COVID-19 has been a significant disrupting factor to the global supply chain. It forced an immediate shift to digital channels, eroded relied-upon logistical strategies, and forced companies to re-think in-person interactions of every kind.

As we embark on 2021, it might be tempting to settle into the new reality, either accepting it as status quo or awaiting a return to normalcy. However, it’s clear that volatility is the new normal for the time being. While it’s tempting to focus the topic of supply-chain disruption on sourcing and logistics, there’s a peripheral challenge that’s closely related and, if neglected, could degrade financial performance, eroding the good results of the many supply-chain pivots that took place in 2020.

I’m referring to your internal pricing, cost-management and sales commercial guidance processes: the supply chain of internal data, covering how information is gathered, analyzed, disseminated, acted upon, and measured. If supply-chain resilience is defined as the ability to steel the supply chain against future disruption while quickly rebounding from past disruption, reimagining pricing and sales is akin to steeling the company’s P&L.

The costs of inefficient and ineffective processes within pricing and sales can be significant, yet are often hidden from view. A recent Global B2B Benchmark Report analyzed the aggregate cost of these sub-par practices, and learned that B2B companies lose up to 17.1% of annual margin and 31.8% of annual revenue due to these issues. It’s possible to recapture a portion of this lost margin, and anywhere from 1% to 3% in annual margin and 5% to 15% of same-customer sales can be reclaimed. Before you can embark on that path, however, you must determine where margin loss may be occurring.

Following are a few key questions about your company’s pricing and sales processes to consider, along with a look at how enterprising companies are utilizing artificial intelligence and smarter software to address those questions.

Do you have a reliable mechanism and process for passing through costs to your customers? Global markets are facing unpredictable, volatile and increasing costs, and many B2B company leaders are more closely considering the impact of that market dynamic on pricing and margins, especially as they’re faced with increasing pressure from customers to lower prices.

This leads to some very difficult questions, such as: Can I increase my prices without negatively impacting volumes? How far do I need to go? For which customers and products do I need to increase price? While smartly passing on costs to customers can lead to more profits, and at times is the only practical option, it can be taken too far, leading to losses of customers, revenue and profits.

While managing this challenge can be relatively straightforward, how can you be certain your pricing strategy is meeting objectives and delivering the desired results?

Whether the cost change is a result of current market disruption, occasional cost increases or decreases, or regular cost swings, it’s critical to know exactly how effective past strategies have been. For example, did past attempts to pass along cost increases to customers leave money on the table due to pricing that was too low, or result in lost business due to prices that were too high?

Price optimization can help you understand how effective past strategies have been, while providing an optimal, market-aligned means to inform strategy moving forward. By doing so, you can take a more nuanced approach that determines where to pass on costs, by how much, and when.

Knowing where to pass along costs is critical. As noted above, an across-the-board price change in response to cost doesn’t always make sense. Price optimization provides visibility into each customer’s sensitivity to price, enabling you to discern that a 100% cost pass-through won’t result in volume decline for low sensitivity segments of your business. Yet it may be essential that in high sensitivity segments you pass along only a fraction of the cost increases in order to maintain volume and wallet share.

A smart and effective pricing strategy should not only address the “how much” and “when” parts of the equation, but also the “where” across these discrete micro segments. Once the strategy is set, quickly disseminating the price increase across channels — to sales reps, inside sales, and e-commerce — is critical. Here, price-management software makes it easy to update pricing as costs change and cascade out to all the price modes. Price modes is a term for the many ways in which price is expressed in your business, such as list, matrix, negotiation/spot/override, and customer-specific pricing agreements. To ensure that sales reps can effectively act on the price changes that affect existing quotes or agreements, deal-management software can prompt sales reps with impacted quotes or agreements to adjust prices.

Can you measure and predict what effect price changes will have on your top and bottom lines? Companies often choose the path of least resistance when trying to take a more analytical approach to pricing decisions. A common approach usually begins with data cleansing and analytics — report-centric, hindsight analytics, to be more specific. While there may be some value in knowing where you’ve been, backward-looking analytics provide little to no value when it comes to making better decisions in the future. The other common path is to build or purchase more sophisticated Excel-based models in an attempt to make more optimal decisions.

With both approaches, we find that companies still struggle to manage the complexities of their business. As a result, employees have to apply subjective judgment and experience to make the output of the models practical.

In the case of pricing, Excel-based models can’t possibly account for the complexity in most businesses, or provide sales reps with deal-specific price guidance for each and every transaction or contract. These models typically use overly broad price segmentation, making most prices irrelevant to nearly every deal, and setting you up to drive away some deals you would like to keep and leave money on the table for others.

Additionally, the Excel-based model won’t know which outcome occurred, so the issues will continue to propagate. These models also lack the ability to dynamically update and predict how customers will respond to price changes, before you execute pricing strategies in the market. Spreadsheet approaches simply aren’t up to managing the complexity inherent in most B2B companies. As a result, employees have to apply subjective judgment and experience to make the output of the models practical.

In stark contrast, price optimization that includes robust visual analytics can not only help you measure price elasticity across micro markets within your business, but also predict the potential impact of those prices before you put them in market. This can help you ensure that you know how prices will impact your top and bottom line.

Do you have a centralized mechanism to ensure that sales reps are selling the right products at the right time across the business? In addition to the eye-opening statistics found in the benchmark report, a reactive sales process (31%) was the leading sales challenge identified by poll respondents during MindShare 2020, Zilliant’s annual customer conference. This is not an indictment of a sales team; it means the data and customer intel necessary for a proactive sales strategy don’t reach the sellers in easily executable ways in many B2B companies.

The complexity of the sales role and speed with which reps need to be able to deliver the right offer are only increasing. Executing against multiple, sometimes competing, corporate strategies was an uphill battle for even the most seasoned sales reps before a pandemic changed everything. To the degree that it was ever possible to pull this off with spreadsheets and e-mails, the game has changed.

Enterprising companies are embracing a new centralized approach that uses A.I. to generate sales growth intelligence more quickly, and bridges discrete strategies and systems to drive specific actions across the entire customer lifecycle.

Advanced data science can determine which customers have incremental revenue opportunities, and which products and quantities customers should be buying. When used in conjunction with advanced management software, the outputs of data science can be translated into direct, multi-channel actions. This includes informing sellers about what to sell, when to sell it and how to sell it. Companies are able to publish timebound customer-specific, highly personalized promotional pricing and product recommendations to e-commerce sites, as well as build ultra-targeted, personalized marketing offers and ensure that customer agreements and quotes have the most current and relevant pricing.

The concept of supply-chain resilience should consider how well commercial processes, such as pricing and sales decisions, support the hard-earned gains of broader supply-chain efficiency. Large B2B companies must be equipped with the technology to manage pricing and sales processes effectively.

Smart organizations are already working with a trusted adviser to gain a holistic view of internal data and external market projections with a scientific eye. Are you?

Barrett Thompson is general manager of commercial excellence at Zilliant.