Wes Woolbright, MBA has over a decade of experience in pricing strategies, pricing operations, and revenue management across a variety of retailers, including Walmart (Director, Pricing Operations), Sam’s Club (Director, Pricing), BevMo! (Director, Pricing), and Safeway (National Category Director). Wes received his M.B.A. as well as dual degrees in Economics and history from Willamette University. Wes holds certifications with the Professional Pricing Society.
In Parts 1 and Part 2, Wes Woolbright and Edris Bemanian discussed the evolving landscape of e-commerce, omnichannel retail, and the impact of inflation on pricing strategies. They examined how economic conditions influence consumer loyalty, with shoppers often seeking deals across retailers during downturns. Wes shared insights from various retail models and emphasized the importance of aligning incentives and objectives to support successful technology adoption and change management within retail organizations.
Edris Bemanian: Wes, you’ve consistently been at the forefront of competitive intelligence, price optimization, and the broader ecosystem that pricing solutions impact. Pricing affects every organization, as well as the change management involved. What are a few key things that stand out when you consider the future of pricing organizations? What do you envision for the modern pricing organization of 2030?
Wes Woolbright: Hard to believe 2030 is actually only five years away. Many big changes, especially those involving technology, may take two or three years to implement, so 2030 is not far off. I think a lot of it has to do with how an organization actually values its pricing. At some of the pricing society conferences I’ve attended, mingling and networking with folks from Fortune 500 and Fortune 100 companies, I often hear that pricing hasn’t historically been a priority, especially outside retail. I think there’s an intuition behind that mindset. If a company is already successful, they might not see the need to pay much attention to pricing. They may be focused on logistics, product design, and marketing, which are often already well-optimized, so they don’t necessarily see pricing as an area to maximize further. No one consciously thinks of it that way, but subconsciously, this view can prevail.
Some companies may still be in that mindset in 2030, especially if they’re doing well without sophisticated pricing technology or a data-driven approach. For them, pricing may remain a semi-automated task on someone’s desk, without needing a dedicated pricing organization. In some cases, product teams in B2B or merchant teams in retail might “do it themselves,” though I’d consider that a less enlightened approach. Just as a CEO isn’t expected to be an expert in every function of a company, a merchant trying to master every discipline is likely stretching themselves too thin, which impacts the quality of their work.
In a B2B setting, I see sales and product functions in a similar light. So, a healthy pricing organization in 2030 would have the ability to process large volumes of data, filter out what’s relevant, and provide insights that drive effective pricing decisions. It’s about being able to adapt quickly—even week-to-week or day-to-day—to produce insights that align with a company’s success metrics.
We often hear “optimization,” but what I frequently see is maximization, where the focus is simply on a single objective. True optimization would allow a company to balance outcomes in the moment, to match what the company needs while aligning with its strategy. Given the resources, I see a continued migration toward deeper intelligence, analytics, and customer insights, combined with solid pricing discipline.
I’ve told teams over the years: if the goal is just to beat a competitor by a penny or hit a certain margin rate, anyone with basic spreadsheet skills could do that. We don’t need a pricing department for that. But if we want to achieve the right price for the right item, targeting the right customer at the right time, it requires a robust set of tools and a new mindset. That’s what it takes to get pricing right.
EB: Great answer considering I put you on the spot with such a big question. You answered in the immediate sense, saying that if an organization doesn’t adopt certain technologies in the next two to three years, they likely won’t be doing anything differently by 2030, given how long those changes can take. That was a great point.
Then, you mentioned the perception around optimization, and I’ll add to your points here. I wouldn’t say this is necessarily quoting you directly, but there’s a perception around optimization, particularly in price optimization, as simply a means to maximize a single outcome. Historically, initial implementations focused on maximizing profit, often at the expense of loyalty, trust, and other key factors. As a result, “optimization” almost became a bad word for several years. Would you say this was the case around 2010 through 2016?
WW: Yes, it’s been a long time.
EB: Right, and if we went back and looked at the independent analyst reports, we’d probably see a trend there, showing a dip in price optimization discussions during that period, before it started picking back up. You also mentioned the need for multivariable optimization—a way to optimize across multiple dimensions and present a portfolio of options and strategies.
Do you think that even for organizations where pricing isn’t currently a priority, there will be a natural adoption of these technologies over time as they become more accessible and can be implemented alongside other initiatives? Or do you think that, culturally, some of these companies might continue down their current path because they’re, in a way, a victim of their own success?
WW: In some ways, I hope they don’t automatically adopt it, and I’ll explain why. I admit I’ve contributed to the notion of “art and science” in pricing for years—it’s a term that was often used to drive sales and adoption of software, not just in pricing but across optimization tools in general. But over time, I’ve realized that “art and science” is really just a marketing buzzword. The reality today is that it’s not art and science; it’s judgment and science. If executed well, it becomes an art. Handing a four-year-old a crayon doesn’t necessarily produce something you’d put up in the Sistine Chapel. There’s an overreliance on technology alone. I remember a quote from a pricing conference: “You’re not going to lose your job to a machine; you’ll lose it to someone who knows how to work with one.” This balance of technology and judgment is essential.
I worked with Paul Hunt from a consultancy in Toronto, and he emphasized that you need to understand how pricing works before you can automate it effectively. Many optimization efforts over the years have failed because organizations got the tools, saw an opportunity to raise prices, and expected profits without considering the judgment necessary to apply those changes in a way that maintains customer trust.
For instance, when I was at BevMo, we had periodic meetings with a price software company, and they noted we’d overridden many of the software’s recommendations and actually outperformed the predicted outcome. That’s a clear example of how judgment and science working together can produce optimal results.
