The Real Friction in GTM Isn’t Human, It’s Systemic

The modern revenue engine isn’t slowing down because reps can’t sell. It’s slowing down because the systems meant to help them, particularly CPQ (Configure, Price, Quote), weren’t designed for the velocity and volatility of today’s go-to-market (GTM) motion. Sales leaders often blame sluggish quotes on rep hesitation or poor process discipline. Fixing this requires more than sales enablement. It demands re-architecting CPQ as a dynamic execution layer owned by revenue operations.

When Systems Can’t Keep Up with Sales Velocity

At first glance, slow quotes appear to be a people problem. Reps aren’t following playbooks, discounting takes too long, and approvals go dark. But closer inspection reveals something more structural.

In mid-market and enterprise teams, CPQ is often buried in IT workflows that cannot adapt to evolving deal cycles. It was originally built to enforce governance in the quote process and has calcified into bureaucratic chokepoints, locked behind DevOps walls, where every tweak to pricing, packaging, or logic requires a ticket, sprint, and delay.

This friction doesn’t live at the quote level. It lies deeper: in the invisible handoff between systems, the misaligned logic layers, and the inability to make changes in real time. In a revenue world moving at API speed, GTM execution is throttled by tools built for static workflows, not high-velocity cycles.

Developer-Controlled CPQ Is a Silent GTM Tax

When a developer owns CPQ, every change becomes a cost center. RevOps and sales leaders may spot a pricing inefficiency or a broken approval path, but they can’t fix it themselves. They wait for days, sometimes weeks, for dev tickets to clear. Other prospects and competitors use this to their advantage to secure the sale. 

According to a 2024 Forrester report found that 86% of B2B purchase journeys stall during the buying process, often not due to buyer intent, but because quote-level logic cannot respond in time to meet deal signals When pricing engines and approval chains are locked behind rigid, developer-controlled CPQ systems, every stalled interaction is a signal of deeper, systemic drag. 

Sales Speed Depends on CPQ Agility

Quotes don’t happen in isolation. They’re the downstream output of decisions about pricing strategy, product configuration, customer segmentation, and risk governance. If the CPQ system can’t absorb these decisions quickly and safely, sales speed suffers no matter how skilled your representatives are.

Gartner research predicts that by 2025, 80% of B2B sales interactions between suppliers and buyers will occur in digital channels. This is due to 33% of all buyers desire a seller-free sales experience, and 44% for millennials. In this increasingly digital landscape, the quality and speed of the quoting process becomes even more critical. After all, the quoting experience is the sales experience. CPQ isn’t just an operational tool; it’s the front line of customer perception. If it’s slow, rigid, or error-prone, it drags down your entire GTM engine.

Why CPQ Needs to Shift from IT to Revenue Operations 

The answer isn’t just faster sales training or better CRM hygiene. It’s a fundamental shift in who controls CPQ logic. When RevOps teams are empowered to directly manage pricing structures, approval workflows, and product configurations, they remove weeks of drag from the quoting cycle and gain a sense of control over the process.

This role-based control flips the model. Instead of CPQ serving as an IT-governed system of record, it becomes a RevOps-owned system of execution. Intuitive interfaces allow ops leaders to adapt logic on the fly, launching promotions, updating discount thresholds, or rerouting approvals without writing a line of code.

Platforms like DealHub are enabling a new model, one where revenue operations owns the logic layer. With low-touch configuration, teams can instantly implement changes across pricing and approvals without compromising governance, as the guardrails are already built in.

AI-Powered CPQ is the End of Approval Gridlock

DealHub’s platform uses AI to recommend optimized workflows, flag risky deals, and dynamically approve clean quotes within set thresholds. The impact? Reps aren’t waiting on approvals. RevOps isn’t chasing down logic bugs. Sales cycles tighten, and trust in the system increases.

Research from SuperAGI shows that AI-powered sales teams can increase sales productivity by 30-47%, reduce workload by 40%, and save around 12 hours per week. The adoption rate of AI in sales has reached an all-time high, with 45% of sales professionals using AI at least once a week. In fact, companies have reported a 25% increase in sales revenue after adopting AI sales tools.

From Friction to Flow

GTM often doesn’t stall because reps lack skill; rather, the systems meant to support them can’t keep pace with modern deals. When pricing logic is buried in dev queues and approvals run on outdated workflows, even high-intent buyers get stuck. Forecasts slip. Competitors pounce. And what appears to be a pipeline problem is actually an execution drag hiding in the quote flow. For sales leaders, it’s a painful truth: you can’t coach your way around broken infrastructure.

In today’s motion, quoting isn’t just a step in the process; it is the process. Every price, approval, and configuration is an execution decision that shapes deal velocity. That’s why sales and operations leaders are moving CPQ out of IT and into their own hands. With DealHub, they’re not just improving quote speed; they are operationalizing strategy through a role-based, AI-powered execution layer built for governed scale. That’s how CPQ shifts from a blocker to a GTM advantage.