Operational Competitiveness Rating Research Articles

Measuring the effect of a new point of sale system on the performance of drugstore operations

A new electronic point of sale (POS) system was deployed by a Hong Kong drugstore-chain in eight of its drugstores as the first stage of a company-wide introduction of POS automation. The management wanted to know if the new system had a significant impact on the performances of the drugstores where the new POS system was deployed. We explain in this paper the computation of ratings that gauge the relative performances of the drugstores using a new procedure called operational competitiveness rating analysis (OCRA). We used these ratings to determine whether the drugstore operations improved significantly after the deployment of POS. A full discussion of OCRA's development and its computational procedure is also provided. Scope and purpose The aim of this paper is to demonstrate, using a new performance measurement procedure called operational competitiveness rating analysis (OCRA), how the impact of a new electronic point of sale (POS) system on the performance of a drugstore can be gauged. A case is presented involving a drugstore-chain in Hong Kong. Data on costs and revenue were collected, before and after the deployment of a POS system, from eight of the drugstores of the chain, spanning a period of 18 months. Computation of relative performance ratings for the drugstores using OCRA is explained. The drugstores were ranked by their performance ratings and a rank test was applied to determine if the average rank was significantly higher after the deployment of the POS system. It was evident that while there was a general improvement in the performance of the drugstores over the 18-month period, performance improved significantly after the deployment of the POS system. The paper also provides a full description of the development and computational procedure of the OCRA approach, and concludes with a brief discussion of its desirable properties as a performance measurement tool.

A caveat on the measurement of productive efficiency

The correspondence between used performance measures and enterprise objectives, such as profit maximization and cost minimization, is fundamental for manufacturing companies. This paper identifies, and critically examines, a minimal set of relevant properties that a productivity index needs to satisfy to rightly assess performance development of a decision-making unit. Commonly applied and suggested productivity measurement techniques, such as partial efficiencies, total factor productivity (TFP), index number approaches, integrated partial efficiencies and operational competitiveness ratings, are analyzed in order to assess the alignment with superior objectives. There is a considerable spread in the results of this class of models and the interpretation may prove difficult or misleading. As these apparently less complicated productivity measures increasingly are employed as a component in evaluation of manufacturing efficiency, the question is of high managerial relevance. In particular, the paper points out inconsistencies with properties related to commensurability, monotonicity, and implications of maximizing behavior. Based on this viewpoint, issues such as the consistency with profit maximization will be shown extra interest. The paper also provides a critique of previous work in non-parametric efficiency analysis, where properties have been postulated or based on other arguments. The findings suggest that there is no globally superior measurement technique to be found in this class and that care should be taken when evaluating managerial performance not to penalize rational behavior.

Comparison of three modern multicriteria decision-making tools

The requirements, conditions and values encompassing a decision-making situation determine the decision maker's feasible alternative solutions and circumscribe the best solution. Various approaches have been suggested in the literature to identify the best solution for a class of problems called multicriteria decision making (MCDM). MCDM problems may be deterministic or non-deterministic. These approaches employ different methodologies and usually produce dissimilar solutions. Therefore, it is worthwhile to examine and compare the available MCDM methods. This paper focuses mainly on deterministic MCDM situations and methods and only a brief reference is made to their non-deterministic counterparts. We introduce a new performance measurement method called operational competitiveness rating (OCRA) and discuss its use as a deterministic MCDM tool. We demonstrate OCRA's application to a process selection problem that is adapted from an actual situation that involves qualitative data. W e compare the results obtained by OCRA with the results of analytic hierarchy process and data envelopment analysis to understand their similarities and differences. The comparison of these three non-parametric performance measurement tools provides some useful insights into their behaviour in actual MCDM situations.

Measuring the performance of operations of Hong Kong's manufacturing industries

The relative operational performance of Hong Kong's manufacturing industries is measured and analyzed for the period from 1987 to 1993. The measurement technique used is the recently developed operational competitiveness rating (OCRA) procedure. The comparison of the overall operational performance of Hong Kong's nine manufacturing industry groups is based on the OCRA computations of relative resource consumption and revenue generation performance. The implications of OCRA results in terms of industry performance trends are discussed and strategic issues are reviewed.

Competitive analysis of manufacturing plants: An application to the US processed food industry

We present a model-based approach for competitive analysis of manufacturing plants. As part of this approach, we propose the application of Operational Competitiveness Ratings Analysis (OCRA) to measure the competitiveness of plants in terms of their relative inefficiency. We then present a conceptual framework to classify and identify the drivers of plant competitiveness in terms of decisions related to plant structure and infrastructure. Finally, we demonstrate the application of this model-based approach to conduct competitive analysis of plants in the US processed food industry.

