Most enterprises do not have a pricing technology problem; they have an execution problem. Let’s explore why the gap between pricing intelligence and live commercial decisions persists, and what it takes to close it.
Pricing technology has advanced considerably. Pricing execution has not always kept pace.
Manufacturers and distributors have spent years investing in pricing platforms, CPQ, analytics, automation, and AI, but spreadsheets remain firmly embedded in daily pricing work. Quotes still stall in approval queues, sales teams still override recommendations, and pricing teams still reconstruct margin performance after the fact.
The issue is not necessarily a lack of technology. It’s the distance between what that technology knows and what the commercial organization actually does. That distance is the pricing execution gap.
Copperberg and Vendavo research brings the scale of the problem into focus, finding that 85% of surveyed organizations still rely on spreadsheets in daily pricing workflows, 46% describe themselves as only partially automated, and just 14% say their infrastructure is fully scalable.
For enterprises that have already invested substantially in pricing technology, those numbers point to an important conclusion: Adding another tool is unlikely to solve a problem created by disconnected execution.
Pricing decisions do not happen in controlled conditions
There is a fundamental difference between producing pricing intelligence and putting that intelligence to work. A pricing team can develop sophisticated segmentation, analyze willingness to pay, establish guardrails, identify margin leakage, and recommend an optimal price. But the commercial value of that work is determined somewhere else.
It occurs when a salesperson is negotiating with a customer who wants an answer now. That moment can include competitive pressure, customer history, product availability, contract terms, changing costs, margin targets, and an approaching deadline. Sales wants to preserve momentum, pricing wants consistency, and finance wants to protect margin.
Commercial complexity converges on a single decision: If the guidance needed to make that decision is sitting in another dashboard, requires another login, or needs additional interpretation, the seller faces a choice between following the process and moving the deal forward. That’s where workarounds begin.
Your spreadsheets are telling you something
It’s easy to make spreadsheets the villain in pricing transformation. They are often better understood as a symptom.
There is usually a reason why people repeatedly export information from an enterprise platform into a spreadsheet, rebuild analysis manually, or maintain parallel trackers. The official workflow is not giving them something they need at the point they need it, and the spreadsheet fills the gap.
Copperberg and Vendavo’s research makes this distinction particularly clear: Spreadsheets interrupt the flow of data, decisions, and accountability, but continued spreadsheet use can also reveal where the surrounding infrastructure is failing to serve its users. Removing Excel without removing the reason people depend on it simply moves the friction somewhere else.
A more useful question is: What job is the workaround doing that our commercial platform is not? The answer might be visibility, speed, context, or the ability to understand why a recommendation was made.
Find that gap, and you have found a more productive starting point for pricing transformation.
Close the workflow gaps before adding more technology
According to the Copperberg and Vendavo research, 39% of surveyed organizations cite platform integration as a quoting bottleneck, 38% point to manual effort, and 25% identify approval delays.
These are not abstract technology problems but workflow problems. The opportunity is to connect intelligence to execution so that commercial teams can operate as one coherent platform rather than a collection of capabilities:
- Pricing guidance should appear where sellers quote.
- Margin risk should become visible while the deal is still moving.
- Approval logic should be clear enough that escalation is reserved for decisions that genuinely require it.
- Pricing, sales, and finance should work from consistent data rather than reconciling competing versions after the decision has already been made.
This is where AI becomes particularly useful. Not as another layer of technology, but as a way to make the technology already in place perform more effectively.
Make complexity work for the people making decisions
Commercial complexity is not going away. Customers will continue to expect faster responses, costs will move, competitive conditions will change, and product portfolios, channels, contracts, and customer-specific terms will continue generating enormous amounts of commercial data.
Trying to eliminate that complexity is the wrong objective. The opportunity is to make it usable.
AI can grapple with data at a depth and scale beyond human capability, surfacing relevant signals and guidance as decisions are made. Human experts can then do what they do uniquely well: apply judgment, understand relationships, orchestrate trade-offs, and determine strategy.
That combination turns complexity from a constraint into an advantage.
It also changes what pricing transformation looks like. Instead of asking how many capabilities have been deployed, leaders can ask more consequential questions:
- Are sellers getting guidance while they can still use it?
- Are approval cycles becoming more purposeful?
- Are pricing teams spending less time processing exceptions?
- Can finance see margin risk before it becomes realized margin loss?
- Can every consequential pricing decision be traced back to its rationale and inputs?
Those are signs of execution.
The next pricing advantage may already be inside your enterprise
There is good news in the execution gap for organizations with years of technology investment behind them: The capability required to improve performance may already exist. The next step is making pricing intelligence part of how commercial decisions actually happen.
Pricing becomes more than an analytical capability when intelligence, workflows, and human judgment operate together. It becomes a repeatable commercial discipline, one capable of systematically capturing value rather than relying on heroic intervention when margin has already begun to disappear.
That is a considerably more valuable objective than simply adding another tool.
Close your pricing execution gap
Why do 85% of organizations still rely on spreadsheets in daily pricing workflows? And where can AI make a measurable difference?
Download Closing the Pricing Execution Gap with AI, the new whitepaper from Copperberg and Vendavo, for the research, practical recommendations, and an eight-point checklist for assessing your own pricing execution.
Then pressure-test your own execution with Vendavo’s pricing tools and assessments: https://www.vendavo.com/insights/tools/