I just received a YouTube link from my colleague Christian with a nice and short campaign movie about digital twins and all the great benefits they imply.
You can see digital twin technology being applied to airplane engines, buildings, oil rigs or human organs… and it looks amazing! It’s not difficult to understand what advantages digital twins offer to the experts developing these amazing technologies, and the possibilities for training, learning and testing in safe environments.
In the same cool way, I would like to present ourselves and our innovative platform. So simple and so easy to see the benefits, but gee, this has suddenly become somewhat challenging.
We are namely building a digital twin of an organizational capability. What is that?
After explaining this for more than two hours (when advising my client) he eventually got it. But why was it so hard?
I believe it is because we are accustomed to innovating and improving physical assets and have been doing so for hundreds of years. That is easy to understand, and it’s even easier to understand that it required a lot of time spent prototyping in order to minimize costly, and even deadly, mistakes in the realization phase.
Now, when we are faced with an even more dazzling potential for improvement, enhancing our human intelligence with computer intelligence in various ways, it is harder for skilled, but non-programming people, to capture and understand the things we want to invent or improve.
So, how can we showcase a digital twin of an organizational capability?
Let’s try with an example from a client we worked with for many years within healthcare.
As part of proving that it is possible to collect complex knowledge from many different clinical disciplines into one Health Care Brain, we worked with a stroke recovery team at one of the university hospitals. Our goal was to build a digital twin of the capability to treat a stroke patient in the best possible way, and to achieve the best recovery state as possible. We asked the neurologists what knowledge and information is vital for them in order to have as many patients as possible walk out from the hospital feeling great.
They then told us all about age, sex, other diagnoses, active medication, former medical history, pulse, blood pressure, temperature, time of seizure, additional medication, experience of the neurologist, equipment at hand, MR scanning, different scales of determining level of damage, experience of other medical personnel, requirements of the treatment rooms and all the rule based combinations of the above. We made a logical model of this knowledge and created a data model.
We built a digital twin that comprised the core logic from the best neurologists treating stroke patients in the real world. Just like prototyping a virtual jet engine to see if it can handle the strains and demands in different kinds of situations, we tested the digital twin with all the real patient data we could find. Together with these professionals we were able to find potential errors and correct them. But we also found and added new insights along the way, which they did not know had an impact on the recovery phase.
“Just like prototyping a virtual jet engine to see if it can handle the strains and demands in different kinds of situations, we tested the digital twin with all the real patient data we could find.”
Digital checklists were created, which adapted in real-time to incoming information about the patient. One doctor now had the knowledge from the whole group at hand and received intelligent decision support in very stressful situations.
It was an amazing experience to work with these experts and we were extremely happy when we saw the neurologists sharing knowledge and enhancing the digital twin.
I hope we can make a cool video from this, and perhaps have many other examples in the future. What do you think?
Now you all might wonder, “Why don’t I see this digital twin in action”?
Well, ask the administrators why it’s better that neurologists have to spend 60-80% of their time using post-it notes for planning; to keep check lists in paper collectors; to feed four insufficient computer systems with data while not getting much knowledge output at all); to work overtime until they are physically and emotionally exhausted and crying during meetings because they see people dying or being hospitalized for the rest of their lives.
Many claim that doctors and nurses don’t want to share knowledge and are difficult to work with. We have never experienced that. They are smart people that view learning as a big part of their lives and have a calling to help people in need.
Watch the YouTube video that inspired me…