Stop Burning Cash: Fix your RevOps in 2026

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Most SaaS founders unintentionally throw money away, not because their tools are bad, but because of broken RevOps foundations and misaligned teams. In this practical webinar, AllDemand co-founders Eva McCann and Sam McCann team up with Toby Sharp (Head of Revenue Operations at Comply Pro) to get candid about expensive mistakes they see daily in New Zealand SaaS.

Key themes:

1. The Illusion of Maturity
Most companies look mature: they have HubSpot, call recorders, someone with RevOps in their title and polished dashboards. But leadership tells a different story: growth feels unpredictable, forecasts swing wildly, every quarter ends in a scramble. This is the "illusion of maturity" - visibility without control. Underneath sits "operations debt," accumulating when you scale faster than your operating systems. As Toby observes: "Growth at all costs isn't just gone, but AI is raising the bar even further."

2. Cash Leak #1: Strategy on Paper, Behavior in Chaos
On paper, you have clear pipeline stages and service level agreements (SLA). In reality, reps keep deals alive to make numbers look good, marketing assumes leads are followed up when they're not. Leaders call this a "discipline problem," but it's a design problem. The solution: nudge theory (make the right behavior the easiest behavior). Eva's example: a business recorded meetings but updates remained manual. They turned on AI-enabled meeting intelligence with a 10-point checklist running automatically, scoring 0-10 and updating HubSpot properties. Result: less admin time, more accurate inputs and better forecast accuracy because deal quality was measured, not guessed.

3. Cash Leak #2: Pretty Dashboards on Rotten Data
Underneath polished dashboards sit duplicates, wrong buying committee roles and churned customers still tagged active. The blunt reality: AI doesn't fix dirty data, it accelerates bad decisions. AllDemand's approach: (1) Expose the rot (2) Stabilise continuously using deduplication engines (3) Be strategic when spending money on data enrichment; look for signals of pain and readiness to buy, not just basic company facts.

4. Cash Leak #3: Gold Unused in Meeting Recordings
If no one aggregates patterns from recordings and pushes them into systems, you've built an expensive podcast archive. Modern teams treat calls as datasets by tracking pricing pushback, feature gaps, churn risk, feeding these into messaging and product. For every closed-won deal, create an onboarding dossier capturing roles, pain and success definition. Toby's example: Comply Pro captures goals from calls, uses AI to map to features, produces proposals automatically (taking 30-60 minutes down to 10). At 70 deals monthly, that adds up fast.

5. Cash Leak #4: Quote-to-Cash Chaos
When quote-to-cash is messy, you burn cash three ways: margin leak (too many SKUs, inconsistent discounting), timing leak (approvals pushing deals to next quarter), trust leak (billing errors becoming credits). Solution: shrink SKU catalog, standardise discount ranges with approval rules, lock critical value properties flowing from CRM to quoting tools and finance.

6. The Operating Rhythm That Prevents Drift
AllDemand's embedded RevOps loop: weekly operational stand-ups reviewing SLA breaches and stuck deals; Monthly GTM Leadership Council deciding what ships next; Quarterly foundation audits checking if lifecycle stages are still valid. Toby's rhythm at Comply Pro adds daily triage and monthly all-hands. "These layers sound simple, but they stop our system from sliding back into random acts of improvement."

7. RevOps as Product Team, Not Help Desk
Old model: ticket desk. Modern model: product management for revenue engine. Work in timeboxed sprints with a single backlog prioritised by revenue impact. 

8. The Foundation Pyramid: Clean → Accountable → AI-Ready
Base (Clean): data you trust, segments based on pain evidence, lifecycle reflecting reality. Middle (Accountable): operating rhythm, distributed ownership, backlog sprint process. Top (AI-Ready): only when the first two are solid do you enrich data, suggest actions, trigger workflows (inside guardrails). Jump to AI without the foundations and it's wasted.

Key takeaways:

  • Diagnose which cash leak costs you most: strategy/behavior mismatch, rotten data, unused call intelligence, or quote-to-cash chaos

  • Design systems where right behavior is easiest: use AI meeting intelligence to automate updates and eliminate cognitive load

  • Stabilise data continuously: dedupe engines run constantly; enrich event-driven data with pain-qualified signals

  • Treat calls as datasets: create onboarding dossiers that travel to customer success so context doesn't die at handover

  • Establish embedded RevOps rhythm: weekly stand-ups, monthly councils and quarterly audits prevent drift

  • Run RevOps as product team: timeboxed sprints and a single backlog to balance big rocks with small wins

  • Build the pyramid in order: clean first, then accountable, only then the foundations are laid will you be AI-ready.

Watch the full discussion below for detailed workflow examples, tool recommendations, and the reality that even companies doing hundreds of millions in ARR wrestle with these same core principles.

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