Process wind tunnel for improving insurance business processes

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Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

Process wind tunnel for improving insurance business processes

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For simulation modeling, what-if analysis and optimization studies of many service and production operations, demand models that are reliable statistical representations of current and future operating conditions are required. Current simulation tools allow demand modeling using known closed-form statistical distributions or raw demand data collected from operations. In many instances, demand data cannot be described by known closed-form statistical distributions and the raw data collected from operations is not representative of future demand. This paper describes an approach to demand modeling where historical demand data collected over a finite time period is combined with user-input using two-tier bootstrapping to produce synthetic demand data that preserves the statistical distribution of the original data but has overall metrics such as volume, workflow mix and individual task and job sizes that represent projected future state scenarios. When the customer demand data follows highly non-normal distributions, a modified procedure is presented.

Wsc 2015 modeling customer demand in print service environments using

Wsc 2015 modeling customer demand in print service environments using

Wsc 2015 modeling customer demand in print service environments using

This paper describes a discrete-event simulation and event-log analysis based approach for computing sustainability metrics in production environments to perform various types of comparative analysis and assessments. Event logs collected from the production environment are analyzed to compute current state sustainability metrics such as energy usage, carbon footprint and heating/cooling requirements. Bootstrapping based forecasting leveraging expert input is utilized to estimate future demand. The forecasted demand is then simulated to predict sustainability metrics. The discrete-event simulation results from the forecasted data and computation of heat produced is combined with thermodynamic models of heat transfer through the thermal envelope of the facility to provide more accurate estimates of true carbon footprint associated with the production operations while also enabling cross-comparative studies of setting operations in different geographical locations. The framework and software tool enables the integration of productivity metrics and sustainability metrics in decision-making process for designing and operating production environments.

AN EVENT-LOG ANALYSIS AND SIMULATION-BASED APPROACH FOR QUANTIFYING SUSTAINAB...

AN EVENT-LOG ANALYSIS AND SIMULATION-BASED APPROACH FOR QUANTIFYING SUSTAINAB...

AN EVENT-LOG ANALYSIS AND SIMULATION-BASED APPROACH FOR QUANTIFYING SUSTAINAB...

The paper describes a software toolkit that enables the data-driven simulation-based optimization of print shops It enables quick modeling of complex print production environments under the cellular production framework. The software toolkit automates several steps of the modeling process by taking declarative inputs from the end-user and then automatically generating complex simulation models that are used to determine improved design and operating points. This paper describes the addition of another layer of automation consisting of simulation-based optimization using simulated-annealing that enables automated search of a large number of design alternatives in the presence of operational constraints to determine a cost-optimal solution. The results of the application of this approach to a real-world problem are also described.

SIMULATION-BASED OPTIMIZATION USING SIMULATED ANNEALING FOR OPTIMAL EQUIPMENT...

SIMULATION-BASED OPTIMIZATION USING SIMULATED ANNEALING FOR OPTIMAL EQUIPMENT...

SIMULATION-BASED OPTIMIZATION USING SIMULATED ANNEALING FOR OPTIMAL EQUIPMENT...

This paper describes a systematic six-step data-driven simulation-based methodology for optimizing people-based service systems on a large distributed scale that exhibit high variety and variability. The methodology is exemplified through its application within the printing services industry where it has been successfully deployed by Xerox Corporation across small, mid-sized and large print shops generating over $250 million in profits across the customer value chain. Each step of the methodology consisting of innovative concepts co-development and testing in partnership with customers, development of software and hardware tools to implement the innovative concepts, establishment of work-process and practices for customer-engagement and service implementation, creation of training and infrastructure for large scale deployment, integration of the innovative offering within the framework of existing corporate offerings and lastly the monitoring and deployment of the financial and operational metrics for estimating the return-on investment and the continual renewal of the offering are described in detail.

Data-Driven Simulation-Enhanced optimization of Service operations

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IIE Lean Best Practice Award presentation (Won First Place in the competition)

IIE Lean Best Practice Award presentation (Won First Place in the competition)

IIE Lean Best Practice Award presentation (Won First Place in the competition)

Fat-tail inputs in manufacturing systems (Industrial Engineering Research Con...

Fat-tail inputs in manufacturing systems (Industrial Engineering Research Con...

Fat-tail inputs in manufacturing systems (Industrial Engineering Research Con...

Maximizing operations productivity with lean document production

Maximizing operations productivity with lean document production

Maximizing operations productivity with lean document production

A software toolkit and data-driven process improvement solution leveraging ev...

A software toolkit and data-driven process improvement solution leveraging ev...

