Don’t make your digitalisation strategy a no man’s land: putting people at the centre

Industrial digitalisation is a technical subject that cannot be separated from the people who run it. Every transformation model in the previous article ends up in the same place: the variable that decides the outcome is human.

This is part 7 of 9 of the “OT/IT convergence” series; it follows part 6, the organisational models and continues with part 8, the environmental account.

The apparent contradiction

At first sight, digitalising a plant looks like the opposite of human work. Automation takes over manual steps, software takes over some of the judgement, and the shop floor gets quieter.

On real sites it goes the other way. Every step of digitalisation we have seen in a factory has gone hand in hand with teams becoming more skilled and more at ease with their tools. A digitalised plant does not need fewer capable people. It needs more of them, doing different work.

That question became pressing when the pace of change jumped during and after the COVID-19 crisis, and remote working, remote support and electronic records arrived faster than anyone had prepared for. What happens to the end user when the change lands before the training does?

A human-centred strategy starts at design

For a transformation to hold, people have to be part of the strategy from the first design sketch, not consulted a fortnight before go-live.

Starting from the people who will use the system has practical effects. Real needs become visible, instead of needs someone assumed. New ways of working are adopted rather than tolerated. Errors and workarounds drop, resources go to what is actually used, and there is a feedback channel once the system is live.

The first of those effects pays for the rest. On almost every site there are screens and functions that nobody opens, because they answer a need that was inferred in a meeting room rather than observed at the equipment. An hour spent beside the operator at the start of a shift often saves weeks of rework later.

Digital tools serve people, not the reverse

Digitalised plants rely on closer collaboration between people and machines. The machines are getting smarter, yet the human being stays at the centre of decisions, of supervision and of configuration.

The operator’s role changes. Instead of carrying out a fixed sequence, they become the person who interprets what the system shows and decides what to do with it. That capacity to use technology to make a decision in context is still something digital systems do poorly on their own.

Paul Daugherty and James Wilson make a similar argument in Human + Machine (2018): AI and automation create the most value when they augment what people do rather than replace them. For an engineer, that is a design input, because it changes how the system is specified.

The consequence is a design obligation. Digital tools have to be built around the people who will use them, and be intuitive and usable on a real shift, with gloves on, under time pressure. The aim is fewer errors and a transformation that actually improves production. When an operator has to fight an interface, more training will not fix it: the specification was wrong, and the equipment will keep producing errors for the rest of its service life.

Training is part of the project

Digitalisation puts real strain on organisations, and teams need support through it. Training keeps people current with the technology, builds their skills and, done well, keeps them motivated.

Regulators say the same in their own words. EU GMP Annex 11 §2 asks that all personnel have appropriate qualifications, level of access and defined responsibilities. 21 CFR Part 11 §11.10(i) requires that people who develop, maintain or use electronic record systems have the education, training and experience for their tasks. On the security side, the ISA/IEC 62443 series (formerly ISA-99) treats training and awareness as part of the asset owner’s security programme. The two transformation models set out in part 6 of this series also put people and their learning at the centre: one reads transformation as a change of organisational capability rather than of tooling, the other as a sequence in which the obstacles are social before they are technical.

The cross-training that changes the most

One intervention does more than the others and costs very little: train the IT team on OT, and the OT team on IT practice.

The IT team gains from learning what Modbus and OPC UA actually do, why a PLC scan cycle matters, and what happens to a batch when a control station reboots in the middle of a phase. The OT team gains from understanding what an attacker does after initial access, why the same local administrator password on thirty stations is a problem, and what an audit trail is for.

A half-day session where each side walks the other through its own systems is usually enough to change the tone of the next project meeting. Convergence changes who talks to whom. That is a social change first, and a technical one second.

Why this article belongs in a series about architecture

You could write nine articles on OT/IT convergence entirely about zones, conduits, protocols and standards. They would be accurate, and they would not be enough.

Most of the literature on digital transformation arrives at one idea: it succeeds when technical progress and people’s capacity to adapt move together. In our experience, convergence programmes rarely fail on a technical problem that could not be solved. They stall on the organisation: unclear ownership, teams that do not speak the same language, users who were never asked.

Next: the environmental account, the cost of digitalisation, and the case for it as an environmental instrument.

References

• Paul R. Daugherty and H. James Wilson, Human + Machine: Reimagining Work in the Age of AI, Harvard Business Review Press, 2018.
• Jeanne W. Ross, Cynthia M. Beath and Martin Mocker, Designed for Digital: How to Architect Your Business for Sustained Success, MIT Press, 2019.
• European Commission, EudraLex Volume 4, Annex 11: Computerised Systems, §2 Personnel.
• US FDA, 21 CFR Part 11, §11.10(i).