Assessing the responsiveness of existing production operations

Production responsiveness refers to the ability of a production system to achieve its operational goals in the presence of supplier, internal and customer disturbances, where disturbances are those sources of change which occur independently of the system's intentions. A set of audit tools for assessing the responsiveness of production operations is being prepared as part of an EPSRC funded investigation. These tools are based on the idea that the ability to respond is linked to: the nature of the disturbances or changes requiring a response; their impact on production goals; and the inherent response capabilities of the operation. These response capabilities include information gathering and processing (to detect disturbances and production conditions), decision processes (which initiate system responses to disturbances) and various types of process flexibilities and buffers (which provide the physical means of dealing with disturbances). The paper discusses concepts and issues associated with production responsiveness, describes the audit tools that have been developed and illustrates their use in the context of a steel manufacturing plant.

Stress on the ward: evidence of safety tipping points in hospitals

Do hospitals experience safety tipping points as utilization increases, and if so, what are the implications for hospital operations management? We argue that safety tipping points occur when managerial escalation policies are exhausted and workload variability buffers are depleted. Front-line clinical staff is forced to ration resources and, at the same time, becomes more error prone as a result of elevated stress hormone levels. We confirm the existence of safety tipping points for in-hospital mortality using the discharge records of 82,280 patients across six high-mortality-risk conditions from 256 clinical departments of 83 German hospitals. Focusing on survival during the first seven days following admission, we estimate a mortality tipping point at an occupancy level of 92.5%. Among the 17% of patients in our sample who experienced occupancy above the tipping point during the first seven days of their hospital stay, high occupancy accounted for one in seven deaths. The existence of a safety tipping point has important implications for hospital management. First, flexible capacity expansion is more cost-effective for safety improvement than rigid capacity, because it will only be used when occupancy reaches the tipping point. In the context of our sample, flexible staffing saves more than 40% of the cost of a fully staffed capacity expansion, while achieving the same reduction in mortality. Second, reducing the variability of demand by pooling capacity in hospital clusters can greatly increase safety in a hospital system, because it reduces the likelihood that a patient will experience occupancy levels beyond the tipping point. Pooling the capacity of nearby hospitals in our sample reduces the number of deaths due to high occupancy by 34%.