Narciso Cerpa

State of the practice: An exploratory analysis of schedule estimation and software project success prediction

During discussions with a group of U.S. software developers we explored the effect of schedule estimation practices and their implications for software project success. Our objective is not only to explore the direct effects of cost and schedule estimation on the perceived success or failure of a software development project, but also to quantitatively examine a host of factors surrounding the estimation issue that may impinge on project outcomes. We later asked our initial group of practitioners to respond to a questionnaire that covered some important cost and schedule estimation topics. Then, in order to determine if the results are generalizable, two other groups from the US and Australia, completed the questionnaire. Based on these convenience samples, we conducted exploratory statistical analyses to identify determinants of project success and used logistic regression to predict project success for the entire sample, as well as for each of the groups separately. From the developer point of view, our overall results suggest that success is more likely if the project manager is involved in schedule negotiations, adequate requirements information is available when the estimates are made, initial effort estimates are good, take staff leave into account, and staff are not added late to meet an aggressive schedule. For these organizations we found that developer input to the estimates did not improve the chances of project success or improve the estimates. We then used the logistic regression results from each single group to predict project success for the other two remaining groups combined. The results show that there is a reasonable degree of generalizability among the different groups.

What factors lead to software project failure

It has been suggested that there is more than one reason for a software development project to fail. However, most of the literature that discusses project failure tends to be rather general, supplying us with lists of risk and failure factors, and focusing on the negative business effects of the failure. Very little research has attempted an in-depth investigation of a number of failed projects to identify exactly what are the factors behind the failure. In this research we analyze data from 70 failed projects. This data provides us with practitionerspsila perspectives on 57 development and management factors for projects they considered were failures. Our results show that all projects we investigated suffered from numerous failure factors. For a single project the number of such factors ranges from 5 to 47. While there does not appear to be any overarching set of failure factors we discovered that all of the projects suffered from poor project management. Most projects additionally suffered from organizational factors outside the project managerpsilas control. We conclude with suggestions for minimizing the four most common failure factors.

Collective action for mobile payment platforms

Graphical abstractDisplay Omitted Mobile payment requires collective action between banks and telecom operators.A case study on cooperation between all major Dutch banks and operators is analyzed.Differing strategic objectives between banks and operators hinder collective action.Lack of leadership, authority and commitment hindered collective action.Realizing joint m-payment platforms for banks and operators is highly challenging. Mobile payment has long been discussed but has still not reached mass market in Western societies. Banks and telecom operators often struggle to develop platforms for authorization and authentication of mobile payment services. This paper analyses an in-depth case on collaboration between three major Dutch banks and three Dutch telecom operators who jointly developed a trusted service manager for mobile payment. Collective action theory and platform theory is combined to study the issues of collaboration and competition between banks and operators. We find that differing strategic objectives and interests, conflicts, lack of dependencies and governance issues led to dissolution of the mobile payment platform. These problems partly result from platform characteristics of openness to third parties, governance of relations with third parties and platform competition.

Australian software development: what software project management practices lead to success?

We surveyed a number of Australian software practitioners in order to understand what software development practices were used in their recent software projects. We were particularly interested to discover what project management practices are common in Australian software projects. The relationship between practices and software project outcomes enables us to investigate why some projects succeed and others fail. We found that nearly 20% of projects had no lifecycle methodology and 10% of our respondents did not understand what was meant by a software development lifecycle methodology. Many recognized software practices are not being applied consistently in the projects investigated. Fifty percent of projects began with unclear requirements. Risk assessment is not normally a part of the development process and the organizations are not learning from their mistakes as post mortem reviews are much more likely to be held for successful projects than they are for unsuccessful projects.

The optimization of success probability for software projects using genetic algorithms

The software development process is usually affected by many risk factors that may cause the loss of control and failure, thus which need to be identified and mitigated by project managers. Software development companies are currently improving their process by adopting internationally accepted practices, with the aim of avoiding risks and demonstrating the quality of their work. This paper aims to develop a method to identify which risk factors are more influential in determining project outcome. This method must also propose a cost effective investment of project resources to improve the probability of project success. To achieve these aims, we use the probability of success relative to cost to calculate the efficiency of the probable project outcome. The definition of efficiency used in this paper was proposed by researchers in the field of education. We then use this efficiency as the fitness function in an optimization technique based on genetic algorithms. This method maximizes the success probability output of a prediction model relative to cost. The optimization method was tested with several software risk prediction models that have been developed based on the literature and using data from a survey which collected information from in-house and outsourced software development projects in the Chilean software industry. These models predict the probability of success of a project based on the activities undertaken by the project manager and development team. The results show that the proposed method is very useful to identify those activities needing greater allocation of resources, and which of these will have a higher impact on the projects success probability. Therefore using the measure of efficiency has allowed a modular approach to identify those activities in software development on which to focus the projects limited resources to improve its probability of success. The genetic algorithm and the measure of efficiency presented in this paper permit model independence, in both prediction of success and cost evaluation.

