Digital twins: think about situations not semantics

“Let me start by defining what I mean by digital twin...”

This is how almost every presenter opened their talk at a Digital Twins conference. By the end of the conference, it was a running joke. And if they were being honest they would conclude “A digital twin is a trend I heard about that I think I can leverage to sell my product”.

This reminds me of a quote from Harvard Business School Professor Theodore Levitt,

“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!”.

While the presenters at the Digital Twins conference are busy defining what a drill is, there are countless real-world problems to solve. They’re forgetting the most important part; user experience. This is what brings value to all the stakeholders involved.

After defining what a digital twin means to them- a Digital Twins company will probably start talking about bringing data behind ‘a single pane of glass’. This idea is good data governance but we are still not talking about a solution. We still have the same data we had before- now just under a single, proprietary, closed-off ecosystem or; “pane of glass”. This is focusing on the technology and not the problem.

The best way to solve a problem is to remove it- not add more technology. Let’s remove the glass altogether, perhaps automate the experience so you don’t need to collect or visualize data.

Digital twin companies might be database experts- but they are not data insights experts. They are not qualified to provide insights into your data or tell the difference between correlation and causation. And you cannot just throw ‘AI’ at it. An IF statement is not AI. And a rules engine is not machine learning. People with domain knowledge still need to be a part of the solution. People who can turn data into insights. For example, a workplace consultant for commercial buildings or a logistics consultant for a warehouse.

In writing all of this I obviously have a few companies in mind. The only one I will pick on is Microsoft. Their demo (below) of Azure Digital Twins uses a scenario for supply chain management that doesn’t actually bring anything new to the table. Firstly, the issue is reported via person and is not automatically detected. Secondly, using her supply chain domain knowledge she knows where to look to find the potential cause of the problem- it is not automatically identified. Thirdly, the product with ‘insights’ in the tile provides a graph but the insights come from her domain knowledge once again. Finally, she mentions ‘machine learning’ after manually shutting down a factory. The missing opportunity across all of this is automation. But my point is- why do we even need to mention digital twins- this particular demo is showing data visualization- which has value- but this is not a new product category or innovative breakthrough- it’s just real-time integrations.

You might hear me use the phrase, digital twin, to explain how PlaceOS works. But I use it in context and focus on it being the ‘how not the what or why’. We have an integration that tells us the real-time state and status of any device: a digital twin of that device, system,  or person. This is simply how we get data- what we do with it is the user experience- and defined by the user.

As trends mature and expectations vs realities balance- the buzz words often fade away. IoT is a good example of this (and even worse was the Internet of Everything). The biggest promise of Digital Twins is the life cycle management of an asset from design to operation. But we will know it’s matured when we are talking about a life cycle management platform- not a digital twins platform.

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