AN EVALUATION OF ORDER PICKING POLICIES FOR MAIL ORDER COMPANIES

This paper is concerned with the problem of order picking in mail order companies. Order picking is the retrieval of items from their warehouse storage locations to satisfy customer orders. Five order picking policies, strict order, batch, sequential zone, batch zone, and wave, are evaluated using labor requirements, processing time, and customer service as performance measures. A simulation model was developed to investigate these picking policies in a mail order environment. Prior research has focused on the study of individual picking policies. This study extends the prior research by evaluating multiple picking policies under varying operating conditions. The results of the study seem to indicate that (1) wave picking and batch picking perform well across the range of operating conditions considered in this study, and (2) sequential zone and batch zone picking do not perform well, especially as the order volume increases. However, the benefits and drawbacks to each picking policy must be taken into account. The key to effective implementation of an order picking system is to match the firm's business strategy, capabilities, technology, and space requirements with an order picking policy that maximizes the benefits of order picking to the firm and its customers.     

Decision‐Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems

It is critical for complex systems to effectively recover, adapt, and reorganize after system disruptions. Common approaches for evaluating system resilience typically study single measures of performance at one time, such as with a single resilience curve. However, multiple measures of performance are needed for complex systems that involve many components, functions, and noncommensurate valuations of performance. Hence, this article presents a framework for: (1) modeling resilience for complex systems with competing measures of performance, and (2) modeling decision making for investing in these systems using multiple stakeholder perspectives and multicriteria decision analysis. This resilience framework, which is described and demonstrated in this article via a real‐world case study, will be of interest to managers of complex systems, such as supply chains and large‐scale infrastructure networks.     

Managing Supply Chain Execution: Monitoring Timeliness and Correctness via Individualized Trace Data

Improvements in information technologies provide new opportunities to control and improve business processes based on real‐time performance data. A class of data we call individualized trace data (ITD) identifies the real‐time status of individual entities as they move through execution processes, such as an individual product passing through a supply chain or a uniquely identified mortgage application going through an approval process. We develop a mathematical framework which we call the State‐Identity‐Time (SIT) Framework to represent and manipulate ITD at multiple levels of aggregation for different managerial purposes. Using this framework, we design a pair of generic quality measures—timeliness and correctness—for the progress of entities through a supply chain. The timeliness and correctness metrics provide behavioral visibility that can help managers to grasp the dynamics of supply chain behavior that is distinct from asset visibility such as inventory. We develop special quality control methods using this framework to address the issue of overreaction that is common among managers faced with a large volume of fast‐changing data. The SIT structure and its associated methods inform managers on if, when, and where to react. We illustrate our approach using simulations based on real RFID data from a Walmart RFID pilot project.     

The Impact of Information System Personnel Skill Discrepancies on Stakeholder Satisfaction

System development efforts depend to a large degree upon how well information systems (IS) managers, IS specialists, and IS users work together in a project team structure. Yet, these individuals frequently work under different perceptions about matters of importance to development, management, and success. This paper introduces a framework for examining IS specialists' skill requirements from a multiple‐stakeholder perspective. Derived from discrepancy theory, the framework concedes that different stakeholders hold a variable set of expectations for IS personnel skill levels as well as a perception of skills held by IS personnel. We examine differences in expectation and performance expressed by each group and describe the impact of the discrepancy on user satisfaction, career satisfaction of IS specialists, and on job performance evaluations by IS managers. Results confirm that a discrepancy between an IS specialist's expectations of skill and their perceived skill self‐proficiency impacts career satisfaction. Similar relations hold for IS managers and users. Since different stakeholders may hold different perceptions, satisfaction of all parties becomes problematic unless a common frame of reference can be determined.     

Sensing Abnormal Resource Flow Using Adaptive Limit Process Charts in a Complex Supply Network*

Supply networks are becoming increasingly complex with multiple overlapping relationships between firms that may span across industries. Consequently, inventory management is becoming more difficult as managers have to cope with variability in the supply flows that originate from different parts of the network. Managers that quickly sense abnormal flows may intervene and adapt their inventory policies in response to system changes. In this article, we present a framework for sensing abnormal flows originating within the upstream supply network of a focal organization. Our framework combines time series modeling with process charts to identify abnormal flow patterns in the incoming supply streams. It is a flexible framework that uses off‐the‐shelf technology to provide managers with a process that can be employed for monitoring multiple individual or aggregated data streams originating within any complex system such as complex adaptive supply networks. We illustrate our framework on four years of longitudinal supply data from the second largest food bank in the United States. We identify multiple instances of abnormal supply flows and validate our results through rigorous inventory analysis as well as field‐based expert interviews. We discuss the implications of our findings for inventory management in complex supply networks, both from academic and practitioner points of view.     

