You’ve spent 20+ years walking into complex growth environments and building GTM engines from the ground up. What do you see that a conventional CMO might miss?
The growth problem is almost never sitting inside marketing.
When you walk into a business, the reflex is to look at the funnel and ask which campaign is missing. Twenty years in, I've learned the leaks are between the functions, not inside them. The deal that stalls because sales and marketing quietly define a good lead differently. The demand you build for a product that can't be implemented fast enough to keep the promise. The value that gets undersold because nobody agreed the story.
A conventional brief treats marketing as the awareness layer at the top. Our own deal data told me marketing's real leverage sits far deeper in the journey than the top of the funnel. So I stopped trying to optimise my own department and started fixing the handoffs between all of them.
That's the thing I think a conventional CMO can miss. Growth is a system, not a department. My job isn't to run better marketing. It's to make product, sales, pricing, delivery and marketing actually reinforce each other, so a customer gets one clean experience instead of five disconnected ones. Less glamorous. Far more useful.
HR teams are under pressure to do more strategically while still managing a mountain of everyday processes. Where does ELMO take the biggest operational burden off their plate?
The biggest burden isn't any single task. It's the reassembly work.
HR teams spend an extraordinary amount of time moving the same information between systems that don't talk to each other, then stitching it back by hand to answer one simple question from the CEO. Our benchmark research this year found a third of HR teams still gather their metrics manually, and four in ten need manual work just to answer a question from leadership. That's a week eaten before anyone gets to the strategic work they were hired for.
So the burden we take off the plate isn't the pay run or the onboarding checklist on their own. It's the swivel-chair between all of them, and the reconciliation in the middle.
The fix isn't another clever tool on the pile. It's putting workforce, payroll, learning and performance data in one place they can trust, so the answer is already there when leadership asks. Here's the part people underestimate. Adoption of AI was never the hard part for these teams; 93% of Australian HR teams already use it. Getting the foundations right underneath it is the hard part, and that's the burden worth removing.
Payroll is one area where “good enough” simply isn’t good enough. What are the risks you see organisations taking when payroll sits across disconnected systems and processes?
Payroll is the one thing an organisation has to get right every single time. Nobody thanks you for a perfect pay run. They very much notice a wrong one. It's personal; it's someone's mortgage, their weekend, their trust in their employer. "Good enough" has to sit a test almost no other system faces.
When payroll runs across disconnected systems, the risks stack up. Compliance is the sharp one now. Since January 2025, intentionally underpaying staff is a criminal offence in Australia. Honest mistakes aren't captured, but the back-pay bills and civil penalties for errors still bite, and the Fair Work Ombudsman has clawed back well over a billion dollars for workers in recent years. Almost none of the brands in those headlines set out to do the wrong thing. The error crept in through complexity; awards and entitlements that didn't flow cleanly between systems.
The second risk is losing a single version of the truth, so every reconciliation becomes manual detective work, and manual work is where mistakes live. The third is that you can't see a problem coming, because the data that would warn you is scattered across places nobody's looking at together.
The one people underrate is reputation. To your people, a payroll error isn't a finance glitch. It's a signal about whether they can trust you. That's why connecting payroll to the rest of the workforce picture isn't housekeeping. It's risk management.
You’re building a governed, AI-first GTM model at ELMO. How has that forced you to rethink how marketing actually gets done?
It's forced me to admit that the tool is the easy part.
We went all in on AI across the go-to-market team, but governed, not a free-for-all. The first thing that changed is where the effort goes. The old assumption was that AI does most of the work and humans add a light polish. In practice it's the reverse. The technology is maybe a third of the effort. The judgement, the context and the people change are the other two-thirds, and that's the hard part.
Here's the lesson that stuck. We ran a deep analysis of our own deals. The first version gave us a confident, board-ready finding. A later version, with cleaner data, flipped it completely. The AI wasn't wrong; it gave exactly what we asked for. I nearly took the wrong story to my own board, and a person caught it, not a better prompt. AI accelerates conviction, including conviction that's wrong. The fluency of an answer tells you nothing about whether it's true.
So the way marketing gets done has changed. We use AI to draft fast and do the heavy lifting, but a human owns tone, positioning, judgement and the final call. My test for the team is simple. If you could defend a decision with the screen closed, you're still the boss. If you'd have to check with the AI first, the title has quietly moved. Our job now is orchestration and judgement, not output. The machine makes more; the humans have to make it right.
You’ve worked across both PLG and sales-led motions. When does each model work best and where do marketers often get it wrong?
Both work. The mistake is treating them like tribes you belong to rather than tools you choose.
The honest question is never "do I prefer product-led or sales-led." It's "how does this buyer actually make this decision." Product-led works when a person can feel the value before they need to talk to anyone, and when the risk of trying it is low. Sign up, get value, expand. Sales-led works when the purchase is high-stakes, touches a lot of people, and switching costs are real. That's HR and payroll to a tee. You don't rip out the system that pays your people on a free trial and a credit card.
Where marketers get it wrong is bolting a product-led motion onto a product that genuinely needs guidance to land, then wondering why the trials stall. Or the reverse: wrapping a simple, self-serve product in a heavy sales process and adding friction the buyer never wanted.
The other trap is thinking nurture means "email, email, call." Real nurture is intentional help; the right content and conversation at the right moment, moving someone toward being ready, not chasing them through a script. Match the motion to the decision, and be honest about how long and how many people that decision really involves.
AI is changing how buyers discover, research and shortlist vendors. Which part of the traditional marketing playbook would you happily tear up?
The top-of-funnel volume game.
For years the playbook rewarded producing a mountain of generic, search-optimised content and gating it to harvest email addresses. Buyers now start with an AI assistant, not a search bar. They arrive already researched, already shortlisted, having asked a model to compare their options before a vendor even knows they exist. Churning out interchangeable "what is X" content to catch keywords is writing for an audience that's leaving.
So we now write for two audiences: the humans we've always written for, and the models deciding whether to recommend us. The interesting part is what earns the recommendation. When we looked at where AI actually cites us, it was for the same things our customers already value; local compliance, real support, genuine expertise. You don't game your way into an AI recommendation. You earn it the way you earn a human one.
That's the shift I'd make. Stop chasing attention with volume. Earn recommendation with a real point of view, original data and proof only you have. Algorithms change constantly. Reputation compounds. The brand a machine recommends is usually the brand people already trusted.
You’ve spent your career solving hard revenue problems in transformational environments. What’s the one GTM problem you’d challenge every CMO to stop accepting as “just how things work”?
That marketing's job ends the moment it hands a lead to sales.
We've all inherited the relay race. Marketing generates leads, throws them over the wall to sales, sales throws the customer to onboarding, onboarding throws them to success. Information and energy leak at every handoff, and everyone hits their own target while the customer feels the seams. We accept it because that's how the org chart is drawn.
But it doesn't match the evidence. When we studied our own won deals, marketing's hardest and most valuable work wasn't at the top of the funnel. It was near the close, helping get people over the line. If that's true, then measuring marketing purely on leads at the top is measuring the wrong end.
So here's my challenge to every CMO, myself included. Stop accepting the handoff. The buyer doesn't see functions; they see one experience, or a broken one. Our job isn't to run the best marketing leg of the relay. It's to help design one connected go-to-market motion with everyone, product, sales, service and finance, so nobody's dropping the baton. Not because it's tidy. Because that's where the growth actually is. Let's stop optimising the handoffs and start removing them.
