Magne Jørgensen

Jefferson Seide Molléri, Casper Lassenius, Magne Jørgensen

Context: Backsourcing is the process of insourcing previously outsourced activities. When companies experience environmental or strategic changes, or challenges with outsourcing, backsourcing can be a viable alternative. While outsourcing and related processes have been extensively studied in software engineering, few studies report experiences with backsourcing. Objectives: We intend to summarize the results of the research literature on the backsourcing of IT, with a focus on software development. By identifying practical relevance experience, we aim to present findings that may help companies considering backsourcing. In addition, we aim to identify gaps in the current research literature and point out areas for future work. Method: Our systematic literature review (SLR) started with a search for empirical studies on the backsourcing of software development. From each study we identified the contexts in which backsourcing occurs, the factors leading to the decision to backsource, the backsourcing process itself, and the outcomes of backsourcing. We employed inductive coding to extract textual data from the papers identified and qualitative cross-case analysis to synthesize the evidence from backsourcing experiences. Results: We identified 17 papers that reported 26 cases of backsourcing, six of which were related to software development. The cases came from a variety of contexts. The most common reasons for backsourcing were improving quality, reducing costs, and regaining control of outsourced activities. The backsourcing process can be described as containing five sub-processes: change management, vendor relationship management, competence building, organizational build-up, and transfer of ownership. Furthermore, ...

Martin Shepperd, Carolyn Mair, Magne Jørgensen

CONTEXT: The role of expert judgement is essential in our quest to improve software project planning and execution. However, its accuracy is dependent on many factors, not least the avoidance of judgement biases, such as the anchoring bias, arising from being influenced by initial information, even when it's misleading or irrelevant. This strong effect is widely documented. OBJECTIVE: We aimed to replicate this anchoring bias using professionals and, novel in a software engineering context, explore de-biasing interventions through increasing knowledge and awareness of judgement biases. METHOD: We ran two series of experiments in company settings with a total of 410 software developers. Some developers took part in a workshop to heighten their awareness of a range of cognitive biases, including anchoring. Later, the anchoring bias was induced by presenting low or high productivity values, followed by the participants' estimates of their own project productivity. Our hypothesis was that the workshop would lead to reduced bias, i.e., work as a de-biasing intervention. RESULTS: The anchors had a large effect (robust Cohen's $d=1.19$) in influencing estimates. This was substantially reduced in those participants who attended the workshop (robust Cohen's $d=0.72$). The reduced bias related mainly to the high anchor. The de-biasing intervention also led to a threefold reduction in estimate variance. CONCLUSIONS: The impact of anchors upon judgement was substantial. Learning about judgement biases does appear capable of mitigating, although not removing, the anchoring bias. The positive effect of de-biasing through learning about biases suggests that it has value.