Please welcome Dr. Stefan Haeussler to the ISE Department. Dr. Haeussler serves as an assistant professor at the University of Innsbruck.
As always refreshments are available in 428 Daniels Hall 30 minutes before the seminar begins.
Decision makers in industry can make use of huge amounts of data available through IT systems like Enterprise Resource Planning systems. Although in general the access to actual and accurate data is seen as positive, it may also lead to poor outcomes which is especially true for human decision makers (e.g., due to the information overload). With regard to lead time management, we know from literature and anecdotal evidence that such a phenomenon
exists: the so-called ‘lead time syndrome’. The lead time syndrome is a vicious cycle where the observed duration of orders through the production system (flow time) increase a planning parameter (planned lead time) which leads to perpetually increasing input to the system which increases the flow times again. Interestingly, there is no literature on the human causes for the lead time syndrome although in industrial practice human decision makers play a key role in planning systems. Therefore, the first part of this talk is on our study that analyzes the human causes for the lead time syndrome by using a laboratory experiment. The second part of this talk focuses on (one of) our most recent solutions to the lead time syndrome: an algorithm based on artificial intelligence (a machine learning algorithm) with the ultimate aim to support the human decision maker.