Factors that motivate software engineering teams: A four country empirical study

Motivation, although difficult to quantify, is considered to be the single largest factor in developer productivity; there are also suggestions that low motivation is an important factor in software development project failure. We investigate factors that motivate software engineering teams using survey data collected from software engineering practitioners based in Australia, Chile, USA and Vietnam. We also investigate the relationship between team motivation and project outcome, identifying whether the country in which software engineering practitioners are based affects this relationship. Analysis of 333 questionnaires indicates that failed projects are associated with low team motivation. We found a set of six common team motivational factors that appear to be culturally independent (project manager has good communication with project staff, project risks reassessed, controlled and managed during the project, customer has confidence in the project manager and the development team, the working environment is good, the team works well together, and the software engineer had a pleasant experience). We also found unique groupings of team motivational factors for each of the countries investigated. This indicates that there are cultural differences that project managers need to consider when working in a global environment.

Evaluating logistic regression models to estimate software project outcomes

Context: Software has been developed since the 1960s but the success rate of software development projects is still low. During the development of software, the probability of success is affected by various practices or aspects. To date, it is not clear which of these aspects are more important in influencing project outcome. Objective: In this research, we identify aspects which could influence project success, build prediction models based on the aspects using data collected from multiple companies, and then test their performance on data from a single organization. Method: A survey-based empirical investigation was used to examine variables and factors that contribute to project outcome. Variables that were highly correlated to project success were selected and the set of variables was reduced to three factors by using principal components analysis. A logistic regression model was built for both the set of variables and the set of factors, using heterogeneous data collected from two different countries and a variety of organizations. We tested these models by using a homogeneous hold-out dataset from one organization. We used the receiver operating characteristic (ROC) analysis to compare the performance of the variable and factor-based models when applied to the homogeneous dataset. Results: We found that using raw variables or factors in the logistic regression models did not make any significant difference in predictive capability. The prediction accuracy of these models is more balanced when the cut-off is set to the ratio of success to failures in the datasets used to build the models. We found that the raw variable and factor-based models predict significantly better than random chance. Conclusion: We conclude that an organization wishing to estimate whether a project will succeed or fail may use a model created from heterogeneous data derived from multiple organizations.

Stakeholder dissonance: disagreements on project outcome and its impact on team motivation across three countries

When a project perceived to be a failure by one set of stakeholders is perceived as a success by another set of stakeholders we have outcome disagreement. Our objective is to discover if team motivation is affected when developers and managers disagree on a projects outcome. We also investigate if culture influences team motivation. We collected questionnaire data on 290 completed projects from software engineering practitioners based in Australia, Chile, and USA. We asked if the respondent considered their project was successful and if higher level management considered the project a success. We found that more projects were perceived successful by management than by developers. Also, successful projects are associated with higher levels of team motivation than failed projects or projects with outcome disagreement. Culture makes a difference to levels of team motivation for both failed projects, and projects with outcome disagreement. An over-riding influence on team motivation is agreement with other stakeholders. To motivate practitioners, stakeholders need to agree on what constitutes a successful or a failed project before the start of the project.

Strategic Information Systems Planning: An Empirical Evaluation of Its Dimensions

Strategic management of Information Technology (IT) has long been regarded as a critical component of business performance. This study addresses two objectives. Firstly we investigate the practice and effectiveness of Strategic Information Systems Planning (SISP) as a function of strategic management in 29 large Australian organizations. Secondly we review these results through a theoretical lens established by Segars et al. (1998) who identified six dimensions that provide a structured approach to reviewing the SISP process. Our results show that SISP was widely used in these 29 organizations in aspects such as planning associated with strategic IS investment and application, and whilst the theoretical review generally supported the literature, some amendments are required to the participation and focus dimensions suggested by Segars et al. (1998). Such results have implications for both practitioners and researchers.

Bases para la creación de una metodología de adopción de comercio electrónico para las PYMES chilenas

Esta investigacion propone una metodologia de adopcion de comercio electronico, la que esta enfocada a las pequenas y medianas empresas (PYMES) Chilenas. La metodologia comprende las etapas esenciales en la adecuacion de estas al comercio electronico, por lo que se presentan elementos estrategicos en sus primeras etapas, asi como, elementos funcionales y operativos para la implementacion de la metodologia a la PYME de una forma exitosa. Esta metodologia fue validada a traves de dos casos de estudio realizados en empresas PYMES que cuentan con implementaciones de comercio electronico y que han tenido que enfrentar los problemas caracteristicos que se presentan con la adopcion de esta tecnologia