Most enterprises don’t have a pricing technology problem. They have a pricing automation and workflow problem. Despite significant investment in pricing software, 85% of still rely on spreadsheets in daily pricing workflows. Here’s why the pricing intelligence and live commercial decisions gap persists, plus 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 critical difference between producing pricing intelligence and putting that intelligence to work. A pricing team can develop sophisticated segmentation, model willingness to pay, establish guardrails, and identify margin leakage. The commercial value of that work is determined by what happens in a live negotiation, not inside the pricing platform.
That negotiation involves competitive pressure, customer history, product availability, contract terms, changing costs, margin targets, and a deadline. Sales wants to preserve momentum. Pricing wants consistency. Finance wants to protect margin. Each priority is legitimate. Only one controls the clock: the customer.
These pressures converge on a single decision. When the guidance needed to inform that decision requires a separate login, another dashboard, or additional interpretation, the seller faces a choice: follow the pricing process or close the deal. That is the pricing execution gap. It is where B2B pricing strategy breaks down in practice.
Your spreadsheets are telling you something
Spreadsheets are not the root cause of poor pricing performance. They are a symptom of broken pricing automation. When 46% of organizations describe themselves as only partially automated (Copperberg/Vendavo, 2026), the spreadsheet is filling a gap that the official workflow fails to close.
There is usually a specific reason people export from enterprise platforms into spreadsheets: the official workflow fails to deliver what they need, when they need it. Rather than treating spreadsheet use as a failure of discipline, treat it as diagnostic data.
The productive question is: what job is the workaround doing that your pricing automation workflow is not? The answer is typically one of four things: speed, visibility, context, or explainability. These give you the ability to understand why a recommendation was made, not just what it is.
Close the workflow gaps before adding more technology
Copperberg and Vendavo research (2026) identifies exactly where execution breaks down: 39% of organizations cite platform integration as a quoting bottleneck, 38% point to manual effort, and 25% identify approval delays. These are workflow problems, not technology gaps. Adding another tool will not solve them.
Closing the pricing execution gap means connecting intelligence to execution so commercial teams operate as a coherent system. In practice, that requires four things:
- Pricing guidance appears where sellers quote, not in a separate environment that requires a platform switch.
- Margin risk is visible while the deal is still in motion, not discovered in a post-close reconciliation.
- Approval logic is clear enough that escalation is reserved for decisions that genuinely require human judgment.
- Pricing, sales, and finance work from consistent data so there is no competing version to reconcile 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 the enemy. Treating it like noise is. Faster customer expectations, shifting costs, competitive dynamics, and the data volume generated by complex B2B pricing environments will only increase. The objective is not to simplify it. The objective is to make it work for the people making decisions.
This is where pricing automation earns its place. AI processes commercial data at a scale no pricing team could replicate manually: surfacing signals, flagging margin risk, and delivering guidance as decisions are made. What AI cannot do is apply judgment, navigate relationships, or orchestrate competing strategic priorities.
That is what pricing experts do best. When machine intelligence and human expertise operate together inside a coherent commercial system, complexity becomes a competitive asset rather than an operational constraint. Automated pricing optimization changes what experts spend their time on: less data processing, more 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
For organizations that have already invested substantially in pricing technology, there is a meaningful insight in the execution gap: the capability needed to improve performance may already exist. The next step is not another platform. It is connecting pricing intelligence to the workflows where commercial decisions actually happen.
When pricing analytics, automation, and human judgment operate together inside a coherent commercial system, pricing shifts from an analytical function to a repeatable commercial discipline, one that captures value systematically rather than relying on escalation after margin has already been lost.
That is the right measure of pricing automation maturity: not which tools are deployed, but whether the people making commercial decisions are getting the right guidance while they can still use it.
That is a considerably more valuable objective than simply adding another tool.
Frequently Asked Questions (FAQ)
What is the pricing execution gap?
The pricing execution gap is the distance between what a pricing team knows — through analytics, AI, and market intelligence — and what commercial teams actually do when making pricing decisions. It exists when pricing guidance is inaccessible, delayed, or disconnected from the workflows where quotes and deals are closed.
Why do enterprises still use spreadsheets for pricing in 2026?
According to Copperberg and Vendavo research (2026), 85% of organizations still rely on spreadsheets in daily pricing workflows despite enterprise platform investment. Spreadsheets persist because they fill gaps in pricing automation: when an enterprise platform does not deliver guidance where and when sellers need it, they default to tools that do.
What is pricing automation?
Pricing automation is the embedding of pricing logic, guardrails, and approval workflows directly into commercial platforms — so that pricing decisions happen consistently, with policy-aligned guidance, without requiring manual intervention at every step.
How do you close the pricing execution gap?
Closing the pricing execution gap requires connecting pricing intelligence to the systems where decisions are made: embedding guidance in CPQ and quoting tools, making margin risk visible during active deals, clarifying approval logic, and ensuring pricing, sales, and finance work from a single data source.
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/