Haretoise: The answer for when industrial and digital cultures collide

You can draw parallels between the pace of technological change and the fable of the tortoise and the hare –software is the fast-moving hare, and hardware is the slow and steady tortoise.

It’s not always clear which is going to cross the line first, so maybe we need to consider a hybrid –  a haretoise.

But first, let’s consider the merits and challenges of each.

The ‘digital’ Hare

The digital world may be racing ahead, but it is also imperfect – something that Silicon Valley relishes: Facebook’s famous mantra in the ’00s was, “Move fast and break things.”

Minimum viable products (MVPs) sit at the core of this approach – where the consumer internet leverages real-time user data and feedback to iterate solutions.

Updates are cheap and can be rolled out instantly, and the risk and consequence of failure is typically low – especially in the consumer world.

Amazon, a organisation the majority of us will be familiar with, uses AI and machine learning algorithms to recommend new titles – Customers who bought book ‘X’ might also like book ‘y’.

If they get the suggestion wrong, it’s not a big deal. In the consumer world, AI can make things better – but it doesn’t need to be perfect.

A culture of “failing fast” has created many of the game-changing, market-leading businesses and services we use every day – Airbnb, Uber, Amazon and more.

The ‘industrial’ Tortoise

Manufacturing is different. We operate and rely on infrastructure and hardware that have a 30, even 40-year lifecycle. Trains, planes, lathes, mills, pumps – industrial assets can last for decades, and run under some extreme conditions.

Yet just like the tortoise, part of the value of industrial assets is that they are slow and steady. Reliable.

That’s because industrial hardware has to prioritise safety – jet engines, power stations, water treatment facilities cannot fail. Whether you are making electricity or wine, quality and safety count.

Visit a factory – and before the laptop even boots up you will be taken through the site’s safety presentation faster than you can say ‘steel toe-capped boots’. It’s part of the culture. Slow and steady is a virtue.

The thing is – digital can help. Massively. While perfection is a virtue, it’s an incredibly expensive and wasteful one. That’s no good for businesses, economies or the environment.

So, if the answer isn’t the tortoise or the hare, what is it?

Enter the Haretoise

To meet their commercial and strategic goals, industrial companies are trying to bring the fast-moving, iterative nature of software to the slow, safe, steady state of engineering.

This, however, can create cultural conflict. The risk averse tortoises don’t want to fail fast. At the same time, the faster hares might make mistakes – but by collaborating closely with the tortoises they can model and predict problems before they even happen.

Technologies like the Digital Twin are great enablers of this.

So, what companies need from their employees is the ability to reconcile traditional hardware thinking with the ability to constantly learn, experiment and, yes, fail fast. But they need to do it while managing risk.

It’s not a one-way street. Digital natives need to demonstrate that their software is just as robust as the industrial hardware it serves. Companies that implement at speed and scale need to demonstrate ROI – just as they would if they were buying new capital equipment.

Technical expertise, deep domain expertise, is just as important as it ever was. But to provide the best industrial products and services at the best cost, a new breed of engineer is needed.

It is worth investing in. At GE Digital, we call them ‘Digital Migrants’ (and we employ many who are helping our customers to save millions of dollars in maintenance costs every year).

With decades of real industrial experience, they provide the best analysis to train our Machine Learning algorithms – and provide insights to our customers – that really are the best of both worlds.

Our customers tell us this directly: It is much easier to take an engineer from the factory floor and train them in data science, than it is to take a data scientist and train them to understand the physics of a piece of hardware.

To overcome the cultural divide between the two, it’s important to have both digital natives AND digital migrants. They become your ‘translators’ that help bring the two worlds together.

And who knows, along the way, you might even find a few Haretoises!