Are humans the problem or answer to bridging the digital divide?
25 June 2026 
In engineering, obsolescence is usually associated with parts, platforms and systems. Yet in a world increasingly focused on digitalisation, Kate Houlden of Like Technologies argues that realising the value of long-term human experience could be a solution in plain sight.
For much of the past twenty years or so, the direction of engineering has been ever-increased digitalisation. IIoT, connected assets, predictive analytics and autonomous systems have long promised a more efficient, more visible, more controllable industrial environment.
In this vision – now brought right up to the fore with the emergence of AI – knowledge becomes something to be captured, structured, and surfaced through systems. Total automation is almost assumed to be the ultimate goal across almost all industry forward-thinking and ambition.
Yet in actuality, the picture is less straightforward. Across sectors, many organisations find themselves caught between the aspiration of seamless digital integration, and the persistence of work that resists being neatly captured or codified.
When systems meet the real world
Engineering environments are rarely as orderly as the models used to design them. Legacy assets coexist with modern systems. Processes evolve. Constraints change. Factors from outside the production plant come into play. And, at the heart of the matter, it’s people who adapt.
The recently published ERIKS MRO Supply Chain Report offers a useful window into this reality. Its findings suggest that, in many organisations, formal systems struggle to fully reflect operational practice. In some cases, controls and data are described as “incomplete” or even “useless” when set against what actually happens day-to-day.
One telling example is the report’s reference to the widespread use of so-called “squirrel stores”. According to the report, more than half of engineers surveyed admitted to maintaining these informal “secret” caches of spare parts kept outside official inventory systems, because they never fully trust the reliability of the supply chain system.
From a purist systems perspective, this is would seem to be evidence of a failure. Systematically, it undermines visibility, distorts data, and introduces inefficiency. But from an operational perspective, is it so bad – if it works?
These behaviours do not emerge for no reason. They arise in response to real-world pressures: delays in procurement, uncertainty in availability, and the very real cost of downtime. In that context, holding a private cache of critical components is not irrational. It’s arguably just pragmatic, in a very human way.
Rather than viewing such practices purely as problems to be eliminated, they can be read as signals: evidence of where systems do not yet align with the realities of work.
The value that isn’t on the dashboard
This misalignment points to a deeper issue that not all engineering value is easily captured.
Much of what keeps systems running effectively depends on forms of knowledge that are built through experience, shaped by context, applied through judgement.
The ERIKS report above also acknowledges that significant value within engineering functions remains “dependent on the individual employee” – an organic contribution that sits outside formal structures.
This creates an often-invisible tension within digitalisation efforts. On the one hand, organisations seek to externalise knowledge, embedding it into systems where it can be standardised and scaled. On the other, they remain reliant on expertise that is inherently difficult to formalise.
It is here that the idea of the quest for some kind of “digital absoluteness” starts to look like a mission with no end.
Sometimes – in the real world – the most critical insights are those that emerge from experience that cannot be logged digitally. “It’s making a funny noise”. “That looks wrong”. Even, “what’s that smell?”
Anyone who watched the recent Channel 4 docu-drama Dirty Business, which focused on the perils of off-site monitoring in the utilities industry, will understand the sight of an engineer knee-deep in sewage on the phone to headquarters as they tell him the readings say everything is fine.
The risk of optimising for the wrong thing
None of this is to diminish the value of digital tools. Connected systems, real-time monitoring and predictive analytics have transformed many aspects of engineering for the better.
But problems arise when digitalisation becomes an end in itself. When success is defined by the extent to which human involvement is reduced, rather than by how effectively systems and people work together, the persistence of informal practices, workarounds and locally held knowledge is often treated as a barrier to progress, rather than a recognition that humans still have value in the wider process.
Reframing the human role
The challenge of restoring value in human eyes-and-ears insight, however, comes from the growing difficulty of recruiting and retaining experienced engineers, and the disproportionate impact when that knowledge is lost.
What if, instead of viewing the human element as a source of variability to be controlled, it were seen as a source of resilience? A thing of real value.
In practice, experienced engineers do more than execute tasks. They interpret incomplete information, adapt to unexpected conditions, bridge gaps between systems, and make decisions where rules fall short.
These are not residual functions awaiting automation. They are core to how engineering operates in the real world. The most effective organisations are not those that pursue digital absolutes, but those that integrate digital tools with human capability, using technology to support judgement, not replace it.
Bridging the divide
The “digital divide” in engineering is often framed as a gap between analogue and digital. In practice, it is better understood as a gap between expectation and reality. Digital systems promise visibility and control. Human expertise provides context and adaptability.
Bringing those two elements together means recognising that engineering has always been, and is likely to remain, a fundamentally human activity – enhanced by technology, but not defined by it. In fundamentally assuming humans are the problem in a pursuit of digital perfection, we risk overlooking the very thing that makes engineering work. We make earned, human knowledge obsolete at our peril.