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LARGE SCALE REQUIREMENTS ANALYSIS AS HETEROGENEOUS ENGINEERING Kalle Lyytinen Department of Information Systems Case Western Reserve University kalle@po.cwru.edu Mark Bergman Department of Computer Science Naval PostGraduate School, Monterey John Leslie King School of Information University of Michigan Keywords: system requirements, functional requirements, system failures, heterogeneous engineering. Abstract: We examine how to improve our understanding in stating and managing successfully requirements for large systems, because the current concept of a system requirement is ill suited to develop true requirements for such systems. It regards requirements as goals to be discovered and solutions as separate technical elements. In consequence, current Requirements Engineering (RE) theory separates these issues and reduces RE to an activity where a technical solution is documented for a given set of goals (problems). In contrast, we advocate a view where a requirement specifies a set of mappings between problem and solution spaces, which both are socially constructed and negotiated. Requirements are emergent and need to be discovered through a contracted process, which likens to a “garbage-can” decision-making. System requirements thereby embrace an emergent functional ecology of requirements. This leads to equate requirements engineering with heterogeneous engineering. The admitted heterogeneity of technological activity avoids a commitment to social (or technological) reductionism. Requirements engineers need to be seen as “heterogeneous engineers” who must associate entities that range from people, through skills, to artifacts and natural phenomena. They are successful only, if built socio-technical networks can remain stable in spite of attempts of other entities to dissociate them. 1 INTRODUCTION Information systems development (ISD) has remained a high-risk proposition despite huge advances in computing and telecommunications technologies. Information systems projects in general, and large information systems projects in particular continue to fail at an unacceptable rate (Abdel-Hamid and Madnick 1990; Myers 1994; Drummond 1996; Mitev 1996; Rosenwein 1997). While some portion of troubled ISD projects is turned around successfully, intensive research in the past has generated little understanding in how to avoid failures in large systems development I. Seruca et al. (eds.), Enterprise Information Systems VI, © 2006 S pringer. Printed in the Netherlands. 9 9– 23. initiatives. From the growing incidence of failed projects, we conclude that advances in technologies are not sufficient to save large projects. Instead, they remain susceptible to failure until we learn to understand how technological, organizational and institutional changes are interwoven in large systems, and how system developers should accordingly state and manage requirements for such systems. Consider the following example. On March 11, 1993 the world was shocked by the sudden cancellation of the Taurus project, which the London Stock Exchange had been developing for more than six years. Taurus was expected to be
10 ENTERPRISE INFORMATION SYSTEMS VI instrumental in the radical restructuring the securities trade, widely known as the Big Bang, by forming a backbone system for the London Stock Exchange. The project cost the Stock Exchange $130 million, and securities companies invested $600 million more (Drummond 1996). After years of alternating embarrassments and heroic efforts, Taurus was cancelled before a single module was implemented because the required functionality and performance could never be delivered. Although Taurus was a very complex project, involving novel technologies and massive organizational and institutional scale, ineffective project controls allowed requirements to change continuously throughout the project. Moreover, management ignored clear warning signs about organizational and technical risks, whilst powerful interests pushed for Taurus’ development despite confusion over the system’s purpose and design. Simply, there was no understanding what the systems was supposed to do and what stakeholders it should serve. In the end, advocates held an almost superstitious faith in the project, dismissing objections and proposals for modifications and clearer statement of the requirements with comments like “...we have had all those arguments. Great idea but no, we have been arguing about it for twelve years, forget it” (Drummond 1996) (p. 352). With the benefit of hindsight, the Taurus failure could have been averted by adjusting its course based on a more delicate and politically sensitive requirements engineering. But this was not done despite a well known truism shared both in academia and industry that systematic requirements engineering is a keystone to a successful delivery of a large scale system. The failure of Taurus can be partly attributed to the dismissal of this well known fact, but we think there is more to learn. Taurus failure was also due to the fact that we poor knowledge about how to state and manage requirements for large systems that involve political and institutional elements. Stating requirements for such systems is not just a technical exercise, but necessitates a new mind set which we call “heterogeneous engineering” after Hughes (Hughes 1979a; Hughes 1979b; Hughes 1987). Heterogeneous engineering sees all requirements specifications to be inherently heterogeneous due to the need to establish stable networks involving both social and technical elements through engineering (if the network is not stable the system fails!). As Law (Law 1987) (p. 112) puts this: “The argument is that those who build artifacts do not concern themselves with artifacts alone, but must also consider the way in which the artifacts relate to social, economic, political, and scientific factors. All of these factors are interrelated, and all are potentially malleable.” Consequently, requirements engineers need to be seen as “heterogeneous engineers” who must successfully associate entities that range from people, through skills, to artifacts and natural phenomena. In this paper we will examine the problem of stating and managing requirements for large system development initiatives qua “heterogeneous engineering.” Our argument is twofold. First we will argue that failures like the Taurus disaster do not happen only because existing approaches to requirements engineering have not been adopted. In contrast, we argue that current requirements engineering techniques used alone will not do the job. This is because they are based on a fallacious assumption that business problems and political problems can be separated from technical requirements engineering concerns of how to specify a consistent and complete technical solution to a business problem. In contrast, large scale system development initiatives involve a simultaneous consideration of business, institutional, political, technical and behavioral issues. Second, based on behavioral theories of decision-making we argue, that solutions and problems are intertwined and addressed simultaneously during a requirements engineering process. Thus, requirements engineering can be understood only by using theories of behavioral and institutional decision making along with applied technical understandings, but not only through the lens of rational technical “engineering.” The remainder of the paper is organized as follows. In section 2, we shortly examine the received “view” of requirements engineering as outlined by the proponents of the current requirements engineering literature. In section 3, we propose an alternative concept of requirements engineering which we call the functional ecology of requirements. In this view, requirements are not discovered but constructed as mappings between solution and problem spaces. The construction process involves a protracted “walk” between these spheres. Section 4 concludes the paper by drawing some consequences for requirements engineering research. 2 REQUIREMENTS ENGINEERING DEFINED The concept of a system requirement is relatively well known in the system and software engineering literature since mid 70’s. The concept was originally conceived to involve the stating what the system is supposed to do before stating how the system produces the desired functionality (Ross 1977). The
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5.3.6 Effect on all Policies by Int
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ACKNOWLEDGEMENTS We would like to t
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This paper describes the data sampl
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RELATIONAL SAMPLING FOR DATA QUALIT
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PART 2 Artificial Intelligence and
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Abdelkafi, N. .....................
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