Irja Kankaanpää

Software modernization decision criteria: an empirical study

Decisions regarding software evolution strategies such as modernizations are economically important. We present results of our empirical study of the views of decision makers. We have asked their views of the relative importance of 49 software modernization decision criteria. We have gathered data from Finnish software industry. There were 26 experts from 8 organizations involved. They were mainly upper or middle level managers. Our study shows that there is a large set of criteria which should be taken into account, and that those studied by us provide a good coverage of the relevant ones. We list the top-20 criteria. We also performed a cluster analysis which produced two groups of subjects. Views of the decision makers in software user and software supplier organizations were different. We suggest that decision makers work process could be enhanced by taking into account the received lessons.

Group Decision-Making Processes in Industrial Software Evolution

Software evolution decision-making is important. Decisions can be made by an individual or a group. Currently it is not known how decision-making is organized in software industry. However, that knowledge is needed to improve the decision-making processes. Therefore, we have studied 29 decision making experts, who were involved in software evolution decision-making. The study was performed with qualitative methods, which enabled the gathering of versatile information concerning the views of the decision-makers. The study revealed group decisions are widely used both in private and public organizations and attitudes towards them are generally positive or neutral. The study provided information about usage of groups in the preparation phase of the decisions and in the actual decision-making phase. In most cases groups were used in the preparation phase. The revealed decision-making process is related to two theoretical process models. The findings help to understand industrial decision-making in this important, but empirically surprisingly scarcely studied area.

Defining the process for making software system modernization decisions

This paper outlines a process for software system modernization decisions. The rationale of the process is explained and the process is defined in a way that allows its adaptation for other organizations and situations. The process is a light-weight one and is based on the use of objective data. The procedures for collecting the data are explained. The process has been used to solve a real industrial decision making situation in which the process was successful.

LEGACY SYSTEM EVOLUTION - A Comparative Study of Modernisation and Replacement Initiation Factors

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IS Evolution Benefit Assessment – Challenges with Economic Investment Criteria

Maintenance and system evolution activities have a significant role in the information system (IS) life cycle. It has been estimated that approximately 80% of the total IT expenses are allocated for maintenance activities [20]. According to Lehman’s first law, maintenance is necessary, because software needs to be continuously improved or it will get out of date and cannot respond to the requirements of its environment [19]. Despite the importance of IS evolution investments, there is a gap between the IT related costs and company profitability [27]. Brynjolfssen [10] described this as a productivity paradox: information technology utilization has increased since the 70’s but simultaneously productivity has slowed down. The work effort of maintenance is generally proportional to the life time of a system. Therefore, it is more dominant in legacy information systems [7]. Besides being old, a legacy system is typically large at size and contains vital information for the user organization, uses out-of-date technology, and is laborious to maintain [3] [4]. There are three strategies to deal with a legacy system: 1) maintaining and using the system as it is, 2) developing or purchasing a new system to replace it, or 3) radically improve, i.e. modernize, the legacy system in order to meet the new business needs [4] [25, p 8-10]. IT investments can be roughly classified in two categories, acquisition projects and development projects [24]. In the context of IS evolution, acquisition project includes purchasing off-the-self software in order to replace the existing legacy system. Development investment refers to a project that aims at developing new or modernizing the existing system. Therefore, replacement can be either an

Assessing software replacement success: an industrial case study applying four approaches

This paper describes an industrial case study assessing software replacement success and other effects. The target of assessments has been a large commercial legacy system for customer register management. The success of its replacement by its performed rewrite has been assessed via four approaches concerning: user satisfaction, strengths and problems of the system, problem surveillance and expert judgments. The approaches and metrics have been selected in cooperation with industrial experts in order that they would meet the needs of their organization. The assessments have been conducted by comparing the situations before and after the rewrite. They have included quality aspects. The applied approaches have supplemented each other well and results provided by them have been mainly consistent. The study has offered a wide view of the system replacement effects and lessons for the replacement assessment process improvement in industrial settings.