Funfact: Since 2012 the interest for the topic has x 100
Holy, surprisingly its popular in south korea which was unexpected for me.
Fun fact: Lokad started to implement digital twins of supply chains more than a decade ago; although I don't overly like this terminology. As a rule of thumb, I tend to dislike terminologies that try to make tech sounds cool, irrespectively of the merit of said technology. There are tons of challenges associated with large scale modeling of supply chain, the first one being: how accurate is my digital twin? Tech vendors are usually exceedingly quite about this essential question.
Answering a question on YouTube:
As per my understanding the following are the core concerns -
2) Doesn't necessarily represent reality based on Agent behaviour
3) Gives me insights, ok now what should i do? Don't give me numbers, tell me what to do. If an employee sits down and tweaks parameters then how do i make sense if the decision is correct?
Yes, in short, the two big gotchas are (a) your digital twin may no reflect the reality (b) your digital twin may not be prescriptive.
Concerning (a), measuring accuracy when considering the modeling of a system turns out to be a difficult problem. I intend to revisit the case in my series of supply chain lectures, but it's nontrivial, and so far all the vendors seem to be sweeping the dust under the rug.
Concerning (b), if all the digital twin delivers are metrics, then, it's just an elaborate way to waste employee's time, and thus money. Merely presenting metrics to employees is suspicious if there is no immediate call-to-call. If there is a call-to-action, then let's take it further and automate the whole thing.
Thanks Joannes, would it make sense to have more intelligent agent behavior? How far should we go to say that we have reached a point of say realistic representation of an agent? Also when we say accuracy , what does it really mean? Is it like ,say , we predicted something up or down and we are correct 90 times out of 100 so our accuracy is 90%?
How far should we go to say that we have reached a point of say realistic representation of an agent? Also when we say accuracy , what does it really mean?
Right now, as far as my understanding of the supply chain literature goes, there is just nothing yet published to tell you whether a simulation - in the general case - is accurate or not. The tool we have for time-series forecast don't generalize properly to higher dimensional settings.
For example, if a simulator of a multi-echelon supply chain of interest is implemented, and then someone decide to refine of the model of some inner agent within the simulator, there is no metric that are even known to be able to tell you if this refinement is making the simulator more accurate of not.
Stay tuned, I am planning a lecture on the subject in the future, it's a big tough question.