It's a pattern I keep seeing across organisations. Not a lack of effort. Not a lack of tools. Especially not a lack of tools, because most organisations already have more of those than they know what to do with. It's not even a lack of strategy. It is a quiet, persistent friction that shows up everywhere. And over time, it compounds.
On client projects, it usually looks like this:
- Duplicated data entry
- Disconnected systems
- Manual workarounds
- Spreadsheets quietly doing the job of middleware between platforms
- "We'll fix that later" processes that somehow become permanent
None of it shows up on a balance sheet. All of it adds up.
Productivity Isn't Being Designed. It's Being Held Together.
On paper, everything looks fine. Teams are busy. Projects are moving. Systems are in place. But zoom in, and productivity isn't being designed. It's being held together.
People switch between five and ten systems to finish a single task. They re-enter the same information twice, sometimes three times. They lean on a spreadsheet to bridge a gap that should never have existed, and chase an update that was meant to be automatic.
And it's more widespread than most leaders assume. MuleSoft's 2026 Connectivity Benchmark, a survey of more than 1,000 IT leaders, found the average organisation now runs around 957 applications, and only 27% of them are connected. Most of the friction your teams feel every day lives in the gaps between those systems.
Where Automation Actually Fits
Automation isn't (always) about replacing people, and it isn't about automating everything you can find. It's about removing the repetitive, low-value, frankly frustrating friction that stops good people from doing their best work.
When I start with an organisation, the first question isn't "What can we automate?" It's "Where is work breaking down, and why hasn't anyone been able to fix it?" That second question matters. Sometimes the answer is technical. Just as often it's human: the process never got fixed because the tools to fix it were too clunky, too slow, or too far from how people actually work, so the friction simply became accepted as part of the job.
This is also why investments in new technology don't always deliver the value people expect. I've seen organisations invest heavily in new platforms, automation tools, and AI capabilities, only to find that the work still feels just as hard six, twelve, or even eighteen months later. In most cases, the technology isn't the problem. It's the order things were done in.
Three patterns come up again and again.
The expectation is that the capability will somehow reveal the use case. It rarely works that way. The most successful automation and AI initiatives start with a business problem worth solving, not a platform looking for a purpose.
Automation gets handed to IT to build, while the people who own the work remain consulted rather than accountable. The result is often technically sound automation layered over a process that was never redesigned. The work moves faster, but it's still the same work.
Bots are deployed, integrations are completed, dashboards are built. They're all important milestones, but they're not the outcome. The measures that really matter, cycle time, error reduction, customer experience, hours returned to people, often receive far less attention.
The common thread is simple. Automation is often treated as a technology decision, when it's really a decision about how work should flow. Connect the systems, deploy the bots, and if the underlying process is still a mess, all you've done is help it fail faster.
