Managing Learning and Turnover in Employee Staffing

We study the employee staffing problem in a service organization that uses employee service capacities to meet random, non-stationary service requirements. The employees experience learning and turnover on the job, and we develop a Markov Decision Process (MDP) model that explicitly represents the stochastic nature of these effects. Theoretical results are developed that show the optimal hiring policy is of a state-dependent "hire-up-to" type, similar to the inventory "order-up-to" policy. This holds for discounted-costs MDP's under both finite and infinite planning horizons. We also develop structural properties of the optimal policy to facilitate computation of the optimal hiring numbers. For two important special cases of the general model, we prove the optimality of a myopic policy under both stationary and stochastically increasing service requirements. Moreover, we show that in these two cases, when service requirements are k-periodic, it is sufficient to solve a k-period MDP problem with appropriate end-of-horizon cost function. When general, non-stationary service requirements are present, we prove the existence of a one-sided "smoothing effect" of the optimal hire-up-to-levels. Numerical results show that the use of state-dependent hire-up-to policies may offer significant cost savings over simpler hiring policies. In particular, our results show that when employee capacity increase due to learning is substantial and flexible incremental capacity (overtime) is tight, a fully state-dependent policy out-performs a policy that hires only on the basis of the total number of employees in the system. Our problem formulation and results suggest natural connections to the classic results in inventory literature. We also discuss many of the connections and distinctions in the paper.

Managing Learning and Turnover in Employee Staffing

We study the employee staffing problem in a service organization that uses employee service capacity to meet random, nonstationary service requirements. The employees experience learning and turnover on the job, and we develop a Markov Decision Process (MDP) model which explicitly represents the stochastic nature of these effects. Theoretical results show that the optimal hiring policy is of a state-dependent “hire-up-to” type, similar to an inventory “order-up-to” policy. For two important special cases, a myopic policy is optimal. We also test a linear programming (LP) based heuristic, which uses average learning and turnover behavior, in stationary environments. In most cases, the LP-based policy performs quite well, within 1% of optimality. When flexible capacity—in the form of overtime or outsourcing—is expensive or not available, however, explicit modeling of stochastic learning and turnover effects may improve performance significantly

DETERMINATION OF THE OPTIMAL CONTROLLABLE KEY INDICATOR OF CALL CENTER IN ORDER TO INCREASE EFFICIENCY FOR GENERATING INCOME

This paper focuses on call centers, which have become a common means of communication with potential customers in various companies. Specifically, this paper analyzes call center data and the importance of assessing key indicators for evaluating call center performance. The questions this paper addresses are the criteria for evaluating call center quality and the methods for analyzing call center data. Previous research has shown the significance of call centers as the "face of the company," with the quality of their work reflecting how efficiently a company will serve its customers ' requests in the future. The main goal of this paper is to fill a gap in previous research by identifying the main controlled key indicator for call center quality and to suggest ways to improve efficiency. By using analytical methods to examine call center data, this paper identifies the most important criteria for call center quality and provides recommendations for enhancing service quality. The main findings of this paper show the importance of call center operator performance in determining call center performance which affects company revenue. By evaluating key indicators such as the number of operators, this paper demonstrates how call centers can reduce service costs and improve efficiency. During the analysis using call center data for two years, it turned out that the company had expenses 1/3 of the total amount of maintenance compared to the previous year, which is not effective in terms of economy. Operational planning has a direct impact on operators’ costs and the main cost component is the hourly cost of operators. If optimal planning turns out to be at least 10% better than the arrangement set in the call center, company will save a good amount. The significance of this paper lies in its potential to improve the quality of service in call centers and its contribution to the field of customer service management. By providing insight into the importance of call center efficiency, this research offers recommendations for predicting the optimal number of operators to improve the customer experience with reducing service costs

Executive Quirks in Operational Decisions

We ask if corporate executives have fixed effects (quirks) that explain perational decisions made in firms, independent of firm effects. We replicate the approach in Bertrand et al. (2003), solving the empirical challenge of distinguishing firm and executive effects by constructing a dataset of executives who move from one firm to another. We find that executives indeed exhibit fixed effects separate from firm effects. These quirks are large, although there is a wide dispersion of sizes among executives. The quirks also come in themes, such as a bias toward investing in human rather than physical capital. We also find that quirks mostly lead to inefficient outcomes for firms. Finally, we link quirks to observable characteristics of executives, such as their age or education. We conclude by arguing for an increased focus on individual effects in operations management research.operations management; executive fixed effects; firm fixed effects; agency

Cost of High Employees Turnover Rate in Oil Refinery Industry of Pakistan

Employee’s turnover is the challenging issue for the organizations and has always negative impact on the organizations. When employees leave their company, it does not only reduce the performance of the organizations but lessen the productivity and profitability of the organizations as well. It also increases the management difficulties and hiring cost for the new people to fill the vacant positions and train them. It has been observed that employee turnover, especially in oil refinery industry of Pakistan, is becoming a problem which costs a lot of money, efforts and energy. This problem might be a major obstacle for HR professionals in formulation of their HR policies. Major factors involve in employees turn over include: performance appraisal system, organizational policies and their implementations, working environment, job growth, bosses behaviors, benefits, compensation, economic condition of the company and performance of the company, etc. This study aims to identify the cost on employee’s turnover in oil refineries of Pakistan and to suggest some employee retention strategies within the oil refineries of Pakistan. Data was collected mainly from secondary sources through the use of internet searching and downloading the research papers related to the topic of the paper. The author recommend that oil refineries of Pakistan need to review their policies to retain their valuable employees and save their cost on employees turnover. Keywords: Cost on employees turn over, Oil refineries of Pakistan, working environment, compensation

The Impact Assessment Of Demographic Factors On Faculty Commitment In The Kingdom Of Saudi Arabian Universities

