Tzvi Raz

An empirical analysis of the relationship between project planning and project success

Abstract This paper examines the relationship between project planning efforts and project success. Three planning aspects are considered (requirements definition, development of technical specifications, and project management processes and procedures), along with three perspectives on project success (end-user, project manager, and contracting office). The study is based on data from more than a hundred defense research and development projects (aimed at the development of weapon systems and support equipment) performed in Israel and includes an analysis of the statistical correlation between the two sets of variables. The findings suggest that project success is insensitive to the level of implementation of management processes and procedures, which are readily supported by modern computerized tools and project management training. On the other hand, project success is positively correlated with the investment in requirements’ definition and development of technical specifications.

Use and benefits of tools for project risk management

Abstract Risk management is one of the key project management processes. Numerous tools are available to support the various phases of the risk management process. We present the results of a study designed to identify the tools that are most widely used and those that are associated with successful project management in general, and with effective project risk management in particular. The study is based on a questionnaire administered to a sample of project managers from the software and high-tech industries. The response data was analyzed in order to find which tools are more likely to be used in those organizations that report better project management performance and in those that value the contribution of risk management processes.

Risk management, project success, and technological uncertainty

In times of increased competition and globalization, project success becomes even more critical to business performance, and yet many projects still suffer delays, overruns, and even failure. Ironically, however, risk management tools and techniques, which have been developed to improve project success, are used too little, and many still wonder how helpful they are. In this paper we present the results of an empirical study devoted to this question. Based on data collected on over 100 projects performed in Israel in a variety of industries, we examine the extent of usage of some risk management practices, such as risk identification, probabilistic risk analysis, planning for uncertainty and trade-off analysis, the difference in application across different types of projects, and their impact on various project success dimensions. Our findings suggest that risk management practices are still not widely used. Only a limited number of projects in our study have used any kind of risk management practices and many have only used some, but not all the available tools. When used, risk management practices seem to be working, and appear to be related to project success. We also found that risk management practices were more applicable to higher risk projects. The impact of risk management is mainly on better meeting time and budget goals and less on product performance and specification. In this case, we also found some differences according levels of technological uncertainty. Our conclusion is that risk management is still at its infancy and that at this time, more awareness to the application, training, tool development, and research on risk management is needed.

On the construction of control charts using linguistic variables

SUMMARY This paper studies two approaches to constructing control charts for linguistic data. Linguistic data can provide more information than the binary classification used in control charts by attributes. A generic approach for constructing attribute control charts using linguistic data is described. Several methods for calculating the values representing sample means, and for determining the centre line and the control limits are presented.

Probabilistic and membership approaches in the construction of control charts for linguistic data

Abstract Two approaches for constructing control charts for quality assurance when the observations are in the form of linguistic data are presented. Both approaches are based on fuzzy set theory and use fuzzy subsets to model the linguistic terms used to describe product quality. They differ in the interpretation of the control limits and in the procedure used to reduce the fuzzy subsets to scalars for determining the chart parameters. The results obtained with simulated data suggest that, on the basis of sensitivity to process shifts, the control charts for linguistic data perform better than conventional p control charts. The number of linguistic terms used in classifying the observations was found to influence the sensitivity of these control charts. The transformation method used to obtain the representative values and the amount of fuzziness do not seem to affect the performance of either type of control charts.

A Survey of Models for Allocating Inspection Effort in Multistage Production Systems

This paper describes the elements of the inspection allocation problem and surveys some of the models proposed in the literature. The limitations of the existing work are noted and possible approaches to the solution of more realistic problems are menti..

Evaluation of Models for Forecasting the Final Cost of a Project

This paper addresses how to estimate the final cost of a project and when the estimate becomes accurate. The performance of five forecasting models drawn from literature was evaluated with data from a sample of actual projects. A stability analysis was carried out in order to identify when the forecasts become stable and accurate for the model that emerged as the most accurate.

Factors affecting duration and effort estimation errors in software development projects

The purpose of this research was to fill a gap in the literature pertaining to the influence of project uncertainty and managerial factors on duration and effort estimation errors. Four dimensions were considered: project uncertainty, use of estimation development processes, use of estimation management processes, and the estimators experience. Correlation analysis and linear regression models were used to test the model and the hypotheses on the relations between the four dimensions and estimation errors, using a sample of 43 internal software development projects executed during the year 2002 in the IT division of a large government organization in Israel. Our findings indicate that, in general, a high level of uncertainty is associated with higher effort estimation errors while increased use of estimation development processes and estimation management processes, as well as greater estimator experience, are correlated with lower duration estimation errors. From a practical perspective, the specific findings of this study can be used as guidelines for better duration and effort estimation. Accounting for project uncertainty while managing expectations regarding estimate accuracy; investing more in detailed planning and selecting estimators based on the number of projects they have managed rather than their cumulative experience in project management, may reduce estimation errors.

An integrated approach for risk response development in project planning

The risk response development phase is a major phase in the project risk management process. We present a model that integrates project work contents, risk events, and risk reduction actions and their effects into a comprehensive framework. The model allows the representation of the overlapping effects of multiple risk reduction actions and of the impacts of secondary risk events, and supports the evaluation of the total risk exposure of the project under various combinations of risk reduction actions. The model can be treated with optimisation techniques in order to generate the most cost-effective combination of risk reduction actions. In this work we describe the model, outline a solution procedure and illustrate its application with an example taken from the software industry.

Activity based costing for projects

Abstract A generic activity-based costing model is presented. The model includes a cost allocation structure designed specifically for projects, and a number of cost drivers for typical project activities. A numerical example illustrates the benefits that ABC can provide. The paper concludes with a discussion of some issues involved in the implementation of ABC, and of activity-based management.