Jon Dodkins

Head of Technical Solutions

Jon Dodkins is Head of Technical Solutions. With over two decades experience in tech, with recent work focusing on platform strategy, cloud, developer experience and DevOps, Jon has a track record of scaling software, teams, and organisations.


In 2013, Target launched its expansion into Canada with big expectations and big investment, over $2 billion across 133 stores. A key part of the plan was a state-of-the-art inventory and supply chain system, designed to automatically keep shelves stocked and logistics humming.

But behind the scenes, the system was quietly unravelling…

Product dimensions were wrong. Shelves were too small. Stock data was patchy at best. The automated systems did their job, they just did it with bad data and untested assumptions. Customers walked into bright, shiny stores… and found empty shelves.

Within two years, Target pulled out of Canada entirely. Why had one of the world’s best-known retailers failed? It wasn’t for lack of the latest technology. In simple terms, they’d tried to automate without first understanding, and preparing, the system they were automating.

Zooming Out Before You Speed Up

This story is a warning to every business tempted by the promises of any new shiny technology, including automation and AI. We should all strive for greater efficiency and it’s easy to get swept up in the buzz: faster workflows, smarter decisions, leaner operations. But there’s a crucial step that often gets skipped: understanding the system first.

Most organisations aren’t broken because of a lack of automation or AI. They’re struggling because their underlying systems: processes, data structures, team responsibilities are complex, fragile, and full of blind spots. These are the foundations needed for any tech strategy to work.

And what happens when you apply automation or AI on top of those broken systems? You don’t fix the problem – you amplify it.

The Speed Trap

We see this all the time. An organisation wants to speed up approvals, automate reporting, implement AI or digitise customer onboarding. The instinct is to reach for tools: low-code platforms, robotic process automation bots, cloud APIs, AI integrations. And yes, these tools are powerful. But when used without a clear understanding of how the business actually functions end to end, they create the illusion of progress. Suddenly approvals are flying through faster, only to hit a backlog in finance. AI models spit out insights, but based on incomplete or dirty data. Reports are automated, but no one trusts the numbers.

All that investment, and nothing really changes – except now the system is even harder to debug. (This is classically the moment when a leader moves on, leaving the mess to their successor.)

But all this is what happens when you optimise in isolation, without considering how the system flows, how the data moves, or where the real bottlenecks lie.

The Phoenix Project is a bestselling business novel that uses storytelling to explore the challenges of modern IT, operations, and digital transformation. In the book, this exact mistake plays out painfully: teams rush to deliver features, fix incidents, and automate tasks – but nothing improves because the organisation doesn’t understand where the real constraints are. It’s only when they step back, identify the bottlenecks, and view the business as a system – not a collection of silos – that progress finally starts to stick.

Is Your Business Ready for AI? Start with the System

Here’s the hard truth about AI: you can’t bolt AI onto chaos and expect clarity. You can’t automate dysfunction and expect efficiency.

The pressure to adopt AI is enormous – boards are asking for it, competitors are doing it, headlines are full of it. But in the rush, many leaders overlook the less glamorous, more difficult work: auditing the data estate, understanding legacy constraints, untangling process spaghetti, and designing for the future, not the past.

That’s where Systems Thinking is your friend. It’s not a buzzword. It’s a discipline. A way of stepping back to see the whole picture: how work flows, where delays occur, where feedback loops exist (or don’t), and what unintended consequences are lurking beneath the surface.

One of the best explorations of this is Donella Meadows’ Thinking in Systems, where she reminds us that systems behave in ways we don’t always expect and go against our intuitions – and that lasting change only comes from understanding, and mapping, the patterns beneath the surface rather than simply reacting to symptoms

The Right Technology Needs the Right Foundations

I’m sounding rather grumpy here, aren’t I? Let me be really clear: new technology can absolutely transform your business – though you may need help in understanding your own context, building a strategy and getting the prerequisite ducks in a row.

Here’s what that might mean in practice:

  • Your data needs to be clean, reliable, and well-understood.
  • Your architecture needs to be suitably scalable for your needs, as decoupled as possible, and observable.
  • Your people need to understand not just how tools work, but how the business works as a system.

And it’s these areas where many companies need help.

You don’t need just developers or automation tools – you need experienced architects, transformation partners, and system thinkers. People who can guide you through the chaos and help you build a roadmap that aligns technology with real outcomes.

Don’t Build a Faster Mess

There’s a famous quote by Peter Drucker:

There is nothing so useless as doing efficiently that which should not be done at all.

Automation done wrong is exactly that, a faster mess. A high-speed version of a broken system.

If your data is untrustworthy, if your processes are poorly understood, if your systems are rigid and siloed, then automation will only get you to the wrong destination faster.

But if you start with clarity – about the system, the constraints, the flow of work, and bring in the right expertise to design for flexibility and scale, then automation and AI become game-changers.

Final Thoughts

And my word, how the game can change.

Automation, at its most basic level, is a time saver. But when it’s built on solid foundations: clean data, well-designed processes, and thoughtful system architecture – it becomes something far more powerful. It becomes a launchpad.

This is when the real magic starts to happen:

  • You stop reacting to problems and start anticipating them.
  • AI doesn’t just analyse; it augments your decision-making.
  • Integration isn’t a painful retrofit; it’s an engine for new value streams.
  • Your people stop battling systems, and start using them to do their best work.

With the right foundations in place, you unlock possibilities:

  • Hyper-personalised customer experiences
  • Real-time insight that drives smarter strategy
  • Seamless collaboration across teams and ecosystems
  • Freedom to adopt emerging technologies without fear of collapse

You go from tinkering with tools to genuinely transforming how your business operates. That future isn’t reserved for the tech elite. It’s available to anyone who chooses to zoom out, see the system, and build with intention.

So, take the time. Do the groundwork. Because the step-change you’re looking for? It doesn’t start with a tool. It starts with the system.

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