between the U.S. and foreign countries.
In 2015, China’s State Council unveiled its Made in China 2025 plan, a ten-year mission to “replace foreign technologies, products, and services with Chinese technologies, products, and services in the China market through any means possible so as to enable Chinese companies to dominate international markets,” according to a March 2020i report published by the Office of the United States Trade Representative (USTR). The plan specifically targeted advanced manufacturing sectors, including maritime engineering equipment, aviation and spaceflight equipment, automated machine tools, power equipment, and more.
In 2018, the U.S. Commerce Department issued a reportiii that found U.S. steel imports were nearly four times the U.S. exports. The report concluded under section 232 of the Trade Expansion Act of 1962 that these findings threatened to impair national security, which resulted in the administration imposing a 25% tariff on steel and a 10% tariff on aluminum imports.
And while other countries have also proposed their own trade policies in what is seen as retaliatory to U.S. trade actions, including India and Canada, China’s impact on the U.S. industrial sector has the potential to “create or exacerbate market distortions and create severe excess capacity.”iv In total, about 96% of U.S. merchandise imports are industrialv, meaning the ripple impacts from these policies are hugely felt in the U.S. industrial B2B industry.
Maintaining margins with respect to tariffs requires more than waiting out the storm. Rather, it requires you re-evaluate how well-equipped your business is to swiftly analyze and respond to unexpected cost swings — regardless of when they hit and from where.
Maintaining Margins Against Various Tariff Scenarios
Planning for various tariff outcomes is the industrial sector’s best defense to maintaining margins and volume in varying tariff scenarios.
High tariffs equal higher costs for B2B companies – this much is true. However, pricing discussions don’t need to start and end with imposing a broad sweeping price increase across the board, passing through nearly 100% of the costs on to customers. A more strategic and dynamic approach as to how, when, and by how much to pass on cost increases is critical to hold the line on margin and maintain market share.
For example, different customer segments within a business have varying degrees of price elasticity, meaning it can vary widely how much a price change will impact volume across one business. In terms of tariffs, this means that some customer segments where price elasticity is low can absorb a more than 100% cost pass-through. In other customer segments where the opposite is true and price elasticity is high, passing on 100% of the cost will inevitably result in lost volume.
Flexible price optimization solutions, such as those that can calculate the price elasticity of various micro segments and predict the outcomes before prices are put in market, can empower pricing teams to quickly determine the smartest cost pass-through strategies. When combined with powerful price management solutions, pricing teams can execute the necessary price changes quickly on a mass scale.
In a low or zero tariff scenario, it’s easy to enjoy the growth that comes with better margins and ignore what may be minor inefficiencies or sub-optimal account planning and pricing practices. In fact, one benchmark study we conducted found that B2B manufacturers, distributors and services companies miss out on anywhere from 7.6 to 30.8% of potential revenue due to customer churn (defected or declining purchase volume) and cross-sell (additional product categories customers should be buying but aren’t) due to sales complexity. Additionally, 1.8 to 13.4% in potential profit margin is lost annually from inconsistent pricing and wide variances among pricing practices, and misaligned market pricing practices.vi
These inefficiencies and suboptimal practices are more easily hidden during good economic conditions, when P&L statements are informed by increased volumes, profits and average selling prices (ASPs), but rear their ugly heads in a down market or when higher tariffs exacerbate the problems underneath.
Perhaps the most critical factor is how to handle the shift from a high- to low-tariff environment. The transition period, whenever it arrives, is fraught with obstacles. An end to the tariff program (whether quick and precipitous or more drawn out) presents a massive pricing problem. During the tariff period, most distributors have added a tariff line item to their quotes to pass costs on to customers. This brings transparency and is palatable, as customers expect some level of price increases during this time. Most manufacturers have been forced to fold the extra cost into their product price, again finding their customer base both reluctant and sympathetic.
But consider the unique cost and price circumstances when the tariff program finally ends. Will any customer want to pay for tariffs that no longer exist? How will customers respond to prices heavily influenced by tariff-laden, high-cost inventory? What do your competitors’ tariff-influenced inventory positions look like? The risk for substantial margin erosion and/or volume loss caused by this zombified inventory is real.
How the Right Blend of Data Science and Tools Can Maintain Margins
The complexities of scenario planning for different tariff outcomes — from the range of products impacted, to the country of origin, to the potential retaliations and changes in policy as the result of global events — compound when product types, sizes, SKU counts and customer pricing agreements are factored in. Here, the limitations of traditional pricing tools fall short, where overly general pricing leads to lower margins or lost market share.
With near surgical precision, today’s technology uses artificial intelligence and sophisticated software to optimize prices for any tariff scenario. Many of these systems include a central data repository of product data and tariff information to eliminate the guesswork of price management across different micro segments. Other technology and process improvement tools available today include deal management applications that help sales teams make more informed pricing decisions during negotiations or when renewing customer price agreements, by allowing them to quickly view price guidance and the contextual justification for that guidance. These tools give sales reps the information they need to allow room for negotiation and avoid a panic-like race to the bottom that may otherwise erode margins. In any instance where new software or technology is introduced, it’s important to partner with a trusted expert to ensure a successful implementation and continued success.
Ultimately, mitigating the risks of tariffs and other drastic market shifts requires a flexible and resilient pricing model. Whatever technology or software is involved, scenario-planning of pricing models should be performed frequently to identify possible risks and formulate effective action plans against all likely outcomes. Without these measures, industrial B2B companies may suffer unnecessary losses during high-tariff environments and find it difficult to recover during low-tariff environments.
Brooks Hamilton is vice president, services, for Zilliant. Zilliant’s solutions help B2B companies solve a wide range of pricing and sales challenges, allowing them to gain more strategic control of their business performance using an innovative blend of data science and software solutions.