What Consulting Pattern-Recognition Brings to PMS

1. You spent nearly nine years in strategy consulting, parachuting into banking turnarounds, insurer integrations and pharma transformation offices you’d never worked in before, then learning the specifics fast enough to redesign them. How much of that pattern-recognition skill actually transfers to an industry as operationally specific as vacation rental management, where you have no prior track record?

The specifics don’t transfer, though some of it is common to any business. I’ve never run a channel manager, and there are people at ICNEA with twenty years in this industry who don’t need me explaining their own product to them.

But that was never the job in consulting either. What you actually learn walking into a bank, an insurer or a pharma company you’d never seen before is how to get up to speed fast enough to be useful to people who have spent their careers there: how to read a business, separate symptoms from causes, build your own judgement quickly, and then get things moving. That’s method rather than sector knowledge, and it travels. It’s the most transferable thing I have, and I’d say it’s an advantage rather than a handicap.

The other half is that I’m not starting from zero here. I’ve been a landlord using this kind of software, and I’ve spent the last stretch building my own. I come at this from the customer’s side rather than the vendor’s, which is a real starting point even if it isn’t the same as operating experience.

What I try to be careful about is not confusing speed with understanding. So the first three months are mostly listening — clients, clients who left, the team — with the explicit aim of finding out which of my starting assumptions are wrong. A fresh perspective is only worth something if you let it be corrected.

2. You are currently bootstrapping InMio, your own property management software, born out of your personal frustration as a landlord. Stepping into Icnea as COO means leading a much larger, more established player solving an adjacent problem. What have you learned building your own product from scratch that you expect to directly shape how you run Icnea, and where do you draw the line between the two?

The line first, because it’s simple: InMio is a personal project and it isn’t a competitor to ICNEA. It came out of managing my own property portfolio, on the long-stay side, for small non-professional owners. It’s B2C. ICNEA is B2B, professional managers running short-stay operations who need a PMS and a channel manager to run a business. Different customer, different problem, different logic. I raised it before joining rather than waiting for anyone to ask, and I’ll keep building it in my own time.

I built it for three reasons. It solved a problem I actually had. It gave me a real use case for applying AI rather than talking about it in the abstract, which I think matters more than any certificate. And I wanted a new challenge, and building something myself was one of the ways that could go. When I showed it to people around me a few asked to be told if I ever commercialised it, which is flattering but it’s still a side project, not a company.

What carries over is mostly commercial. Onboarding is where you win or lose people; a small owner gives up at the first confusing screen or the first import that fails quietly. Distribution is harder than building, which almost everyone who starts from the product underestimates. And you learn what a feature really costs once you’re the one maintaining it.

The B2C/B2B contrast is honestly part of what attracted me here. B2B has more room in it.

3. Your mandate at Icnea explicitly includes promoting AI as a competitive advantage, and you were leading AI adoption at Signature Management Consultants, alongside AI fluency and Claude-specific certifications. Concretely, what does an AI-driven transformation look like for a 25-year-old PMS built for small and mid-size operators, as opposed to the AI narrative you’d pitch to a bank or an insurer?

The difference starts with who you’re talking to. In a bank the conversation runs through committees, governance and model risk, and the pitch is largely about control and operational efficiency at scale. Our customer is someone running forty apartments with no IT department and no appetite for a transformation programme. For them it’s about ease of use, speed and taking work off their plate. If AI arrives as one more feature to learn, it won’t get used.

In practice I see three layers, in this order.

Data first, and it’s the least glamorous part. Twenty-five years of product means plenty of data, but data built to run operations rather than to be analysed. Until that’s usable, everything else is a demo.

Then internal productivity: support triage, faster onboarding, AI-assisted development. I use these tools daily myself, which helps in judging what they do and don’t do well.

Then the product, which is where it matters most for our clients — multilingual listing content, drafting guest messages, checking and reconciling channel connections, flagging anomalies before the client has to call us about them.

The direction over time is that the PMS stops being a system you operate and becomes closer to an assistant that helps you run the business. For a manager with fifteen properties, four hours back a week is a real result. Nobody is going to ask which model it runs on.

4. Your consulting work has been defined by hard financial discipline: identifying tens of millions in cost-out, engineering break-evens, designing target operating models with strict governance. How does that cost-control, metrics-first instinct sit alongside running a company whose customers are largely small, resource-constrained property managers rather than large financial institutions?

I’d frame it less as cost control and more as rigour. Systematisation, professionalisation, doing things the same way twice. A good part of my job here is designing processes that work well enough that the company can grow without adding people at the same rate. That’s where the consulting background earns its keep, and it has very little to do with cutting.

It also happens that a lot of the cost in a business like ours is self-inflicted. A support ticket usually has a cause: a fragile integration, a screen nobody understands, an onboarding step that got skipped. Removing the cause is cheaper than handling the ticket well, and the client is better off either way.

Where I have to watch myself is the consulting reflex. In a company this old with customers this loyal, some of what looks inefficient on a spreadsheet is exactly why people stay — support answered by a person, availability, patience with clients who aren’t software buyers by trade. In this market people leave because something is annoying, not because it’s expensive.

And the metrics should point outwards, not only inwards. Where I’d like this to end up is ICNEA being less a tool our clients use and more a partner in their growth: helping them see where their revenue comes from, where it doesn’t, and what to do about it. That’s a direction rather than a plan — I’ve been here three days. But it’s the one I’d like us to take.