Revenue Operations: How to Build a RevOps Function from Scratch

Revenue operations aligns sales, marketing and customer success under one set of processes, data and metrics. Gartner describes the model as one that breaks down organisational silos and lets organisations operate with greater efficiency. In 2021 it predicted that by 2025, 75% of the highest-growth companies in the world would deploy a RevOps model. That was a forecast, not a measured outcome, and we are not aware of a public Gartner figure confirming the result. It nonetheless captures where leading practice was heading.

The model is relevant to Australia and New Zealand because the market structure makes alignment unusually valuable. Revenue teams are typically smaller than their US counterparts, buying committees are often cross-border, and many companies sell into the region from a head office elsewhere. When each function builds its own spreadsheets and definitions, a small team cannot afford the duplication. A single owner of process, data and reporting recovers capacity that is otherwise lost.

The implication for a Chief Revenue Officer is to treat RevOps as an operating discipline rather than a department. A function can be one person at first. What matters is that someone is accountable for the revenue process end to end, with authority across sales, marketing and customer success, and with a mandate from the CEO to set standards that all three follow.

A practical test of whether a company needs RevOps is how many versions of the truth exist. If the CEO, the CFO and the head of sales each carry a different pipeline figure into the monthly meeting, the company already has a RevOps problem, whatever it calls the function. Smaller companies often feel this most acutely, because a single large deal or departure can change the picture and nobody can say quickly why. The cost is rarely recorded, but it shows up as slow decisions, repeated reconciliation and forecasts that nobody trusts.

Cross-border selling adds further definitional questions. Companies in the region that sell into Asia, the Gulf or the UK face currency differences, multiple legal entities and partner-sourced deals. Decide early how these appear in pipeline, which entity books the revenue and who owns the relationship, so that the first report does not need a footnote for every region.

What to do: write a one-page mandate for revenue operations that names the owner, the decisions they control, such as stage definitions, lead routing and forecast methodology, and the reports they will publish. Have the CEO and heads of sales, marketing and customer success sign it before any hiring or tool selection.

Gartner's 2025 survey of 243 chief sales officers and senior sales leaders, fielded in November and December 2024, found that 49% say their sales organisation's definition of a qualified lead differs greatly from marketing's. Only 45% reported that their organisation met several 2024 strategic goals. An earlier Gartner survey of more than 200 sales leaders, from late 2022, found 62% describing sales and marketing as defining qualified leads differently. The wording and samples differ, so the figures are not a trend, but the problem persists.

Alignment has measurable value. In the same 2023 release Gartner said that sales organisations that align cross-functional KPIs are nearly 3 times more likely to exceed new customer acquisition targets. The statement is a Gartner claim without a stated sample, so it is better read as strong directional support than as a forecast. Yet it matches experience: when teams share definitions, they stop arguing about whose numbers are right and start deciding what to do.

Definitions to settle first are few. What is a marketing-qualified lead, a sales-accepted lead and an opportunity? What evidence is needed to move a deal from one stage to the next? When does a deal count as pipeline, and when as forecast? Who owns the account after a sale? Each should be written as a rule that a new starter can apply and an auditor can test, not as a description of culture.

Finance should be in the room. Revenue recognition, bookings and pipeline are often defined by different people for different purposes, and a RevOps function that ignores finance will build a view of revenue that the CFO cannot reconcile. The simplest safeguard is to agree one bridge from pipeline to bookings to recognised revenue, with a named owner for each step. That bridge becomes the spine of the weekly report and the basis for credible forecasting.

Write definitions as rules, with evidence. A qualified lead might require a named contact with budget authority, a stated need and a defined next step, recorded in specific fields. An opportunity might require a confirmed buying process and a dated decision. A stage change should require evidence, not opinion. When a stage depends on how confident a seller feels, the pipeline total reflects optimism, not probability, and forecasts will swing accordingly.

What to do: run a two-hour workshop with sales, marketing, customer success and finance, with the CRO as sponsor. Agree the definitions, write them into the CRM as required fields and picklists, and publish a data dictionary. Re-baseline the last four quarters of pipeline and conversion against the new rules, so that the first reports are comparable.

Bain's 2025 survey of more than 1,200 senior commercial executives across 18 industries found that more than 80% claim to run structured, repeatable sales and marketing activities, yet 70% do not effectively integrate their sales plays into their technology, and only about 20% have realised full value from revenue technology. The gap between process and system is where much of the waste sits. Companies believe they have a process, but the tools do not reflect it.

