Revenue Operations Leader
Catherine Jones
Most revenue teams don’t have a pipeline problem.
They have a system problem.
Revenue Operations Leader
Most revenue teams don’t have a pipeline problem.
They have a system problem.
Core Expertise
Across 15 years and organizations at every stage of scale, I’ve learned to hold both. These are the domains where I operate — and what breaks when this thinking is absent.
Most pipeline problems are governance problems in disguise. I design the end-to-end operating model — forecasting, ARR and NRR reporting, renewal operations, and the cadences that give leadership a number they can defend.
The annual plan fails when it has no model underneath it. I’ve owned territory design and quota allocation planning in partnership with Sales leadership, Finance, and HR — building the bottoms-up revenue model and presenting the outputs to the CEO and CSO.
When sellers stop logging activity, the problem is never the system — it’s that no one ever acted on the data. I rebuild the governance and process discipline that make the CRM worth using, and stay that way after I’m no longer in the room.
A forecast is only as credible as the data feeding it. I build the models and dashboards that give every stakeholder — from the front line to the board — a single trusted view of pipeline health, attainment, and risk.
Comp disputes and behavioral drift are almost always a misalignment problem, not a math problem. I partner with HR and Rewards to design incentive plans that connect rep behavior to company goals, and build the quota and territory architecture that makes the numbers defensible.
The handoff between marketing and sales is where qualified pipeline goes to die without governed routing logic. I’ve built the MQL scoring, lead routing, and handoff architecture in HubSpot and Salesforce — and trained the sales teams that use them.
Where I Create Impact
Pipeline data that doesn’t match what Finance sees. I rebuild the governance layer that creates one trusted number across every function.
Reps who can’t state their own attainment. I build the seller analytics that give each rep and leader clear, real-time performance visibility.
Scaling headcount into revenue architecture that hasn’t kept pace. I design the handoffs, CRM governance, and comp structures that grow with the business.
A CRM that’s a system of record in name only. I rebuild the governance, stage signal definitions, and process discipline that restore trust in the data.
Leadership making resourcing calls without reliable data. I build the reporting and forecasting infrastructure that closes the visibility gap.
NRR is lagging but no one can say why. Expansion revenue is invisible, renewal risk surfaces too late, and CS has no shared data model with Sales. I build the reporting infrastructure that makes revenue retention as visible as revenue acquisition.
Sellers spending more time on admin than selling. I redesign the workflow and CRM architecture that removes the friction slowing down the revenue motion and gives reps their time back.
A forecast that leadership presents but doesn’t believe. I build the methodology and stage signal architecture that turns the number into something everyone in the room can defend.
Comp disputes surfacing every commission cycle. I design the incentive architecture and quota logic that remove the ambiguity reps exploit and the disputes that erode trust between Sales and Finance.
My Approach
I don’t arrive with a template. I diagnose before I design, build with the team rather than for them, and the infrastructure I leave behind keeps running when I’m not in the room.
Forecasting breaks down more often from bad data than bad math, and CRM adoption breaks down more often from bad process design than bad training. Before any architecture decision, I map where trust has broken down — between Sales and Finance, between the system of record and what leadership actually believes.
The best system is the one the org can actually adopt. I build toward the end state in phases they can absorb — fitting the team’s current capacity, existing technology, and the political reality of how decisions get made. A perfect system that never gets used is just a PowerPoint.
My job is to set the architecture standard and be accountable for the outcome — not to be the last person touching the system. If it only works while I’m in the room, the design wasn’t finished.
Leadership has the visibility to make confident decisions. Revenue teams have the systems to perform with accountability. The infrastructure holds after I stop touching it — that’s the only standard that matters at this level.
Most AI investments in RevOps stall at the data layer, not the tooling layer. The same four failure modes that break revenue systems also determine whether AI investments compound or stall. I build the foundation first. Then the automation holds.
Where Revenue Actually Breaks
A Series B with 20 sellers and a €1B global org with 140 present differently. But underneath the scale difference, I’ve found the same four structural failure modes, in different proportions. I map them before I redesign anything.
Do the people making decisions trust the numbers in front of them? If not, the break is usually upstream — in how the data is captured and governed, not in the forecasting model itself.
When something breaks or underperforms, is it clear who owns it? I look for the governance voids — territories without owners, processes without DRIs, handoffs that exist in someone’s memory rather than a system. Ambiguity at this level is expensive and compounds quarterly.
