Why Pricing Technology Fails at Distributors, and What Successful Transformations Do Differently

Pricing leaders from Henry Schein, Jennings Executive Search, and ProfitOptics discuss why pricing implementations stall, how to build organizational trust, and what AI changes about the future of pricing technology.

Distributors and manufacturers have invested heavily in pricing technology. Yet many still struggle to turn that investment into consistent, measurable improvements in pricing performance.

The challenge often isn't the pricing model itself. It's everything surrounding it: data that doesn't support the decisions people need to make, processes that vary across teams, technology that doesn't fit existing workflows, and salespeople who don't trust the recommendations they're given.

Pricing technology implementations often fall short because companies focus on the software before aligning the people, processes, data, and business outcomes that make it valuable.

That was a central theme of a recent ProfitOptics roundtable exploring pricing transformation, organizational readiness, and the growing role of AI.

The discussion brought together five leaders with different perspectives on the challenge:

• Alex Kugler, VP of Strategic Pricing, Henry Schein
• Ryan Walter, Partner, Jennings Executive Search, and author of The Pricing Talent Playbook
• Jon Ladle, Chief Strategy Officer, ProfitOptics
• Dave Anderson, Managing Director, Commercial Excellence Strategy, ProfitOptics
• Geoff Marlatt, CEO, ProfitOptics, who moderated the discussion

Their conversation surfaced five lessons for organizations considering a new pricing platform, modernizing an existing environment, or deciding how AI fits into their commercial operations.

1. Start With a Transformation Roadmap, Not a Technology Decision

Pricing transformation is rarely a single software project.

At Henry Schein, Alex Kugler described a broader transformation that involves organizational structure, existing ERP capabilities, data infrastructure, pricing processes, and a longer-term technology roadmap.

The sequencing matters. Pricing capabilities depend on the quality of the underlying data and the organization's ability to act on it. Related processes, including rebates, chargebacks, quoting, and contract management, also need to be considered in the larger plan.

Jon Ladle reinforced the importance of establishing leadership alignment and understanding the business problem before choosing a technology solution.

A company may know it wants better pricing recommendations. But that isn't yet a complete definition of success. Does the business need more consistent execution across branches? Better control over exceptions? Faster quoting? Improved margin visibility? Less manual work?

Those answers should shape the roadmap and the technology, not the other way around.

The takeaway: Define the business outcomes, dependencies, and organizational requirements before selecting the software.

2. A Pricing Recommendation Has No Value If Nobody Trusts It

A sophisticated pricing model can recommend an optimal price. That doesn't mean a salesperson will use it.

Jon Ladle emphasized that adoption and explainability are essential to pricing performance. A recommendation that looks like a black box may struggle to gain traction, even when the underlying mathematics are sound.

Pricing leaders need to understand how recommendations are presented, how exceptions are handled, and whether the system gives employees enough context to make confident decisions.

This changes what success looks like.

Instead of evaluating pricing technology only on model accuracy, organizations should also examine what happens at the point of execution. Are salespeople accepting recommendations? When they override them, why? Are discounts becoming more consistent? Can managers identify patterns that deserve attention?

These measures help distinguish a technically successful implementation from one that is improving commercial performance.

The takeaway: Build trust and usability into pricing technology from the beginning. Adoption is part of the return on investment.

3. Pricing Transformation Is a People Challenge as Much as a Technology Challenge

Pricing touches nearly every commercial function.

Sales, finance, IT, operations, and executive leadership may all have different expectations of what a pricing initiative should accomplish. Those expectations need to be reconciled before a new process or system is rolled out.

Dave Anderson highlighted the importance of understanding stakeholders and managing change. The people who will use a new capability need to see how it improves their work, not simply how it supports a corporate initiative.

Ryan Walter approached the issue through talent and organizational design.

The right pricing team depends on what the business is trying to accomplish. His framework examines capabilities across leadership, analytics, strategy, execution, and governance.

A company investing in advanced analytics may still struggle if it lacks the people to translate insights into decisions, establish policies, or work effectively with the sales organization.

Likewise, a capable team can be constrained by fragmented processes and systems that make consistent execution difficult.

The takeaway: Treat talent, stakeholder alignment, governance, and change management as core elements of the transformation, not supporting activities.

4. AI Changes What's Possible, but It Doesn't Fix a Broken Process

AI is changing the economics of software development and the skills pricing teams will need.

It can help teams analyze information, develop capabilities, accelerate repetitive work, and explore solutions that previously required more time or specialized resources.

But the panelists also raised important cautions.

Dave Anderson warned against using AI to automate processes that are already ineffective. Making a flawed workflow faster doesn't necessarily make the business better.

Ryan Walter discussed how AI is changing expectations for pricing talent, including the importance of asking good questions, evaluating outputs, and applying judgment rather than simply producing analysis.

Alex Kugler described the distinction between individual experimentation with AI and the governance required when AI becomes part of an enterprise process. Business-critical decisions require appropriate oversight, validation, and controls.

The implication for pricing leaders is straightforward: AI should be applied to a well-understood business problem, with clear accountability for the results.

The takeaway: Use AI to improve how pricing work gets done, but keep experienced people responsible for defining the problem, validating the output, and managing the business impact.