Organizational commitment is perceived as an attitude of association to the organization by an employee, which leads to particular job-related behaviors such as work absenteeism, job satisfaction and turnover intensions. Turnover is the ratio of the number of workers that had to be replaced in a given time period to the average number of workers. Employee turnover is affected by job dissatisfaction, errors in employee selection, and poor management. As a performance indicator, turnover should be understood by management and leadership of the company.  Turnover in the teaching profession can have important consequences for universities and students, including the financial and time costs of filling positions, disruption of curricular continuity, and difficulty in maintain a cohesive school environment.  This study examines the impact assessment of personal factors on organizational commitment which leads to turnover intentions. The results indicated that the universities in KSA are not stipulating effective measure to retain their worthy and highly qualified resources. Some of the preventive actions include management training in order to capture warning of job dissatisfaction and periodic workplace evaluation of satisfaction, an open door policy style of management, and uphold strict hiring standards. In order to keep costs down, a streamline and efficient human resource program is suggested. Furthermore, organizations may gain more by attaching employees, increasing their investments, and enhancing their obligations to fulfill their goals

Flexible Service Capacity: Optimal Investment and the Impact of Demand Correlation

We consider a firm that provides multiple services using both specialized and flexible capacity. The problem is formulated as a two-stage, single-period stochastic program. The firm invests in capacity before the actual demand is known and optimally assigns capacity to customers when demand is realized. Sample applications include a car rental company\u27s use of mid-sized cars to satisfy unexpectedly high demand for compact cars and an airline\u27s use of business-class seats to satisfy economy-class demand. We obtain an analytical solution for a particular case, when services may be upgraded by one class. The simple form of the solution allows us to compare the optimal capacities explicitly with a solution that does not anticipate flexibility. Given that demand follows a multivariate normal distribution, we analytically characterize the effects of increasing demand correlation on the optimal solution. For the case with two customer classes, the effects of demand correlation are intuitive: Increasing correlation induces a shift from flexible to dedicated capacity. When there are three or more classes, there are also adjustments to the resources not directly affected by the correlation change. As correlation rises, these changes follow an alternating pattern (for example, if the optimal capacity of one resource rises, then the optimal capacity of the adjacent resource falls). These results make precise conjectures based on numerical experiments that have existed in the literature for some time

Workforce planning for practical training programs via multi-criteria decision making

Sektörde eğitim ve takiben yapılan işe alım programları, turizm ve diğer hizmet odaklı sektörler için verilen eğitimlerin özünü oluşturmaktadır. Ancak bu programlar belirli süreler aldığı için katılım yapan öğrenci/yeni mezunlar bir başlangıç yaptıktan sonra çeşitli sebeplerle programdan ayrılarak sonunu getirmeyebilmektedir. Belirli bir işgücü yaratan bu öğrencilerin ani ayrılışları eğitimin verildiği kurumun işgücüne de zarar verebilmekte olup, kurum yöneticilerinin sektörde eğitim programları için öğrenci alım kararlarını verirken planlı olmayan öğrenci kayıp unsurunu da dikkate almaları gerekmektedir. Bu çalışmada hizmet odaklı bir sektörde, ilgili bölümlerin mezunlarının katıldığı iki aşamalı özel bir eğitim programı için bir optimizasyon modeli oluşturulması hedeflenmiştir. İlgili kurumdaki yöneticiler hangi bölümden kaç tane yeni mezunu programa katacaklarına, planlı olmayan ayrılmalar ve işgücü kapasitesi kısıtlarını da göze alarak karar vermek durumundadır. Problemin çözümü için çok ölçütlü karar verme yöntemlerinden hedef programlama tekniğini kullanılmış ve sonuçlar analiz edilerek insan kaynakları yöneticileri için öngörüler elde edilmesi amaçlanmıştır.Practical training programs constitute the essence of education for tourism and other service-oriented sectors. However, these programs take considerable time to finish, and participating students/new graduates may leave the program for a variety of reasons without finishing. Attrition can harm the overall workforce of the related institution, and it is necessary for the managers to take this factor into consideration for recruitment of these programs. In this study, it was aimed to establish an optimization model for a two-stage practical education program in which the recruits are new graduates of related departments aiming to work in a service-oriented sector. Managers in the relevant institution must decide how many new graduates to add to the program, planning for the attrition and labor capacity constraints. The goal programming technique was used for the solution of the problem and it was aimed to obtain managerial insights for the human resources management policies.No sponso

Proactive Customer Service: Operational Benefits and Economic Frictions

Problem Definition: We study a service setting where the provider has information about some customers' future service needs and may initiate service for such customers proactively, if they agree to be flexible with respect to the timing of service delivery. Academic / Practical Relevance: Information about future customer service needs is becoming increasingly available through remote monitoring systems and data analytics. However, the literature has not systematically examined proactive service as a tool that can be used to better match demand to service supply when customers are strategic. Methodology: We combine i) queueing theory, and in particular a diffusion approximation developed specifically for this problem that allows us to derive analytic approximations for customer waiting times, with ii) game theory, which captures customer incentives to adopt proactive service. Results: We show that proactive service can reduce customer waiting times, even if only a relatively small proportion of customers agree to be flexible, the information lead time is limited, and the system makes occasional errors in providing proactive service - in fact we show that the system's ability to tolerate errors increases with (nominal) utilization. Nevertheless, we show that these benefits may fail to materialize in equilibrium because of economic frictions: customers will under-adopt proactive service (due to free-riding) and over-join the system (due to negative congestion-based externalities). We also show that the service provider can incentivize optimal customer behavior through appropriate pricing. Managerial Implications: Our results suggest that proactive service may offer substantial operational benefits, but caution that it may fail to fulfill its potential due to customer self-interested behavior