A healthy dynamic is when software companies, yours included, recognize that when users override a recommendation, it means one of two things: either the human judgment needs to be corrected, requiring internal conversations within that organization, or the science itself might need adjustment. In the latter case, machine learning can then adapt from those human interventions, automating the improvements for future use.
EB: That’s really well said. You essentially explained reinforcement learning, training datasets, and data labeling in the context of pricing. Do you think this understanding is widespread—that’s how it works?
WW: Not really, but I’ve been trying to illustrate it with simple exercises. I have my team perform parlor tricks where half the team calculates simple tasks without any tools, while the other half uses calculators and spreadsheets. Surprisingly, the team without tools often wins in simple calculations. But when it comes to more complex calculations, the machine, of course, has the advantage. It’s about knowing where machine capabilities can add value and taking advantage of what they offer to enhance our judgment.
EB: That’s brilliant. So often, we try to prove out the bells and whistles, showcasing how advanced use cases can be. But to your point, let’s start with a baseline. Are there certain functions we can all agree a computer simply cannot perform? If so, where does that leave us?
I’m now picturing you in a magician’s outfit, running this workshop as “the wizard behind the curtain.”
WW: [laughs]
EB: As you consider your experience with pricing implementations, and with everything we discussed about the future of pricing, do you think we’ll see a growth in pricing functions and roles in the coming years? Will opportunities expand as people continue to work alongside machines, or will they stay flat? Or do you think AI could start replacing some of those roles altogether? I’m not asserting any of these—I’m curious to hear your take.
WW: I’m borrowing this idea from Simon Kucher and others I’ve heard at recent conferences, but there is a strong likelihood of more organizations recognizing the need for specialists in pricing. This specialization is essential. It’s like going to a doctor who actually studied medicine or to a mechanic who knows about your specific car.
In a stable environment, setting a price annually or making minor adjustments is manageable. But in a volatile market, you can’t afford to wait 12 months to adjust prices. Rising costs require timely pricing adjustments, or you risk hurting profitability. Similarly, falling costs demand responsiveness to stay competitive. As volatility increases across different sectors, organizations need to be better prepared—investing in the right people, tools, and technology to meet these challenges. Otherwise, they could end up like Kmart in five to ten years.
Now, on the AI side, there’s a growing recognition, even in the stock market, that perhaps we got swept up in the hype too quickly. The buzz around AI feels similar to the hype over the metaverse just two years ago, which faded quickly. AI may have more staying power, but the question is about using it efficiently and effectively in day-to-day operations to generate real value. In 10 or 15 years, AI might just become seamlessly embedded, running in the background without anyone actively noticing it, which I think is where this all ends up.
For change management, new tools need to integrate seamlessly into existing workflows; people have limited time. You might hear, “It’s just 15 minutes,” but when each new task is “just 15 minutes,” it adds up quickly. Workers are evaluated on their output, and there’s a natural tendency to stick to what they know so they can get things done. As we bridge into using more sophisticated tools, it will be key to ensure these changes aren’t disruptive. The tools should improve outcomes in the background—better prices, better results—without needing the user to adjust how they work. Then, when AI enhancements help people do their jobs more effectively, they’ll recognize the value without the friction of upfront change.
EB: Absolutely. And as you discuss pricing as a specialization, becoming a pricing expert involves exactly what you’ve demonstrated throughout this conversation—stepping back to examine all the influencing factors and understanding what’s really driving the outcomes.
And then there’s the psychological component, the perception shaped by psychology, right? We also have store operations, supply chain, change management, incentives—all these elements come into play. So even as you specialize, the field of pricing inevitably becomes incredibly broad.
WW: Exactly. To be a successful specialist, you have to draw from various disciplines and consider factors beyond what’s immediately in front of you.
Recently, there’s been a lot written about the potential decline of sound economic policy—not from a partisan perspective, but just questioning if we’ll still rely on fundamental economic principles moving forward.
As a pricing professional, I need to think ahead about potential policy shifts, such as tariffs. What would they mean for our pricing? I can’t wait until a 25% tariff is imposed; I need to anticipate it. Similarly, if price gouging restrictions or price controls come into play, I have to prepare to navigate these challenges with a focus on customers, costs, and supply and demand before they fully impact us.
EB: And if an organization isn’t already gathering teams to proactively address these issues, would you say it’s the responsibility of the pricing expert to raise these concerns? Should they be the ones to initiate a contingency plan for when tariffs are implemented and costs increase?
WW: Yep. And again, it’s a challenge. You don’t want to appear to be crying wolf, and sometimes it’s better to take a measured approach. Cooler heads might prevail by February or March next year, and we might not see tariffs, but then we’ve spent all this time preparing for something that didn’t happen.
EB: I understand the challenge you’re describing, especially when you’re trying to prepare for scenarios that might not even materialize. It’s a delicate balance between being proactive and not overreacting to uncertainty. But it’s that kind of foresight that ultimately helps organizations stay agile and ready for whatever comes next.
WW: And some of it may be as simple as, you know, leaders like people coming to them with solutions, not just problems. Right? So there’s probably the burden for a pricing person to be thinking through, OK, what would those answers be? I had an experience years ago where we could see what was coming at us, and I said, “This is what we need to do” — or I didn’t say we needed to do this, but this is an option that’s going to cost a lot of money, but I’m telling you, it’s going to cost less money than if we don’t do it. And we kind of went through the first round of what happened, and sure enough, it cost a lot of money. We implemented some of the stuff we had talked about, and all of a sudden the second and third rounds basically were just blips. It costs a lot to do it, but having done it, it mitigated the impact of not doing it at all.
EB: Thank you, as always, for sharing your insights, Wes!
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