The Salesforce State of Sales report, a vendor survey of 4,050 sales professionals in August and September 2025 that included 250 in Australia and 100 in New Zealand, points the same way. Only a third of teams use an all-in-one platform, and the rest use an average of eight standalone tools. Reps spend more than half their time on non-selling work. These results are global, not ANZ-specific, and come from a vendor with a product to sell, so we use them as indicative.

The implication is that adding another platform is rarely the highest-value move. A better first step is to map how a lead becomes revenue today, tool by tool and hand-off by hand-off, and to find where data is re-keyed, lost or contradicted. The gaps will usually be in lead routing, stage progression, ownership changes at handover and the link between marketing activity and closed revenue. These are process and integration problems, not licence problems.

Integration has a cost dimension too. Every additional tool adds licences, training, interfaces and another place where a record can be wrong. Salesforce's finding that teams without an all-in-one platform average eight standalone tools illustrates the scale of the problem. Consolidation is not always the answer, because specialist tools can be the right choice, but each tool should have an owner, a purpose and a place on the process map.

What to do: produce a single-page map of the revenue process and the systems that touch it. For each hand-off, record the owner, the data passed and the failure rate. Fix the three worst before purchasing anything new, and use the map to challenge any request for another tool.

A RevOps function is often built from a sales operations team that is already overstretched. Gartner's survey of 318 sales leaders, fielded in August and September 2022, found that sales operations professionals dedicate 73% of their time to supporting non-sales functions, up from 39% in 2019. In 2022 only 27% of support time went to the sales function itself, down from 61% in 2019. The scope of the role has expanded far beyond pipeline support.

The same pressure affects sellers. Gartner's 2023 survey of 501 sellers found that 77% struggle to complete their assigned tasks efficiently. The Salesforce 2025 data find that more than half of rep time goes to non-selling work such as data entry and prospecting. Where operational capacity is scarce, the burden falls on the people who should be selling, and data quality suffers because those people have little time or incentive to maintain it.

For a company building RevOps from nothing, the lesson is to define the scope and protect it. If the new function becomes a service desk for every system request in the company, it will not deliver revenue improvement. The mandate should state what revenue operations will not do, such as general IT support, finance reporting unrelated to pipeline, or ad hoc analysis for other departments, and should route those requests elsewhere.

Prioritise ruthlessly. A new RevOps function will receive requests from every direction, so agree a simple scoring approach: expected effect on revenue, number of people affected, effort to deliver and risk if delayed. Publish the backlog and review it fortnightly with the heads of sales, marketing and customer success. Visible prioritisation keeps the function credible and shows stakeholders why their request sits behind a more valuable one.

The cost of overload is also visible in morale and retention. Operations staff asked to serve every function tend to move to roles with clearer remits, taking system knowledge with them. A written mandate, a published backlog and a regular review of capacity are therefore as much about protecting the people as about protecting the process. Document the critical configurations, too, so that the function does not depend on one individual's memory.

What to do: set a capacity plan for the function. Allocate time between four categories: process and definitions, data quality, reporting and forecasting, and enablement. Review the allocation quarterly, and decline work that falls outside the mandate. Track the proportion of seller time freed for selling as an early success measure.

Technology adoption in the region varies sharply by company size. The Australian Bureau of Statistics reports that around 12% of Australian businesses used AI in 2024-25, but around 35% of large businesses, 22% of medium-sized businesses and about 11% of small and micro businesses did so. Large firms have moved from 9% in 2021-22. The figures concern AI, not RevOps, but they indicate how unevenly advanced tools reach smaller firms.

We found no robust, public ANZ-specific benchmark for RevOps maturity, and we would be wary of any that claim precision. The Salesforce survey included 350 respondents in the two countries but reported mainly global results. What the data support is a general principle: smaller and mid-sized firms do not have the specialist capacity of a large enterprise, so they should choose simplicity, buy fewer tools and write definitions that a small team can maintain.

In practice that suggests a lean structure. At the smaller end, one RevOps lead who owns definitions, the CRM and weekly reporting may be enough, supported by an adviser or contractor for specialist configuration. As the company grows, add analyst capacity for forecasting and a systems administrator before adding another layer of management. Resist the temptation to copy the structure of a US enterprise, which assumes depth of resources that few ANZ mid-market firms have.

Talent is the other practical constraint. RevOps blends process design, data analysis, systems configuration and influence, and people who combine all four are scarce. Hire for judgement and influence first and technical depth second, and use contractors for configuration peaks. A RevOps lead who cannot persuade a senior sales director to follow a definition will fail regardless of technical skill, and in a small team that failure is quickly visible.

