Driving the sweeping changes in today's business world is the growing awareness that managing customer relationships is a key factor affecting bottom-line profits. Today's customers greatly value timely accessibility. This ease of customer access is fast emerging as the critical element of global business strategy. In the not-too-distant future, customers will deal preferentially with those companies that are deemed to be the most accessible. As the " lightning rod " for customer interactions, world-class call centers are the single point of contact for customers. According to research conducted at Purdue University, over 75% of customer interactions will occur through call centers and the Internet by the year 2000. Fueled by tremendous advances in the integration of telephone and computer technologies, call centers have the potential for being a company's most potent weapon for maintaining long-term customer relationships. With the pressure on developing high performance call centers, managers have been challenged to understand their gaps in performance, to relate these gaps to financial consequences , and to optimize the selection of the most cost-effective solutions. We will discuss how simulation is helping to meet these needs. AUTHOR BIOGRAPHY JON ANTON is with the Department of Consumer Sciences and Retailing at Purdue University, and he is a researcher in the Purdue Call Center for Customer-Driven Quality. He specializes in enhancing customer service strategy through inbound call centers and teleweb centers along with an intranet and middleware for organizing and delivering company information now stored in limited access databases and legacy systems. Dr. Anton has assisted over 400 companies in the improvement of (a) their customer service strategy and delivery by the design and implementation of inbound and outbound call centers; and (b) the decision-making process of using teleservice providers for maximizing service levels while minimizing costs per call. In August of 1996, Call Center Magazine honored Dr. Anton by selecting him as an Original Pioneer of the emerging call center industry. Dr. Anton has guided corporate executives in strategically repositioning their call centers as robust customer access centers through a combination of reengineering, consolidation , outsourcing, and Web-enablement. The resulting single point of contact for the customer allows business to be conducted anywhere, anytime, and in any form. By better understanding the customer lifetime value, he has developed techniques for calculating the return on investment for customer service initiatives.
推动当今商业世界发生翻天覆地变化的是，人们越来越意识到，管理客户关系是影响利润底线的关键因素。今天的客户非常重视及时的可访问性。这种客户访问的便利性正迅速成为全球业务战略的关键要素。在不久的将来，客户将优先与那些被认为最容易接近的公司打交道。世界级的呼叫中心作为客户互动的“避雷针”，是客户的单一接触点。根据普渡大学的研究，到2000年，超过75%的客户互动将通过呼叫中心和互联网进行。由于电话和计算机技术的巨大进步，呼叫中心有可能成为公司维持长期客户关系的最有力的武器。随着开发高绩效呼叫中心的压力，经理们面临着挑战，他们要了解自己在绩效上的差距，将这些差距与财务后果联系起来，并优化选择最具成本效益的解决方案。我们将讨论模拟如何帮助满足这些需求。作者简介乔恩·安东就职于普渡大学消费者科学与零售系，他是普渡大学客户驱动质量呼叫中心的研究员。他擅长通过入站呼叫中心和电话网络中心以及用于组织和交付公司信息的内部网和中间件来增强客户服务策略，这些信息现在存储在访问受限的数据库和遗留系统中。他曾协助400多家公司改进(a)他们的客户服务战略和交付，通过设计和实施入站和出站呼叫中心;(b)使用远程服务提供商最大化服务水平同时最小化每次呼叫成本的决策过程。1996年8月，Call Center Magazine将Anton博士选为新兴呼叫中心行业的原始先锋，以此来表彰他。Anton博士通过重组、整合、外包和网络支持的组合，指导公司高管战略性地重新定位他们的呼叫中心，使其成为强大的客户访问中心。由此产生的客户单点联系点允许随时随地以任何形式开展业务。通过更好地理解客户生命周期价值，他开发了计算客户服务计划投资回报的技术。
{"title":"The use of simulation in call center optimization (keynote address)","authors":"J. Anton","doi":"10.1145/324138.324141","DOIUrl":"https://doi.org/10.1145/324138.324141","url":null,"abstract":"Driving the sweeping changes in today's business world is the growing awareness that managing customer relationships is a key factor affecting bottom-line profits. Today's customers greatly value timely accessibility. This ease of customer access is fast emerging as the critical element of global business strategy. In the not-too-distant future, customers will deal preferentially with those companies that are deemed to be the most accessible. As the \" lightning rod \" for customer interactions, world-class call centers are the single point of contact for customers. According to research conducted at Purdue University, over 75% of customer interactions will occur through call centers and the Internet by the year 2000. Fueled by tremendous advances in the integration of telephone and computer technologies, call centers have the potential for being a company's most potent weapon for maintaining long-term customer relationships. With the pressure on developing high performance call centers, managers have been challenged to understand their gaps in performance, to relate these gaps to financial consequences , and to optimize the selection of the most cost-effective solutions. We will discuss how simulation is helping to meet these needs. AUTHOR BIOGRAPHY JON ANTON is with the Department of Consumer Sciences and Retailing at Purdue University, and he is a researcher in the Purdue Call Center for Customer-Driven Quality. He specializes in enhancing customer service strategy through inbound call centers and teleweb centers along with an intranet and middleware for organizing and delivering company information now stored in limited access databases and legacy systems. Dr. Anton has assisted over 400 companies in the improvement of (a) their customer service strategy and delivery by the design and implementation of inbound and outbound call centers; and (b) the decision-making process of using teleservice providers for maximizing service levels while minimizing costs per call. In August of 1996, Call Center Magazine honored Dr. Anton by selecting him as an Original Pioneer of the emerging call center industry. Dr. Anton has guided corporate executives in strategically repositioning their call centers as robust customer access centers through a combination of reengineering, consolidation , outsourcing, and Web-enablement. The resulting single point of contact for the customer allows business to be conducted anywhere, anytime, and in any form. By better understanding the customer lifetime value, he has developed techniques for calculating the return on investment for customer service initiatives.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124683564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes the typical steps performed in a simulation consulting project in the aviation industry. While the aviation consulting environment does require some differences in the specific approach, the general framework has been applied successfully in the more traditional areas of logistics and manufacturing.