Are the people doing the work measured in a way that actually incentivizes what the business needs? Comp disputes, behavioral drift, and missed ramp targets are almost always symptoms of a misalignment between the performance model and the operational model — not a people problem.
Do teams have the systems and rhythms to execute consistently at the volume and speed the business requires? Strategy without an operating model is a slide deck. I build the cadences, stage signal architecture, and workflow infrastructure that make the plan executable — and keep it that way.
The organizations I’ve worked with weren’t unique. The dysfunction was structural — and structural problems have structural solutions.
Case Studies
Three organizations at different stages and scales. The architecture decisions made, the structural bets taken, and what came out the other side.
Senior Director, Revenue Operations & Sales Enablement — reporting to the CEO
Pricing governance was the presenting complaint, but the revenue system had no architecture underneath it to support it. The CRM carried a 45% error and duplication rate, stage definitions were rep-interpreted, territory ownership was ungoverned, and there was no CS reporting layer — NRR, renewal performance, and customer health were invisible to Finance and leadership alike.
For a Series B company preparing for its next raise, that level of revenue opacity is a data room problem. Investors stress-test ARR cohorts, pipeline coverage ratios, and stage-weighted forecasts. None existed in a form leadership could stand behind. The annual plan had no model underneath it — and no one owned the process of building one.
Data quality and manual workflows were the constraint — not the tools. Before any automation could work, the governance layer underneath it had to be rebuilt.
“At Series B, the question investors ask isn’t whether the product works. It’s whether the revenue system is real. Is the ARR clean? Does the pipeline coverage hold up? Is the forecast methodology something leadership can defend in a data room? I built the infrastructure that made those answers yes — and ARR grew 20% while the average sales cycle shortened by seven days.”
Global Senior Manager, Sales Force Effectiveness — promoted from Head of Sales Operations, Americas
At €1B with 140 sellers across multiple global markets, the organization had scaled past the operating model designed to run it. Each region produced its own numbers. Leadership received conflicting reports from conflicting systems. Each region’s forecast broke down for the same structural reason: no shared governance model, not a lack of effort from any single team.
Commission disputes corroded rep trust. Forecasts sat unused. A global sales organization at the scale to drive significant growth had no infrastructure to know whether it was. At that size, fragmented revenue visibility isn’t a reporting problem. It’s a strategy execution problem.
The technology existed. The workflows were misaligned across regions and the change management to standardize them had never happened. Standardizing governance required behavioral change at the rep and manager level — not just a new dashboard.
“When a €1B sales org can’t consolidate its own forecast, the operating model is the problem. I built the model — CRM governance across every market, a single forecasting methodology, individual seller analytics, and the ExCo cadence that connected commercial performance to strategic decisions. And when the data revealed a margin decline in one market that leadership wanted to soften in the board deck, I held the line. The number that went into the room was the real one. Twenty-five percent YoY revenue growth, with a commercial infrastructure you could actually explain to a board. That’s what the model was built for.”
Sales Enablement SME — Global Technology Client
At global scale, execution problems are usually structural, not a reflection of the people doing the work. I inherited a 28-person offshore Helpdesk where agents were routing on instinct because no one had designed the system they were supposed to operate — five stakeholder groups, no shared workflow, chronically missed SLAs, and sellers losing selling time to unresolved comp inquiries.
The cost wasn’t measured in tickets. It was measured in seller productivity. Every unresolved comp inquiry kept a rep off the floor. Workflows had grown organically across five stakeholder groups — IT, HR, Technology, Sales, and Compensation — and no one had owned the architecture that connected them. The governance problem was upstream. The seller productivity problem was the consequence.
The agents were capable. The workflows were broken and ungoverned. This was a change management and process design problem — not a staffing or technology problem. Fixing it required redesigning the system, then getting five stakeholder groups to adopt the new model.
“At global scale, execution failures are rarely talent failures. They are architecture failures. The infrastructure governing how 28 agents across time zones routed, escalated, and resolved tickets was the problem. I redesigned it. Resolution time dropped 22 hours. Agents stopped routing on instinct and started routing on process — and sellers spent less time waiting on comp answers and more time selling.”
I’m looking for a full-time Revenue Operations leadership role at a growth-stage or scaling organization where building the infrastructure right is the mandate, not an afterthought.