Where specialist help is needed, buy it for a defined task and a defined end date. Configuration of a CRM, a data migration or the design of a forecast model are good candidates. Ongoing ownership of definitions, priorities and reporting is not, and should stay in the company. That division keeps the cost proportionate while ensuring the knowledge accumulates inside the business, where it will be needed when people change and the company grows.

What to do: size the function to the revenue it supports. Start with a single accountable lead, a part-time administrator and clear external support. Set a review point after six months to decide whether to add capacity, using measures such as forecast accuracy, lead response time and the share of pipeline with complete data.

A useful design principle is to build around the flows that matter, not around departments. The first flow is pipeline: how leads become opportunities and opportunities become revenue, with defined stages, entry and exit criteria and conversion measures. The second is hand-offs: marketing to sales, sales to customer success, and customer success back to sales for renewal and expansion. The third is forecast: how pipeline translates into a number the business can plan against.

Each flow needs a rule set and an owner. For pipeline, the rules are stage definitions and required fields. For hand-offs, they are routing logic, response-time standards and acceptance criteria. For forecast, they are the method, the cadence and the treatment of risk, such as how aged opportunities are discounted. When each rule is written, tested against the last four quarters and enforced in the system, the function can then improve rather than argue.

Only after this should technology be considered. Bain finds that 70% of companies fail to integrate sales plays into their tools, which suggests that most already own capability they have not configured. Review what the existing CRM can do before replacing it. If you do change systems, migrate definitions and clean data first, so that the new platform inherits a working process and not the old one's confusion.

Compensation is where definitions meet behaviour. If sellers are paid on bookings and marketing on lead volume, the definitions on paper will be overridden by incentives in practice. Review how targets, quotas and bonuses reflect the agreed stages and conversion measures, and align them where they conflict. Changes to compensation need legal and human resources input, so plan them for the start of a new period rather than mid-year.

Many first builds also stop at the point of sale. Hand-offs from sales to customer success, and back for renewal and expansion, carry as much revenue as the front end. Define what the seller must pass on, such as goals, stakeholders and commitments, what customer success owns, and the trigger that returns an account to sales. Align retention and expansion with the pipeline stages, so the whole lifecycle appears in one report.

What to do over the first 90 days: weeks one to three, agree definitions and publish the data dictionary; weeks four to six, clean the data and fix the worst hand-offs; weeks seven to nine, implement a weekly pipeline and forecast report from one source; weeks ten to twelve, review results and decide on technology changes. Each stage ends with a sign-off by the CRO and CFO.

A RevOps function should be judged on outcomes the business cares about, not on activity. Useful measures include forecast accuracy against actuals, conversion between stages, sales cycle length, pipeline coverage, the share of opportunities with complete data and the time sellers spend selling. Customer measures such as net revenue retention belong in the same view. Publish them weekly, and review them with the CEO monthly.

AI raises a governance question that RevOps is well placed to answer. Gartner's 2025 survey finds that only 23% of chief sales officers are accountable for AI selection, while 68% only provide inputs or are informed. Salesforce reports that high performers are 1.7x more likely than underperformers to use prospecting agents. If AI tools are chosen elsewhere in the company, revenue teams risk automating a process that nobody has defined.

Gartner also reports that 74% of CSOs say seller skills must change significantly to meet future revenue goals. RevOps can support that change by providing clean data, consistent playbooks and measurement of what works. That is an argument for putting definitions, data and enablement in the same function rather than scattering them. It also means that every AI initiative in the revenue process should have a named owner, a baseline and a test.

Finally, set expectations for time to value. Definitions and data cleaning can show results within a quarter, in the form of a trusted pipeline number and fewer disputes. Forecast accuracy and conversion improvements take longer, typically several quarters, because they depend on enough cycles of consistent data. Tell the board this at the outset so the function is not judged on a number it cannot yet move, and agree the milestones against which progress will be reviewed.

What to do: set five outcome measures for the function in its first year and report them to the board. Make RevOps the owner of AI use cases within the revenue process, with a simple approval route: business case, data check, pilot against a control and a review date. Revisit the structure after twelve months, once the first results are in.

Karter McKinley helps revenue leaders write the mandate, definitions and data dictionary that a first RevOps function needs, and can support the 90-day build alongside your sales, marketing and customer success teams. Our commercial growth and sales execution work is focused on measurable pipeline and forecast quality, and on using the systems you already own before adding new ones.