A Predictive Analytic Model for Value Chain Management

Value chain management has gone through various stages of automation, integration and optimization in the past decades. While an optimization model for value chain deals with business scenarios under known circumstances, a predictive value chain model deals with probable circumstances in the future. Predictive analytics is succeeding optimization in the evolution of technologies supporting value chain management. This paper proposes a forward looking value creation model that combines the important concepts of value chain management and predictive analytics. An enterprise model for value chain predictive analytics that facilitates the convergence of information, operations and analytics is presented

Supply chain management of blood products: a literature review.

This paper presents a review of the literature on inventory and supply chain management of blood products. First, we identify different perspectives on approaches to classifying the existing material. Each perspective is presented as a table in which the classification is displayed. The classification choices are exemplified through the citation of key references or by expounding the features of the perspective. The main contribution of this review is to facilitate the tracing of published work in relevant fields of interest, as well as identifying trends and indicating which areas should be subject to future research.OR in health services; Supply chain management; Inventory; Blood products; Literature review;

Minimizing average handling time in contact centers by introducing a new process: Rowan Support Desk case study

Quality of a call center performance is an important factor in insuring customer satisfaction. Customers, the callers , want their requests solved quickly, permanently and to their satisfaction. Often, there are staff constraints, budget or cost limitation, and the Service Level Agreement (SLA) which is resource availability to accomplish a task within a deadline. The purpose of this research is to analyze feasible approaches to minimize the long-lasting open requests and enhance a call center\u27s performance. Multiple challenges that a call center often faces in handling requests are studied to identify key bottlenecks in the process of handling requests. Rowan University support desk is used as a case study. The focus of this study is on over-extended unsolved requests under set of specific constraints. The following two alternative solutions were investigated and compared. One involves reorganizing the routing procedure, which would allow a ticket to be rerouted to the specialists. The other scenario investigates an increase in staff and efficiencies that would come with it. The research will show that with minimal effort in rerouting the unsolved tickets, we can decrease average handling time which simultaneously increases the total number of resolved tickets and minimize total processing time

Performance Indicators Analysis inside a Call Center Using a Simulation Program

This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key case at the time where the events analyses could be executed. This article comes to the conclusion that Simulation is a completely suitable instrument to accomplish its purpose since it could be adequate to demonstrate, for the call center taken into consideration principally that: (a) it is feasible to reduce the agent contingent; (b) reasonable variations on the demand design can impact very much the key performance indicators of the Call Centers’ project; and (c) it is feasible to increase the service level if a combined handling format is followed

Performance Indicators Analysis inside a Call Center Using a Simulation Program

This paper deals with and shows the results of different performance indicators analyses made utilizing the help of Simulation and concentrated on dimensioning problems of handling calls capacity in a call center. The goal is to measure the reactivity of the call center’s performance to potential changes of critical variables. The literature related to the employment of this kind of instrument in call centers is reviewed, and the method that this problem is treated momentarily is precisely described. The technique used to obtain this paper’s goal implicated a simulation model using Arena Contact Center software that worked as a key case at the time where the events analyses could be executed. This article comes to the conclusion that Simulation is a completely suitable instrument to accomplish its purpose since it could be adequate to demonstrate, for the call center taken into consideration principally that: (a) it is feasible to reduce the agent contingent; (b) reasonable variations on the demand design can impact very much the key performance indicators of the Call Centers’ project; and (c) it is feasible to increase the service level if a combined handling format is followed

Real-time optimization of an integrated production-inventory-distribution problem.

In today\u27s competitive business environment, companies face enormous pressure and must continuously search for ways to design new products, manufacture and distribute them in an efficient and effective fashion. After years of focusing on reduction in production and operation costs, companies are beginning to look into distribution activities as the last frontier for cost reduction. In addition, an increasing number of companies, large and small, are focusing their efforts on their core competencies which are critical to survive. This results in a widespread practice in industry that companies outsource one or more than one logistics functions to third party logistics providers. By using such logistics expertise, they can obtain a competitive advantage both in cost and time efficiency, because the third party logistics companies already have the equipment, system and experience and are ready to help to their best efforts. In this dissertation, we developed an integrated optimization model of production, inventory and distribution with the goal to coordinate important and interrelated decisions related to production schedules, inventory policy and truckload allocation. Because outsourcing logistics functions to third party logistics providers is becoming critical for a company to remain competitive in the market place; we also included an important decision of selecting carriers with finite truckload and drivers for both inbound and outbound shipments in the model. The integrated model is solved by modified Benders decomposition which solves the master problem by a genetic algorithm. Computational results on test problems of various sizes are provided to show the effectiveness of the proposed solution methodology. We also apply this proposed algorithm on a real distribution problem faced by a large national manufacturer and distributor. It shows that such a complex distribution network with 22 plants, 7 distribution centers, 8 customer zones, 9 products, 16 inbound and 16 outbound shipment carriers in a 12-month planning period can be redesigned within 33 hours. In recent years, multi-agent simulation has been a preferred approach to solve logistics and distribution problems, since these problems are autonomous, distributive, complex, heterogeneous and decentralized in nature and they require extensive intelligent decision making. Another important part in this dissertation involved a development of an agent-based simulation model to cooperate with the optimal solution given by the optimization model. More specifically, the solution given by the optimization model can be inputted as the initial condition of the agent-based simulation model. The agent-based simulation model can incorporate many other factors to be considered in the real world, but optimization cannot handle these as needed. The agent-based simulation model can also incorporate some dynamics we may encounter in the real operations, and it can react to these dynamics in real time. Various types of entities in the entire distribution system can be modeled as intelligent agents, such as suppliers, carriers and customers. In order to build the simulation model more realistic, a sealed bid multiunit auction with an introduction of three parameters a, ß and y is well designed. With the help of these three parameters, each agent makes a better decision in a simple and fast manner, which is the key to realizing real-time decision making. After building such a multi-agent system with agent-based simulation approach, it supports more flexible and comprehensive modeling capabilities which are difficult to realize in a general optimization model. The simulation model is tested and validated on an industrial-sized problem. Numerical results of the agent-based simulation model suggest that with appropriate setting of three parameters the model can precisely represent the preference and interest of different decision makers