What influences the speed of prototyping? An empirical investigation of twenty software startups

It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups can learn depends on how fast they can prototype. Despite of the importance, there is a lack of research about prototyping in software startups. In this study, we aimed at understanding what are factors influencing different types of prototyping activities. We conducted a multiple case study on twenty European software startups. The results are two folds, firstly we propose a prototype-centric learning model in early stage software startups. Secondly, we identify factors occur as barriers but also facilitators for prototyping in early stage software startups. The factors are grouped into (1) artifacts, (2) team competence, (3) collaboration, (4) customer and (5) process dimensions. To speed up a startups progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototypingComment: This is the author's version of the work. Copyright owner's version can be accessed at doi.org/10.1007/978-3-319-57633-6_2, XP2017, Cologne, German

A MANAGED APPROACH OF INTERACTION BETWEEN AGILE SCRUM AND SOFTWARE CONFIGURATION MANAGEMENT SYSTEM

In current age the agile software development is one of the most popular software development methodology but due the mismanagement and lack of efficient handling of agile scrum and software configuration management system our software industry is facing a high rate of failed product, keeping this as my motivation, I have designed a efficient checklist which will help the industry to organized the interaction between agile scrum process and software configuration management system in a efficient and managed way and definitely that will increase the successful project in the software industry. Index-term : Agile Scrums, Software development, Software configuration management system, Checklist, Successful project

Organizational agility key factors for dynamic business process management

International audienceFor several years, Business Process Management (BPM) is recognized as a holistic management approach that promotes business effectiveness and efficiency. Increasingly, corporates find themselves, operating in business environments filled with unpredictable, complex and continuous change. Driven by these dynamic competitive conditions, they look for a dynamic management of their business processes to maintain their processes performance. To be competitive, companies have to respond quickly and nimbly to changing environment. One domain that has dominated the thinking of most managers from few years is organizational agility. It is considered as inescapable feature of today's forward-looking corporates. About 90% of executives surveyed by the Economist Intelligence Unit believe that organizational agility is critical for business success. Many researchers tried to define and characterize organizational agility according to their context and domain application. The first aim of this paper is to tighten and explicate a conceptualization of organizational agility that clarifies what it is and how it can be reached by proposing a framework that leads to improve organizational agility. The second aim of the current research is to suggest ideas on how to make business processes agile and what are the practices of organizational agility that can be transferred to BPM

Infollution (Information Pollution) Management, Filtering Strategy, Scalable Workforce, and Organizational Learning: A Conceptual Study

Information generation is increasing rapidly on a global scale. The exponential advancement in information technology and communication has accentuated the problem of effective information management. Yet, employees’ cognitive ability to process information has not increased in parallel with information generation. With the exponential rise of information, information pollution (infollution) emerges as a problem on an exponential basis. Infollution is among the greatest challenges of the 21st century. Nevertheless, based on information processing theory and dynamic capability, researchers have conceptualised that agile organisations can cope with information pollution by promoting scalable workforce and organisational learning. By employing coping strategies, filtering has been hypothesised as moderating the association of scalable workplace and organisational learning with infollution management. This research will extend the literature in the domain of information management and agile organisations. It will be particularly useful for information processors to identify quality information for improved decision-making.&nbsp

A Quality Model for Actionable Analytics in Rapid Software Development

Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by IEEE in the 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018. The final authenticated version will be available onlin