Richard mahoney, associate partner - argon & co
Tell us who you are.
I’m an intralogistics projects professional. I came to warehousing from an engineering background, so I place a strong emphasis on planning, design, and execution. In 2019, I left a career in large-scale consulting to found Studio Logistic, a boutique DC design firm. I felt the industry needed a more specialist capability to help deliver truly high-performance distribution centres.
I had seen a long series of “fast rather than good” projects that produced generic, average facilities, functional, but falling well short of their potential. I believed that with the right tools, discipline, and expertise, that opportunity could be captured, and real performance unlocked. So I founded a company to help companies do that.
Today, I’m an Associate Partner at Argon & Co, where I lead our intralogistics and warehousing capability in New Zealand. Our team focuses on large-scale warehousing development, automation strategy, and operational transformation across manufacturing, FMCG, retail, and primary industries. I spend much of my time alongside our teams in live projects, helping clients make high-confidence decisions on complex capital investments, particularly where automation, buildings, systems, and people intersect.
What is your primary market in ANZ?
Our primary market is medium to large operators across Australia and New Zealand running complex distribution, manufacturing, or fulfilment networks. This includes food and beverage, dairy, FMCG, retail, healthcare, and third-party logistics providers—particularly organisations managing growth, labour constraints, or step-change increases in service expectations.
What is the most significant macro-level shift or challenge currently driving customer investment?
There are two dominant challenges. The first is rising service level expectations around delivery speed and accuracy. The second is the changing nature and availability of the workforce.
Higher service expectations require fulfilment models with speed but also very high availability and reliability. This requires systems, and systems that get it right quickly and consistently, supported by excellent operational execution.
This has driven increased investment in systemisation, while also creating tension between maintaining flexibility and introducing the standardisation required to make those systems effective.
Labour-centric solutions remain viable and appropriate in many contexts. However, where there is material risk around the availability or consistency of skilled labour, we are seeing a clear shift toward automation. In those cases, business cases are increasingly being driven by risk mitigation and resilience, rather than by financial return.
How does your company help them to overcome it?
In short, we place significant emphasis on requirements definition, planning, and design as the foundations of successful delivery. We advocate a “plan slow, act fast” approach.
All major change programmes begin with strategic intent. What differentiates outcomes is the ability to translate that intent into a credible, executable plan. A critical part of that process is bringing stakeholders along early, so the plan is not only technically robust, but also broadly owned by the organisation.
Many projects struggle to realise the benefits not because the design is weak, but because the organisation is not aligned to deliver it. Investing time upfront to address this typically saves months, sometimes years, during delivery and stabilisation.
How is your company deploying or preparing for the integration of AI-driven solutions in industrial automation?
We see AI primarily as an enabler that improves decision quality and system performance, rather than a wholesale replacement for people. Iris (an Argon & Co subsidiary) is doing great work in AI application development along these lines.
While some roles will undoubtedly change, particularly in areas like manual data processing, I see the near term impact in industrial environments is most likely augmentation. AI will make people both more capable and more productive.
I am particularly interested in the evolution of AI-enabled vision systems and true edge processing, where intelligence sits directly on devices rather than relying on centralised cloud infrastructure. This has the potential to unlock new use cases on the warehouse floor for both people and automation. It’s an exciting time!
Beyond existing product roadmaps, what transformative technology or concept will have the greatest disruptive impact in the next five years?
The concept of cross-platform, distributed control is particularly compelling.
Today, most warehouse management and execution environments rely on centralised orchestration, which typically drives a single-vendor approach within a DC. A more distributed control model could enable modular, best-of-breed technology selection and far greater adaptability over time.
If realised effectively, this would materially reduce lock-in, improve resilience, and allow facilities to evolve more easily as volumes, channels, and technologies change.
How does your company culture support innovation and adaptability?
We develop performance-based solutions from first principles. This allows us to pursue the best solution for each specific context, rather than defaulting to pre-built approaches that are quick to develop but not always a perfect fit.
Because we are independent and vendor-agnostic, we can focus on what will genuinely work in practice. Innovation is encouraged, but it must also be deliverable. The ability to manage risk and bring ideas into operational reality is what ultimately matters.
What strategies have you found most effective in attracting and retaining top talent?
Do great work, and then keep doing great work.
The intralogistics sector in ANZ is relatively small, and strong practitioners want to work on challenging, meaningful projects alongside capable peers. Providing opportunities to work on challenging projects, with opportunities to learn from experienced leaders has proven to be the most effective long-term strategy.
What's your long-term vision for the role of automation in your sector?
While I am a strong advocate for automation, I’m a humanist first. I believe automation should make people’s work better, particularly by improving productivity and reducing unnecessary friction in industrial roles. That productivity gain is what ultimately supports higher living standards over time.
As the nature of work continues to evolve, my expectation is that automation will both improve job quality and enable higher-performing supply chains. If it doesn’t achieve both outcomes, it is unlikely to be sustainable or widely adopted.
What is the most important principle that guides your decision-making and long-term planning?
I have three.
First, clarity of objectives, particularly how success will be measured, is critical. When objectives are clear, decisions tend to become far easier and more consistent. This can take time to develop, and most people think they’ve locked this down before they really have.
Second, “plan slow and act fast” is far preferable to planning quickly and then spending years fixing avoidable problems.
Third, evidence matters. Decisions based on opinion have their place, but pressure-testing assumptions and understanding how robust the underlying evidence really is remains one of the most effective ways to prevent poor outcomes.
What's one thing you know now that you wish you'd known when you first started in this field?
That no design is ever truly finished. Only good enough.
Real world design must be based on at least some assumptions anyway, so tying yourself in knots trying to perfect a design based on imperfect information is not a recipe for happiness!
Knowing when a design is good enough to call it good, and then move into execution and actively manage change is really important to strike the balance between quality and efficiency.