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The talk describes how service operations in the insurance industry can be optimized using Process Wind Tunnel. Process Wind Tunnel utilizes novel process analytics, process mining, simulation and targeted automation to improve business processes. It also describes a real-world application of process mining to diagnose complex business process and gain insights. This talk was delivered at the Process Mining Camp 2020 and is available on Youtube (https://www.youtube.com/watch?v=ujEoPiuo9As)

Process Wind Tunnel in Insurance

Process Wind Tunnel in Insurance

Process Wind Tunnel in Insurance

Many business enterprises outsource the management of processes and technology that they consider non-core to third-party service providers. The challenge for the service providers is to leverage their expertise to deliver managed services that more efficient, productive and profitable. Examples include IT infrastructure management (IBM, HP), print services management (Xerox, Ricoh, Pitney Bowes), food services (Aramark, Compass Group, Sodexo) and others. Many traditional product companies have increasingly diversified as service providers of this type and rely on a combination of people and technology for services delivery. The capability and expertise to deliver high quality optimized processes on a large scale without incurring high costs is a key imperative for these companies. This is traditionally achieved through standardization of processes, capture and dissemination of best practices and domain knowledge and structured training programs. Process optimization technologies such as discrete-event simulation, stochastic process modeling and advanced analytics have traditionally been the forte of expert (and often high-paid) consultants which has limited their broad use in these services industries primarily due to cost constraints. This talk will describe how process optimization solutions were developed and delivered on a large scale to the Xerox document production outsourcing-services business. Early on, extensive consulting engagements with end-customers were used to abstract and generalize the process optimization problem. Then the various steps of the process optimization problem such as data collection, statistical analysis, simulation and modeling, optimization, scheduling and monitoring were abstracted and modeled. Technology and algorithms for each step were developed, refined, automated, integrated and then encapsulated in an easy-to-use software toolkit that supported a structured customer engagement process by less-skilled delivery personnel. The delivery of process optimization services using these automated tools that encapsulate advanced analytics, process modeling, optimization and scheduling techniques has enabled significant savings and improvement in customer satisfaction for the document production outsourcing-services business. The talk will conclude with a discussion of lessons learnt and next steps to further automate and simplify the services delivery process.

An innovative software framework and toolkit for process optimization deploye...

An innovative software framework and toolkit for process optimization deploye...

An innovative software framework and toolkit for process optimization deploye...

Application of data-driven process optimization to improve a large credit card production service bureau that exhibited extremely high job size variability. Of particular interest is the fat-failed (very high variability) job size distribution and how factory processes were partitioned based on job sizes and setup requirements to significantly improve throughput, cycle time and labor utilization.

Productivity improvement solutions for manufacturing systems with highly vari...

Productivity improvement solutions for manufacturing systems with highly vari...

Productivity improvement solutions for manufacturing systems with highly vari...

Xerox has invented, tested, and implemented a novel class of operations research-based productivity-improvement offerings, trademarked LDP Lean Document Production® solutions, for the $100 billion printing industry in the United States. These solutions, which Xerox has implemented in approximately 100 sites to date, have provided dramatic productivity and cost improvements for both print shops and document-manufacturing facilities, as measured by revenue-per-unit labor-cost reductions of 20-40 percent. They have generated approximately $200M of incremental profit across the Xerox customer value chain since their initial introduction in 2000. The offerings have extended the use of operations research to small- and medium-sized print shops in the printing industry while increasing the scope of its application to large document-production facilities.

Edelman competition presentation slides

Edelman competition presentation slides

Edelman competition presentation slides

Smart Business Process Framework

Smart Business Process Framework

Smart Business Process Framework

Data-driven model-based restructuring of enterprise transaction operations

Data-driven model-based restructuring of enterprise transaction operations

Data-driven model-based restructuring of enterprise transaction operations

Abstract: A previous Interfaces (Edelman Finalist) paper [12] described the LDP Lean Document Production toolkit and work process based on operations research techniques that demonstrated significant improvements in the productivity of small to mid-sized print shops. In this paper, the extensions of the methodology to improve productivity of very large print shops are described. The printing industry is segmented into four quadrants based on resource utilization and job variability. Job variability in one of the industry segments is extremely high and is characterized by fat-tail distributions. This paper describes the extensions required to handle the applications of LDP Lean Document Production to this market segment.

Implementation of lean document production in the printing industr

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Wsc 2015 modeling customer demand in print service environments using

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AN EVENT-LOG ANALYSIS AND SIMULATION-BASED APPROACH FOR QUANTIFYING SUSTAINAB...

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IIE Lean Best Practice Award presentation (Won First Place in the competition)

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Process Wind Tunnel in Insurance

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Productivity improvement solutions for manufacturing systems with highly vari...

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