Customer Order Scheduling in a General Job Shop Environment*

The primary objective of this study is to examine the performance of order-based dispatching rules in a general job shop, where the environmental factors are shop utilization and due date tightness. An order is defined as a collection of jobs that are shipped as a group—an order—to the customer, only on completion of the last job of the order. We specifically compare dispatching rules from past job-based studies to some rules adapted to encompass order characteristics. Standard flow time and tardiness measures are used, but in addition, we introduce measures that combine average performance with variation in an attempt to capture the performance of a majority of the orders processed in the shop. Of the 16 dispatching rules tested, our results show that four of the simple rules dominate the others. We also found that order-based rules perform better than their job-based counterparts. The study makes use of multivariate statistical analysis, in addition to the usual univariate tests, which can provide additional insight to managers using multiple criteria in their decision process.     

Single‐ and Multiple‐Informant Research Designs to Examine the Human Resource Management−Performance Relationship

During the last decades, many empirical studies have analysed the relationship between human resource management and firm performance. Despite the call for multiple‐rater designs, a relatively large number of researchers still rely on survey responses provided by a single informant in each organization. Single‐informant designs suffer from a number of problems, especially when the responses provided by different types of raters across firms are pooled into a single dataset prior to assessing their equivalence across raters. Using an illustration of the relationship between high performance work systems and firm performance, in this paper we observe that responses provided by managers holding different positions (human resource managers and sales managers) differ significantly and therefore pooling their responses into a single dataset may result in confusing conclusions. Furthermore, we demonstrate that differences arise in the estimated parameters when a multiple‐key‐informant approach, compared to a single‐informant design, is adopted. For these reasons, data collection using multiple key informants is recommended, based on the assumption that some raters in the firm will be more knowledgeable about the variables of interest than others.     

Contracting Under Vendor Managed Inventory Systems Using Holding Cost Subsidies

Vendor managed inventory systems are becoming increasingly popular. An important issue in implementing a vendor managed inventory scheme is the contracting terms that dictate the ownership of the inventory and the responsibility of inventory replenishment decisions. Thus the performance of a vendor managed system crucially depends on these terms and on how inventory‐related costs are shared in a supply chain. We consider a system where a manufacturer supplies a single product to a retailer who faces random demand in a competitive market. The retailer incurs a fixed cost per order, inventory holding cost, and a penalty cost for a stockout (unsatisfied demand is back‐ordered). Further, the manufacturer incurs a penalty cost when there is a stockout at the retailer and a fixed replenishment cost. We assume that the players are rational and act noncooperatively. We compare the performance of retailer managed inventory systems, where the retailer places orders and makes replenishment decisions, with vendor managed inventory systems, wherein the vendor or manufacturer makes inventory and replenishment decisions. Specifically, in the vendor managed inventory system, we propose and evaluate holding cost subsidy‐type contracts on inventories offered by the retailer to improve system performance. We evaluate this contract in the context of three widely used inventory systems—deterministic economic order quantity, continuous review (Q, r) policies, and periodic review policies—and show when such contracts may improve channel performance.     

Marketing Is from Mars,IT Is from Venus: Aligning the Worldviews for Firm Performance

A typical firm is operated by multiple functional managers who may collaborate as well as compete to achieve firm performance. In the digital age, firm performance is essentially customer‐dependent and technology‐dependent, with both marketing and information technology (IT) playing key roles. Unfortunately the two functions often have very different worldviews. We show how these differences can damage firm performance, and suggest ways to mitigate this damage. We build a worldview difference model, synthesized from multiple disciplines. The model is tested using both matched and nonmatched observations from marketing and IT managers, and is analyzed with hierarchical linear models using both perceptual and objective firm performance data over a 4‐year period. We find that differences between the beliefs and perceptions of marketing managers and IT managers generate a negative impact on firm performance, and suggest appropriate technology‐culture associations to effectively align their worldviews for firm performance. To improve firm performance, a cross‐functional appreciation for market and technology drivers can be achieved by making marketing managers more learning‐oriented and by providing IT managers a culture that is congruent with technology.     

