6 resultados para front line management

em Cambridge University Engineering Department Publications Database


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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%.

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The optimization of dialogue policies using reinforcement learning (RL) is now an accepted part of the state of the art in spoken dialogue systems (SDS). Yet, it is still the case that the commonly used training algorithms for SDS require a large number of dialogues and hence most systems still rely on artificial data generated by a user simulator. Optimization is therefore performed off-line before releasing the system to real users. Gaussian Processes (GP) for RL have recently been applied to dialogue systems. One advantage of GP is that they compute an explicit measure of uncertainty in the value function estimates computed during learning. In this paper, a class of novel learning strategies is described which use uncertainty to control exploration on-line. Comparisons between several exploration schemes show that significant improvements to learning speed can be obtained and that rapid and safe online optimisation is possible, even on a complex task. Copyright © 2011 ISCA.

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Product innovativeness is a primary contingent factor to be addressed for the development of flexible management for the front-end. However, due to complexity of this early phase of the innovation process, the definition of which attributes to customise is critical to support a contingent approach. Therefore, this study investigates front-end attributes that need to be customised to permit effective management for different degrees of innovation. To accomplish this aim, a literature review and five case studies were performed. The findings highlighted the front-end strategic and operational levels as factors influencing the front-end attributes related to product innovativeness. In conclusion, this study suggests that two front-end attributes should be customised: development activities and decision-making approach. Copyright © 2011 Inderscience Enterprises Ltd.

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Decision-making at the front-end of innovation is critical for the success of companies. This paper presents a simple visual method, called DMCA (Decision-Making Criteria Assessment), which was created to clarify and improve decision-making at the front-end of innovation. The method maps the uncertainty of project information and importance of decision criteria, compiling a measure that indicates whether the decision is highly uncertain, what information interferes with it, and what criteria are actually being considered. The DMCA method was tested in two projects that faced decision-making issues, and the results confirm the benefits of using this method in decision-making at the front-end. © 2012 IEEE.

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This paper studies the Front End of Eco-Innovation (FEEI), the initial phase of the eco-innovation process. Incorporating environmental concerns at the front-end of innovation is important, as product parameters are still flexible. This paper investigates the FEEI for 42 small and medium sized eco-innovators in the Netherlands by using a survey. The results show that SMEs embrace informal, systematic, and open innovation approaches at the FEEI. Teams appear to be multidisciplinary, and creativity and environmental knowledge are essential. Experimentation played a significant role at the FEEI. The paper concludes with recommendations for future research and implications for managers. © 2013 Elsevier B.V.

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Decision making at the front end of innovation is critical for the success of companies. This paper presents a method, called decision making based on knowledge (DeBK), which was created to analyze the decision-making process at the front end. The method evaluates the knowledge of project information and the importance of decision criteria, compiling a measure that indicates whether decisions are founded on available knowledge and what criteria are in fact being considered to delineate them. The potential contribution of DeBK is corroborated through two projects that faced decision-making issues at the front end of innovation. © 2014 RADMA and John Wiley & Sons Ltd.