5. The Right Pricing Technology Should Fit the Business, Not Force the Business to Fit the Technology

One implication of the discussion is that pricing technology decisions should begin with the realities of the business.

Distributors and manufacturers often operate with established ERP environments, complex commercial agreements, specialized customer relationships, and pricing practices developed over many years.

Some of those processes should change. Others reflect genuine competitive differences or operational requirements.

The challenge is knowing which is which.

A standardized platform may be a good fit when its capabilities align with the company's needs. But when important workflows fall outside the platform's assumptions, businesses can find themselves maintaining spreadsheets, creating workarounds, or waiting for functionality that may not arrive.

This is where the technology conversation is changing.

Organizations have more options to build specialized capabilities around the systems they already use. AI-assisted engineering and reusable technology foundations can make custom development a more practical option than it was in the past.

At ProfitOptics, this is central to our approach. We build custom software for pricing, rebates, and quoting for distributors and manufacturers, working with their existing ERP and business systems rather than requiring a wholesale replacement.

The goal isn't custom software for its own sake. It's to give the business the capabilities it needs to improve pricing execution and protect margin.

For an example of what this can look like, see how a manufacturer improved quoting speed and pricing consistency with a pricing application integrated into SAP and Salesforce.

The takeaway: Start with the capabilities the business needs, then determine whether to buy, configure, or build them.

What Should Pricing Leaders Do Before Their Next Technology Investment?

The discussion points to five questions worth answering before committing to a pricing technology initiative.

1. What specific business outcome are we trying to improve?

Identify the problem in operational and financial terms. Better margin, faster quotes, more consistent pricing, fewer manual exceptions, and stronger governance are related goals, but they aren't interchangeable.

2. Do we understand the current process well enough to improve it?

Map how pricing decisions happen today, including the spreadsheets, approvals, handoffs, and exceptions that may not appear in formal process documentation.

3. Will the people who use the technology trust it?

Involve the people making and approving pricing decisions. Understand what information they need, what slows them down, and what would make a new approach useful.

4. Do we have the capabilities to sustain the change?

Evaluate the skills, leadership, data governance, and operating processes required after the initial implementation.

5. Does the technology fit the business and the systems we already run?

Understand what can be accomplished with existing systems, where additional capabilities are needed, and whether the proposed solution will simplify or complicate daily work.

The larger lesson is that successful pricing transformation isn't measured by whether new software goes live.

It's measured by whether the organization makes better pricing decisions, more consistently, in the course of doing business.

Frequently Asked Questions About Pricing Technology

Why do pricing technology implementations fail at distributors?

Pricing technology implementations often fall short because organizations introduce software before addressing the conditions required for success.

Those conditions include reliable data, a clear pricing strategy, executive alignment, defined responsibilities, and the ability of sales and pricing teams to use the technology in their daily work.

Even strong pricing recommendations have limited value if employees don't understand or trust them. Successful implementations align the technology with business processes, organizational capabilities, and measurable commercial outcomes.

How can distributors improve pricing software adoption?

Distributors can improve adoption by involving sales, pricing, finance, operations, and IT stakeholders early, then making the technology useful within existing workflows.

Pricing recommendations should be understandable, exceptions should be manageable, and employees should have clear guidance about when and how to act.

Leaders should also measure behavior, including recommendation acceptance rates, overrides, and discount patterns, rather than relying only on whether users have logged into the system.

A useful example is a ProfitOptics pricing and quoting implementation that achieved full adoption across more than 100 sales users by integrating pricing guidance into their quoting process.

Can pricing software work with an existing ERP system?

Yes. Pricing capabilities can often be added or improved without replacing the ERP.

ERP systems remain essential to core operations, but specialized commercial requirements may call for capabilities beyond the standard ERP functionality.

Custom pricing applications can connect with existing ERP, CRM, and quoting systems to support pricing recommendations, margin visibility, approval workflows, and other specialized needs.

For example, ProfitOptics built a pricing application integrated with SAP and Salesforce that helped a medical equipment manufacturer reduce quote turnaround time by more than 75%.

The right approach depends on the company's existing architecture, data, and business requirements.

Should distributors buy pricing software or build custom pricing capabilities?

The decision depends on how closely available software matches the company's business requirements.

A standardized platform may be appropriate when its capabilities fit the organization's pricing processes and can be implemented without excessive workarounds.

Custom software becomes worth evaluating when critical requirements are highly specialized or when the company needs capabilities that work across several existing systems.

Building also doesn't have to mean starting from scratch. Reusable technology foundations and AI-assisted engineering can help accelerate development while allowing the solution to reflect the company's specific requirements.

The best starting point is a clear definition of the problem, the expected business value, and the long-term requirements for operating and supporting the solution.

For more on this changing decision, read Dave Anderson's perspective on pricing technology and the shift from build versus buy to build versus build

About ProfitOptics

ProfitOptics builds custom software for pricing, rebates, and quoting for distributors and manufacturers.

Our operator experts work with customers to understand where margin gets made or lost, then build the capabilities needed to improve performance. We work with the ERP and business systems customers already run, combining commercial expertise, reusable technology foundations, and AI-assisted engineering.

Keep what works. Build what's missing.

Explore ProfitOptics customer outcomes or learn more about our approach.