Decision-making and performance measurement models with applications to robot selection

Many advanced manufacturers use robots extensively to perform repetitious, difficult, and hazardous tasks with precision. Robots improve quality and productivity dramatically if deployed properly. The process of selecting the most suitable robot among many alternatives involves robots' performance in a number of key areas. Various quantitative methods have been proposed as an aid to selection decision on the choice of robots. This paper demonstrates the use of and compares some of the current multi-attribute decision-making (MADM) and performance measurement methods through a robots selection problem borrowed from Khouja (Khouja M. The use of data envelopment analysis for technology selection. Comput Ind Eng 1995;28:123–132). Particular emphasis is placed on a performance measurement procedure called operational competitiveness rating (OCRA) and an MADM tool called technique for order preference by similarity to ideal solution (TOPSIS). A rank-correlation test shows that the methods considered produce similar rankings for the robots. The final selection is made on the basis of the rankings obtained by averaging the results of OCRA, TOPSIS, and a utility model.

Performance measurement in government services

Summarizes a study that was carried out on behalf of a government department in Hong Kong, which provides service to public facilities. The department’s overall performance and the performance of its key divisions were examined as part of an investigation to determine whether they were in a position to compete with the private sector when the government ended the department’s monopoly in this particular sector. The department’s performance profile for a period of 16 months was constructed and the performances of two key divisions were compared. All performance measurements were made using a recent method called operational competitiveness rating (OCRA) analysis.

Measurement of the performance of an investment bank using the operational competitiveness rating procedure

The Hong Kong branch of an international investment bank hired additional staff in anticipation of increased business activity that eventually did not quite materialize and management was concerned about the effect of that decision on the bank's overall performance profile. This paper summarizes a study we carried out to address two related questions using only the available data at the time: (1) what is the direction of the overall performance trend and (2) how serious has the impact of the incremental costs of hiring additional staff been on the Bank's overall performance? The discussion in this paper focuses on the construction of the bank's performance profile using a new performance measurement method called operational competitiveness rating analysis (OCRA). The paper also includes comparisons of OCRA and data envelopment analysis (DEA) ratings and profit scores to show the validity support among the three approaches as well as underscore their differences.

Process selection with multiple objective and subjective attributes

In the manufacturing sector, process selection is an important strategic consideration for improving competitiveness. We propose two simple and effective methods for process selection. After providing a detailed description of the general process selection problem with particular emphasis on attribute types, objective attribute values, subjective ratings and importance weights, we review an existing Multiple-Attribute Decision Making (MADM) method called TOPSIS, a Technique for Order Preference by Similarity to Ideal Solution (alternative) and describe briefly an operational performance measurement procedure called Operational Competitiveness RAting (OCRA). We show that these two methods are both distance based and strongly interrelated, and that they can be used for process selection decisions as well as operational performance measurement. Focusing on process selection, we demonstrate in detail the two methods' application and interrelationship through two examples. The selection decision in the examples is made on the basis of objective values of the attributes and their subjective ratings.

On the equivalence of operational performance measurement and multiple attribute decision making

Measurement of operational performance and decision making under multiple attributes are shown to be essentially the same process. A recent operational performance measurement (OPM) procedure called OCRA (operational competitiveness rating) and a multiple attribute decision making (MADM) method called TOPSIS (technique for order preference by similarity to ideal solution) are shown to produce ratings that are identical up to a linear transformation. Further investigations into OPM and MADM lead to their equivalence. The equivalence of the two methods can open up new research and application possibilities in both productivity analysis and MADM. Reviews of both the non-parametric approach that leads to the OC RA procedure and the TOPSIS method are provided, new perspectives on these methods are introduced and examples offered.

Operational competitiveness analysis on software development

The focus of this study is the application of a non-parametric model called operational competitiveness rating analysis (OCRA), to obtain ratings that gauge the relative operational performance of the application software development teams of a large bank in Hong Kong. The computed ratings would be the basis of important management decisions relating to the connection between personnel performance and benefits. This application of OCRA requires the values of resources consumed and outputs generated. Cost figures were used to measure the teams' resource consumption. The value of the teams' software output was measured by function point analysis. The performance ratings obtained by OCRA are compared with data envelopment analysis (DEA) ratings and ratio scores. Comments are offered on the implementation of the proposed approach.

Operational competitiveness ratings of production units

AbstractThe operational competitiveness of a production unit (PU) where resources are transformed into outputs of goods and services is a very important component of its overall competitiveness. A PU's operations are comprised of a number of purposeful activities that consume resources and generate rewards. The efficiency with which these activities are carried out determines the PU's operational competitiveness. A reliable rating system is prerequisite in order to control and improve operational competitiveness. In the present paper we adopt a multi‐activity view of the concept of operational competitiveness and develop a procedure to calculate ratings to help gauge the relative operational competitiveness of a set of PUs. The procedure is based on a nonparametric model but its implementation involves simple ratio‐type computations. The principal criteria for the procedure and the ratings resulting from its application are intuitive appeal, transparency, ease of computation, robustness and ability to reflect the prevailing managerial perspectives and competitive priorities. We demonstrate the application of the procedure to gauge the relative operational competitiveness of a major chartered bank's branch personnel.