Revenue Management in Order‐Driven Production Systems

This article investigates the effectiveness of a tactical demand‐capacity management policy to guide operational decisions in order‐driven production systems. The policy is implemented via a heuristic that attempts to maximize revenue by selectively accepting or rejecting customer orders for multiple product classes when demand exceeds capacity constantly over the short term. The performance of the heuristic is evaluated in terms of its ability to generate a higher profit compared to a first‐come‐first‐served (FCFS) policy. The policies are compared over a wide range of conditions characterized by variations in both internal (firm) and external (market) factors. The heuristic, when used with a Whole Lot order‐processing approach, produces higher profit compared to FCFS when profit margins of products are substantially different from each other and demand exceeds capacity by a large amount. In other cases it is better to use the heuristic in conjunction with the Split Lot order‐processing approach.     

REDISTRIBUTION,PORK, AND ELECTIONS

Why might citizens vote against redistributive policies from which they would seem to benefit? Many scholars focus on ‘wedge’ issues such as religion or race, but another explanation might be geographically‐based patronage—or pork. We examine the tension between redistribution and patronage with a model that combines partisan elections across multiple districts with legislation in spatial and divide‐the‐dollar environments. The model yields a unique equilibrium that describes the circumstances under which poor voters support right‐wing parties that favor low taxes and redistribution, and under which rich voters support left‐wing parties that favor high taxes and redistribution. The model suggests that one reason standard tax and transfer models of redistribution often do not capture empirical reality is that redistributive transfers are a less efficient tool for attracting votes than are more targeted policy programs. The model also underlines the central importance of party discipline during legislative bargaining in shaping the importance of redistribution in voter behavior, and it describes why right‐wing parties should have an advantage over left‐wing ones in majoritarian systems.     

The Effect of Distribution Processes on Replenishment Lead Time and Inventory

We investigate the interrelationship of distribution center picking policies and supply chain inventory performance. In particular, we show how the picking sequence in the upstream supply chain link affects the inventory levels of items being replenished to a downstream link for a common “ship‐when‐full” trailer dispatching policy. Perturbing the picking sequence affects items’ inventory levels asymmetrically which causes the aggregate system inventory to vary. We separate the items in replenishment into those units in transit and those awaiting shipment from the upstream distribution step: we call the latter the residual replenishment. We show that the process governing aggregate residual replenishment is Markov and has a stationary distribution that is discrete uniform. Computing the item‐level residual distribution is intractable and so we develop analytical models from which we derive hypotheses for the effectiveness of stable vs. random picking sequences, how item residual replenishment varies with stable picking sequences, and how the aggregate inventory level changes with picking sequence. These suggest a heuristic sequencing algorithm for minimizing inventory, which performs well in simulation tests over a large testbed of parameter sets.     

Order batching in a pick-and-pass warehousing system with group genetic algorithm

An order batching policy determines how orders are combined to form batches. Previous studies on order batching policy focused primarily on classic manual warehouses, and its effect on pick-and-pass systems has rarely been discussed. Pick-and-pass systems, a commonly used warehousing installation for small to medium-sized items, play a key role in managing a supply chain efficiently because the fast delivery of small and frequent inventory orders has become a crucial trading practice because of the rise of e-commerce and e-business. This paper proposes an order batching approach based on a group genetic algorithm to balance the workload of each picking zone and minimize the number of batches in a pick-and-pass system in an effort to improve system performance. A simulation model based on FlexSim is used to implement the proposed heuristic algorithm, and compare the throughput for different order batching policies. The results reveal that the proposed heuristic policy outperforms existing order batching policies in a pick-and-pass system.     

Multidimension scaling for multiobjective policies

This paper develops and expands the use of multidimension scaling techniques (MDSCAL) as applied in the two separate fields of psychological testing and archaeology to the problem of multiple criteria decision making. Other work by the author published elsewhere shows that it is feasible to use MDSCAL for drawing maps of separate policies using very weak input information from which deductions as to most preferred and least preferred policies may be drawn. An application of this method is made, to show its use and a comparison made with the utility approach. The final, and main, part of the paper examines the robustness of the method for both deterministic and probabilistic input criteria. In this examination it is seen that the mapping method performs very well in picking up extremes of preference even under severe tests of robustness.     