{"title":"Applying simulation in a consulting environment—tips from airport planners","authors":"W.C. Hewitt, E. Miller","doi":"10.1145/324138.324162","DOIUrl":"https://doi.org/10.1145/324138.324162","url":null,"abstract":"This paper describes the typical steps performed in a simulation consulting project in the aviation industry. While the aviation consulting environment does require some differences in the specific approach, the general framework has been applied successfully in the more traditional areas of logistics and manufacturing.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127125968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We present a brief overview of several of the basic output analysis techniques for evaluating stochastic dynamic simulations. This tutorial is intended for those with little previous exposure to the topic, for those in need of a refresher course, and especially for those who have never heard of output analysis. We discuss the reasons why simulation output analysis differs from that taught in basic statistics courses and point out how to avoid common pitfalls that may lead to erroneous results and faulty conclusions.
{"title":"Output modeling: abc's of output analysis","authors":"S. Sanchez","doi":"10.1145/324138.324144","DOIUrl":"https://doi.org/10.1145/324138.324144","url":null,"abstract":"We present a brief overview of several of the basic output analysis techniques for evaluating stochastic dynamic simulations. This tutorial is intended for those with little previous exposure to the topic, for those in need of a refresher course, and especially for those who have never heard of output analysis. We discuss the reasons why simulation output analysis differs from that taught in basic statistics courses and point out how to avoid common pitfalls that may lead to erroneous results and faulty conclusions.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127971410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Modeling a simulation system requires a great deal of customization. At first sight no system seems to resemble exactly another system and every time a new model has to be designed the modeler has to start from scratch. The present simulation languages provide the modeler with powerful tools that greatly facilitate building models (modules for arrivals or servers, etc.). Yet, also with these tools the modeler constantly has the feeling that he is reinventing the wheel again and again. Maybe the model he is about to design already exists (maybe the modeler has designed it himself some time ago) or maybe a model already exists that sufficiently resembles the model to be designed. In this article an approach is discussed that deploys knowledge-based systems to help selecting a model from a database of existing models. Also, if the model is not present in the database, would it be possible to select a model that in some sense is close to the model that the modeler had in mind?.
{"title":"Knowledge-based modeling of discrete-event simulation systems","authors":"H. D. S. Arons","doi":"10.1145/324138.324441","DOIUrl":"https://doi.org/10.1145/324138.324441","url":null,"abstract":"Modeling a simulation system requires a great deal of customization. At first sight no system seems to resemble exactly another system and every time a new model has to be designed the modeler has to start from scratch. The present simulation languages provide the modeler with powerful tools that greatly facilitate building models (modules for arrivals or servers, etc.). Yet, also with these tools the modeler constantly has the feeling that he is reinventing the wheel again and again. Maybe the model he is about to design already exists (maybe the modeler has designed it himself some time ago) or maybe a model already exists that sufficiently resembles the model to be designed. In this article an approach is discussed that deploys knowledge-based systems to help selecting a model from a database of existing models. Also, if the model is not present in the database, would it be possible to select a model that in some sense is close to the model that the modeler had in mind?.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126410766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulation is a popular tool for accurately estimating the performance of an automated material handling system (AMHS). Accuracy of the model is normally dependent on a detailed description of the AMHS physical system components and their coordinate positions. In this paper, a methodology is defined for automatically inputting the physical system components used to describe an AMHS within a simulation language. The method is based on data extraction from a CAD layout file of the system. Automatically generating the physical system components reduces simulation model building time and increases model accuracy.
{"title":"Reducing model creation cycle time by automated conversion of a CAD AMHS layout design","authors":"I. Paprotny, W. Zhao, G. Mackulak","doi":"10.1145/324138.324477","DOIUrl":"https://doi.org/10.1145/324138.324477","url":null,"abstract":"Simulation is a popular tool for accurately estimating the performance of an automated material handling system (AMHS). Accuracy of the model is normally dependent on a detailed description of the AMHS physical system components and their coordinate positions. In this paper, a methodology is defined for automatically inputting the physical system components used to describe an AMHS within a simulation language. The method is based on data extraction from a CAD layout file of the system. Automatically generating the physical system components reduces simulation model building time and increases model accuracy.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114455246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The conduct of Operations Other Than War (OOTWs) has become an extremely important part of the US military's responsibility since the end of the Cold War. The factors that influence success and failure in OOTWs are economic, political, sociological, cultural, and psychological factors more often than they are military factors. This paper explores the need for impact analysis support tools, provides a description of the required elements of such tools, and recommends a formal process for creating OOTW impact analysis tools.
