Rogelio Oliva

Managing the transition from products to services

Management literature is almost unanimous in suggesting to manufacturers that they should integrate services into their core product offering. The literature, however, is surprisingly sparse in describing to what extent services should be integrated, how this integration should be carried out, or in detailing the challenges inherent in the transition to services. Reports on a study of 11 capital equipment manufacturers developing service offerings for their products. Focuses on identifying the dimensions considered when creating a service organization in the context of a manufacturing firm, and successful strategies to navigate the transition. Analysis of qualitative data suggests that the transition involves a deliberate developmental process to build capabilities as firms shift the nature of the relationship with the product end‐users and the focus of the service offering. The report concludes identifying implications of our findings for further research and practitioners.

Cutting Corners and Working Overtime: Quality Erosion in the Service Industry

The erosion of service quality throughout the economy is a frequent concern in the popular press. The American Customer Satisfaction Index for services fell in 2000 to 69.4%, down 5 percentage points from 1994. We hypothesize that the characteristics of services--inseparability, intangibility, and labor intensity--interact with management practices to bias service providers toward reducing the level of service they deliver, often locking entire industries into a vicious cycle of eroding service standards. To explore this proposition we develop a formal model that integrates the structural elements of service delivery. We use econometric estimation, interviews, observations, and archival data to calibrate the model for a consumer-lending service center in a major bank in the United Kingdom. We find that temporary imbalances between service capacity and demand interact with decision rules for effort allocation, capacity management, overtime, and quality aspirations to yield permanent erosion of the service standards and loss of revenue. We explore policies to improve performance and implications for organizational design in the service sector.

Model calibration as a testing strategy for system dynamics models

System dynamics models are becoming increasingly common in the analysis of policy and managerial issues. The usefulness of these models is predicated on their ability to link observable patterns of behavior to micro-level structure and decision-making processes. This paper posits that model calibration––the process of estimating the model parameters (structure) to obtain a match between observed and simulated structures and behaviors––is a stringent test of a hypothesis linking structure to behavior, and proposes a framework to use calibration as a form of model testing. It tackles the issue at three levels: theoretical, methodological, and technical. First, it explores the nature of model testing, and suggests that the modeling process be recast as an experimental approach to gain confidence in the hypothesis articulated in the model. At the methodological level, it proposes heuristics to guide the testing strategy, and to take advantage of the strengths of automated calibration algorithms. Finally, it presents a set of techniques to support the hypothesis testing process. The paper concludes with an example and a summary of the argument for the proposed approach.

A comprehensive analytical approach for policy analysis of system dynamics models

Formal tools to link system dynamics models structure to the system modes of behavior have recently become available. In this paper, we aim to expand the use of these tools to perform the models policy analysis in a more structured and formal way than the exhaustive exploratory approaches used to date. We consider how a policy intervention (a parameter change) affects a particular behavior mode by affecting the gains of particular feedback loops as well as how it affects the presence of that mode in the variable of interest. The paper demonstrates the utility of considering both of these aspects since the analysis provides an assessment of the overall impact of a policy on a variable and explains why the impact occurs in terms of structural changes in the model. Particularly in the context of larger models, this method enables a much more efficient search for leverage policies, by ranking the influence of each model parameter without the need for multiple simulation experiments.

Tradeoffs in responses to work pressure in the service industry

This publication contains reprint articles for which IEEE does not hold copyright. Full text is not available on IEEE Xplore for these articles.

Developing operational understanding of service quality through a simulation environment

Purpose – The purpose of this paper is to articulate the challenges of learning and improving in service delivery systems – that present managers with imperfect information, confounded variables, and tightly coupled interactions between operational and psychological factors – and present a simulator to assist managers to overcome these challenges.Design/methodology/approach – After reviewing the literature on “learning from simulations” and the main challenges of learning in a service environment, the paper presents the assumptions underlying the service quality management simulator, its interface, and protocols to use it that have proven effective.Findings – It is possible to assist managers to develop operational understanding – what to do, when and how much of it to do – about the drivers of service quality using a simulation environment.Research limitations/implications – In its present form, the simulator only takes a functional definition of service quality and captures the relationships in a busine...

Death Spirals and Virtuous Cycles

While the productivity and quality of manufactured products steadily improve, service sector productivity lags and quality has fallen. Many service organizations fall into “death spirals” in which pressure to boost throughput and control costs leads to worker burnout and corner cutting, lowering service quality , raising costs while revenue falls, forcing still greater cuts in capacity and even lower quality. We present a formal model to explore the dynamics of service delivery and quality, focusing on the service quality death spiral and how it can be overcome. We use the system dynamics modeling method as it is well suited to dynamic environments in which human behavior interacts with the physics of an operation, and in which there are multiple feedbacks connecting servers, managers, customers, and other actors. Through simulations we demonstrate that major recurring problems in the service industry—erosion of service quality, high turnover, and low profitability—can be explained by the organization’s internal responses to work pressure . Although the reinforcing feedbacks can operate as virtuous as well as vicious cycles, the system is biased toward quality erosion by basic asymmetries and nonlinearities. We show how, with the right mix of policies, these same feedbacks can become virtuous cycles that lead to higher employee, customer satisfaction and additional resources to invest in still greater service quality improvement.

Drift and Adjustment in Organizational Rule Compliance: Explaining the Regulatory Pendulum in Financial Markets

This article integrates research on rule development, compliance, and organizational change to model rule development and compliance in organizations, using causal-loop modeling from system dynamics to articulate explicitly a few key underlying processes. We focus on financial markets as a case area, suggesting that recurring regulatory problems in financial markets in the United States over the past 60 years, although differing in specifics, are structurally similar. At the heart of the model is the tension between production goals that focus on short-term, certain, salient benefits and required adherence to production-constraining rules that attempt to mitigate long-term, uncertain, nonsalient risks. It describes systemically how organizations attend to rules depending on the nature of the benefits of production compared with those of rule compliance. The model captures the operative mechanisms responsible for the development of pressures for production and for rule compliance in organizations, providing a structural explanation both for problem-prone organizations characterized by erosion of standards and increased violations and for organizations following rules more reliably. Drawing on studies of institutional work, we conclude by suggesting research on how agency, through strategic and tactical choice, potentially modifies structure in rule compliance.

Learning to Compete: Transforming Firms in the Face of Radical Environment Change

Over the last decade, Latin American economies and companies have witnessed substantial changes as their economies have been reformed and opened to world markets. Firms that have adapted to these changes may have useful lessons to offer to companies in other countries as they face economic transformation and expanding competition.

Estimating Retail Demand with Poisson Mixtures and Out-of-Sample Likelihood

Estimation of retail demand is critical to decisions about procuring, shipping, and shelving. The idea of Poisson demand process is central to retail inventory management and numerous studies suggest that negative binomial (NB) distribution characterize retail demand well. In this study we reassess the adequacy of estimating retail demand with the NB distribution. We propose two Poisson mixtures – the Poisson-Tweedie (PT) family and the Conway-Maxwell Poisson (CMP) distribution – as generic alternatives to the NB distribution. Based on the principle of likelihood and information theory, we adopt out-of-sample likelihood (OSL) as a metric for model selection. We test the procedure on consumer demand for 580 SKU-store sales datasets. Overall the PT family and the CMP distribution outperform the NB distribution for 70% of the tested samples. As a general case of the NB model, the PTF family has particularly strong performance for datasets with relatively small means and high dispersion. Our finding carries useful implications for researchers and practitioners who seek for flexible alternatives to the oft-used NB distribution in characterizing retail demand.