Selection system orientations as an explanation for the differences between dual leaders of the same organization in their perception of organizational performance

We investigate to what extent individual managers operating in a dual leadership structure have different perceptions of how well his/her organization is performing. Using selection system theory we develop hypotheses on the relationships between a leader’s selection system orientation and his/her perception of performance along multiple dimensions: market performance, expert performance and peer performance. The hypotheses are tested using dyadic data from 59 organizations in the performing arts led by two—hierarchically equivalent—managers. Our results show that dual leaders’ differences in terms of market orientation and expert orientation relate positively to perceived performance differences along the same dimensions. This relationship is not found with respect to peer selection orientation. Generally, the relationship between orientation differences and perceived performance differences is stronger if the process of interpreting signals to construct a perception of organizational performance leaves more room for equivocality and uncertainty.     

POM Forum: Transfer of Changing Production Know‐How

Even with the rich literature on knowledge management, we still don't know enough about how the rate of change in production‐know‐how affects the choice of mechanisms for its transfer. Codifying tacit know‐how helps, but codification becomes more challenging as the know‐how changes more frequently. Transfer of tacit know‐how becomes much more complicated when it changes often. We need more research in this area, particularly to help production and operations managers who must ultimately use the new know‐how and change their companies' production processes. The paper suggests a framework as a step in that direction. The framework focuses on the interplay between the level of codification and the rate of change of production know‐how, and identifies four zones for classifying production know‐how: “slow and codified,” “slow and tacit,” “fast and codified,” and “fast and tacit.” Examples from McDonald̂s, Club Med, Intel, and AOL are used to illustrate primary transfer mechanisms for each zone (manuals and systems, people, joint‐development, and projects, respectively). Appropriate absorptive capacities in the production units for each zone are also identified. Since the ultimate responsibility of operations managers is to improve (i.e., change) their production know‐how as fast as possible, they would be wise to adopt policies that are closer to those suited for the “fast and codified” zone. Intel and Toyota show good models.     

双旋转货架拣货作业优化设计

本文讨论了由一个拣货员负责的双旋转货架系统,目标是寻找一种最优拣货顺序使得总拣货时间。该问题被证明为强NP-难问题,文章提出了启发式算法寻找最优拣货顺序,并对相关模型及算法进行模拟测试以证明其有效性,为方法选择与应用提供了依据。     

ROBUSTNESS OF VARIOUS PRODUCTION CONTROL POLICIES IN SEMICONDUCTOR MANUFACTURING

This paper compares several different production control policies in terms of their robustness to random disturbances such as machine failures, demand fluctuations, and system parameter changes. Simulation models based on VLSI wafer fabrication facilities are utilized to test the performance of the policies. Three different criteria, namely, the average total WIP, the average backlog, and a cost function combining these measures, are used to evaluate performance. Among the policies tested, the Two‐Boundary Control policy outperforms the others.     

An Evaluation of Routing and Volume-based Storage Policies in an Order Picking Operation

Order picking, the assembly of a customer's order from items in storage, is an essential link in the supply chain and is the major cost component of warehousing. The critical issue is to simultaneously reduce the cost and increase the speed of the order picking activity. This study departs from the limited prior research that focused on either routing of workers or storage of warehoused items. The main objectives are to (1) evaluate various routing heuristics versus an optimal routine in a volume-based storage environment, (2) propose several methods of implementing volume-based storage, and (3) examine the interaction of the routing and storage policies under different operating conditions of pick list size and demand skewness. The experimental results show statistically significant differences in the mean route distance for the routing policies, storage policies, and their interactions. Further testing indicates that the choice of certain routing and storage policies in combination can result in increased picking efficiency.     

A Diagnostic Tree for Improving Production Line Performance

Improving performance of production systems is a critical but often unstructured activity. To help managers convert ad hoc or trial & error improvement efforts into efficient and systematic reviews, we develop a diagnostic tree which decomposes a performance improvement objective into successively more concrete sub‐objectives and finally into potential improvement strategies. Based on principles from the Operations Management literature, this tree is structured to enable a non‐specialist to better understand the links between corrective actions and performance. It also provides an important foundation for a principles‐based knowledge management system that couples the decision tree with a search engine for locating relevant documents within an intranet.