{"title":"OOTW impact analysis","authors":"D. Hartley, R. E. Bell, S. Packard","doi":"10.1145/324898.324992","DOIUrl":"https://doi.org/10.1145/324898.324992","url":null,"abstract":"The conduct of Operations Other Than War (OOTWs) has become an extremely important part of the US military's responsibility since the end of the Cold War. The factors that influence success and failure in OOTWs are economic, political, sociological, cultural, and psychological factors more often than they are military factors. This paper explores the need for impact analysis support tools, provides a description of the required elements of such tools, and recommends a formal process for creating OOTW impact analysis tools.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134446259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
As industrial manufacturing and automation systems grow in complexity, there is a need for control software engineering support. Soft-commissioning and reality in the loop (RIL) are two novel approaches which allow coupling simulation models to real world entities and allow the analyst to pre-commission and test the behavior of a system, before it is completely built in reality. To be flexible and fast in building up a simulation model fulfilling the requirements of soft-commissioning and RIL there is a need for a component-based modeling architecture. We define the characteristic requirements, and derive an architecture out of them, which is discussed from different aspects. Finally we briefly present a simple example.
{"title":"Interface driven domain-independent modeling architecture for “soft-commissioning” and “reality in the loop”","authors":"F. Auinger, M. Vorderwinkler, G. Buchtela","doi":"10.1145/324138.324504","DOIUrl":"https://doi.org/10.1145/324138.324504","url":null,"abstract":"As industrial manufacturing and automation systems grow in complexity, there is a need for control software engineering support. Soft-commissioning and reality in the loop (RIL) are two novel approaches which allow coupling simulation models to real world entities and allow the analyst to pre-commission and test the behavior of a system, before it is completely built in reality. To be flexible and fast in building up a simulation model fulfilling the requirements of soft-commissioning and RIL there is a need for a component-based modeling architecture. We define the characteristic requirements, and derive an architecture out of them, which is discussed from different aspects. Finally we briefly present a simple example.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132400136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We investigate and discuss some of the main issues concerning the estimation of nonlinear simulation metamodels. We propose a methodology for identifying a tentative functional relationship, estimating the metamodel coefficients and validating the simulation metamodel. This approach is illustrated with a simple queueing system. Finally, we draw some conclusions and identify topics for further work in this area.
{"title":"The main issues in nonlinear simulation metamodel estimation","authors":"M. I. Reis, Dos Santos, Acácio M O Porta, Nova","doi":"10.1145/324138.324309","DOIUrl":"https://doi.org/10.1145/324138.324309","url":null,"abstract":"We investigate and discuss some of the main issues concerning the estimation of nonlinear simulation metamodels. We propose a methodology for identifying a tentative functional relationship, estimating the metamodel coefficients and validating the simulation metamodel. This approach is illustrated with a simple queueing system. Finally, we draw some conclusions and identify topics for further work in this area.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121429148","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The web presents an opportunity for realizing a distributed design framework supporting multi-disciplinary, multi-organizational collaborative design and analysis activities. The potential for deploying online, reusable parts libraries for virtual prototyping and design analysis exists. However, several issues must be solved before vendors will be willing to provide online access to their intellectual property (IP). This paper reviews the main problems facing the web-based design and analysis community before the successful application of web-based virtual prototyping can become a reality. To amplify and solidify our arguments, the application domain of web-based hardware/software co-design is used.
{"title":"Web-based analysis and distributed IP","authors":"P. Wilsey","doi":"10.1145/324898.325299","DOIUrl":"https://doi.org/10.1145/324898.325299","url":null,"abstract":"The web presents an opportunity for realizing a distributed design framework supporting multi-disciplinary, multi-organizational collaborative design and analysis activities. The potential for deploying online, reusable parts libraries for virtual prototyping and design analysis exists. However, several issues must be solved before vendors will be willing to provide online access to their intellectual property (IP). This paper reviews the main problems facing the web-based design and analysis community before the successful application of web-based virtual prototyping can become a reality. To amplify and solidify our arguments, the application domain of web-based hardware/software co-design is used.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122986204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A simulation project is much more than building a model. And the skills required go well beyond knowing a particular simulation tool. This paper discusses some important steps to enable project success and some cautions and tips to help avoid common traps.
{"title":"Tips for successful practice of simulation","authors":"D. Sturrock","doi":"10.1145/324138.324153","DOIUrl":"https://doi.org/10.1145/324138.324153","url":null,"abstract":"A simulation project is much more than building a model. And the skills required go well beyond knowing a particular simulation tool. This paper discusses some important steps to enable project success and some cautions and tips to help avoid common traps.","PeriodicalId":287132,"journal":{"name":"Online World Conference on Soft Computing in Industrial Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115159513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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