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Reducing waiting time by pooling demand


By pooling demand, the inter-arrival times are shortened and thus the specific demand goes up (which is intuitive, since pooling demand basically means combining different demand streams). While the utilization rate is not effected by demand pooling, the waiting time is shortened because some inefficiencies (idle time at station A while station B is overwhelmed) are eradicated. However, pooling more and more resources together also decreases the overall efficiency once the demand is met. Therefore, companies need to find a viable balance between efficiency and responsiveness.

What main benefits and costs are connected with pooling in the context of waiting time?

  • Pooling assumes total flexibility (Spanish call center agents will not be able to answer to German customers, even if the call center company decided to pool all calls together).
  • Pooling increases the complexity of the workflow, since demands needs to be shifted between resources who might be locally apart (e.g. two hospitals or two plants).
  • Pooling interrupts the continuity of interaction between the flow unit (customer) and the resource (worker) and can thus hurt the customer experience because customers will not want to see a different physician or a different financial consultant on every separate visit.
These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.
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Shortening set-up times in order to increase flexibility


Every set-up process can be broken up in external and internal activities. External activities can be completed while the station in need of the set-up is still running. Such activities can be moved up front, e.g. preparing patients outside of the operating room while another patient is still being operated on inside. If set-up times can also be improved through other activities (standardization, process optimisation etc.), flow unit types can be changed more often and flexibility is increased. This idea lies at the heart of the mixed-model production, which also profits from configuring a network of production facilities for pooling in order to be more flexible in catering to demand.

These lecture notes were taken during 2013 installment of the MOOC “An Introduction to Operations Management” taught by Prof. Dr. Christian Terwiesch of the Wharton Business School of the University of Pennsylvania at Coursera.org.
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