In search of requirements analyst characteristics that influence requirements elicitation effectiveness: a quasi-experiment

Context: Elicitation effectiveness depends on non-wellunderstood analyst?s skills and abilities. Identifying which analysts? characteristics have stronger influence on elicitation may help to improve requirements quality. Objective: Identify the analysts? characteristics that influence on the elicitation effectiveness. Method: We analyzed the impact of: the analyst?s experience in interviews, elicitation and requirements; their academic qualifications, the familiarity with problem domain and the time spent during the elicitation session in the effectiveness of the elicitation and subsequent consolidation of requirements, using a quasi-experiment. Results: The knowledge of the problem domain, the analysts? academic qualifications and the elicitation time do not appear to influence the effectiveness of the elicitation sessions. The analyst?s experience exerts a slight negative influence on the effectiveness of the elicitation session. The analyst?s experience and familiarity with problem domain adversely affect the consolidation process. Finally, the analyst?s academic qualifications have a strong positive impact(statistically significant) on the effectiveness of the consolidation process. Conclusions: Although the evidence is still scarce, it seems the analyst's confidence on his own experience may be harmful in some cases. Specific training in software requirements may yield much higher gains than non-specific analyst experience

Enhancing Analysts’ Mental Models for Improving Requirements Elicitation: A Two-stage Theoretical Framework and Empirical Results

Research has extensively documented the importance of accurate system requirements in avoiding project delays, cost overruns, and system malfunctions. Requirement elicitation (RE) is a critical step in determining system requirements. While much research on RE has emerged, a deeper understanding of three aspects could help significantly improve RE: 1) insights about the role and impacts of support tools in the RE process, 2) the impact of using support tools in multiple stages of the RE process, and 3) a clear focus on the multiplicity of perspectives in assessing RE outcomes. To understand how using support tools could improve RE, we rely on the theoretical lens of mental models (MM) to develop a dynamic conceptual model and argue that analysts form mental models (MMs) of the system during RE and these MMs impact their outcome performance. We posit that one can enhance analysts’ MMs by using a knowledge-based repository (KBR) of components and services embodying domain knowledge specific to the target application during two key stages of RE, which results in improved RE outcomes. We measured the RE outcomes from user and analyst perspectives. The knowledge-based component repository we used in this research (which we developed in collaboration with a multi-national company) focused on insurance claim processing. The repository served as the support tool in RE in a multi-period lab experiment with multiple teams of analysts. The results supported the conceptualized model and showed the significant impacts of such tools in supporting analysts and their performance outcomes at two stages of RE. This work makes multiple contributions: it offers a theoretical framework for understanding and enhancing the RE process, develops measures for analysts’ mental models and RE performance outcomes, and shows the process by which one can improve analysts’ RE performance through access to a KBR of components at two key stages of the RE process

Proposal of a Quasi-Experiment for studying the effect of experience on elicitation effectiveness

We plan to perform a quasi experiment to evaluate the effect of experience on requirements elicitation. Researchers will play the role of customers, whereas participants will perform the role of analysts. Analysts will hold a 60 minute interview and will then be given 25 minutes to write up a report of their findings. Participant effectiveness will be compared with available data series on the effectiveness of novice analysts that we have collected previously

The Influence of Analyst Communication in IS Projects

Information system (IS) researchers have long noted that IS analysts need to understand users’ needs if they are to design better systems and improve project outcomes. While researchers agree that analyst communication activities are an important prerequisite for such an understanding, little is known about the nature of different communication behaviors IS analysts can undertake to learn about users’ system needs and the impact of such behaviors on IS projects. To address this gap, this paper draws from the learning literature to articulate the information transmission activities IS analysts can undertake and the content of the information they can transmit when learning about users’ organizational tasks and information needs. The influence of analyst communication activities on the generation of valid information regarding user needs, analyst learning, and IS project outcomes are then investigated via a case study of two IS projects. The analysis of the two cases suggests that analysts who encourage the use of concrete examples, testing, and validation, and who solicit feedback about users’ business processes are likely to better understand users’ tasks, and in turn design systems that better meet users’ task needs than analysts who do not