The impact of education and training in large-scale agile transformation

Abstract. Large-scale agile has become a very popular approach for big companies in the past ten years. There are many different frameworks on how to handle large product development units in an agile way. Many companies have divided their units geographically to several countries and multiple development teams may work together with the same product. Due to the complexity of these large companies, organizations have implemented large-scale agile frameworks to help and make processes coherent. Transformation process in large-scale agile companies is long-term and time-consuming process. It is a long process where management must proceed multiple actions to get the large-scale agile framework to work in the organization. One of these actions is training the employees of the organization. This thesis literature review is based on prior research of agile software development, large-scale agile transformation, and Scaled Agile Framework. Literature review based on these three topics gives core to the research part. There was one case organization in this study which was in the middle of the transformation process during this study. This research studies the case organization’s training processes and competence of the employees related to large-scale agile. This research used the case study approach. Baseline data was collected from the case organization’s employees by using quantitative questionnaires and qualitative interviews. This study provided answers for the case organization on how the training can be handled during the transformation process. Study produced proposals on how to improve employees’ training paths in the case organization. Training plays a crucial part in the transformation process. Managers must prepare, plan, and set clear goals for the training paths. Every employee must get the large-scale agile training during the transformation process. With proper planning organizations can avoid transformation failures

AGILE–STAGE GATE MANAGEMENT (ASGM): NPD IMPLEMENTATION PRACTICES FROM GLOBAL FIRMS DEVELOPING COMPLEX, PHYSICAL PRODUCTS

Stage Gate Management (SGM) has been used successfully by global organizations to direct the New Product Development process (NPD) for years, recently a new variant of this venerable approach has emerged. Researchers and firms have begun to intersperse elements of Agile, as popularized for the development of software, to create an Agile – Stage Gate Management (ASGM) hybrid NPD framework. Agile practitioners believe in process waste reduction, an intense focus on customers, and the creation of nimble entrepreneurial project teams, which, for software products, has positively impacted development time to market, resource utilization, and market success, more generally, improved business outcomes. For NPD professionals responsible for physical products, not solely software, do these Agile tenets continue to produce results? With minimal available research, a Grounded Theory study was conducted to inductively create theory from the implementation of ASGM, specifically for firms that design, develop, and manufacture physical products. Twenty-nine experienced industry professionals were interviewed from four global companies which represented five distinct Business Units (BU) which competed in a variety of markets and industries around the world. From these interviews, a Content Analysis approach was employed to organize primary and secondary themes which illustrated NPD team practices. Additionally, a comparative multi-case study method further developed specific Agile/Scrum techniques implemented, the measures of business success realized, as well as, a new ASGM model for like firms. From this research, firms which developed physical products did not implement all Agile practices, only Team Interface, Product Demonstrations, and Specification Flexibility were uncovered. The cases did, however, subjectively realize an improved time to market, as well as, greater product success for projects commercialized using ASGM. Lastly, a new framework emerged which highlighted the unique practice of Agile behaviors earlier in the development process, but rigid, or SGM-like, activities closer towards product launch

Big Data Now, 2015 Edition

Now in its fifth year, O’Reilly’s annual Big Data Now report recaps the trends, tools, applications, and forecasts we’ve talked about over the past year. For 2015, we’ve included a collection of blog posts, authored by leading thinkers and experts in the field, that reflect a unique set of themes we’ve identified as gaining significant attention and traction. Our list of 2015 topics include: Data-driven cultures Data science Data pipelines Big data architecture and infrastructure The Internet of Things and real time Applications of big data Security, ethics, and governance Is your organization on the right track? Get a hold of this free report now and stay in tune with the latest significant developments in big data

Adopting Agile Methods in Large-scale Organizations using Scaling Frameworks

Agile methods were originally developed for small and co-located teams. The popularity and success of agile methods in small teams led to growing interest on agile adoption across large organizations as well. However, there are several challenges while adopting agile to large, e.g., coordination between large number of teams and integration of other nondevelopment units e.g., HR, and marketing. Scaling frameworks, e.g. Scaled Agile Framework (SAFe) and Large ScaleScrum (LeSS) to support scaling agile to large have become popular in the recent past. Despite of popularity, there is very little scientific research on usage of the scaling frameworks. The primary goal of the thesis is to investigate the adoption and usage of scaling frameworks in practice. The goal is divided into two parts: a) scaling frameworks usage and adoption and b) SAFe usage and adoption. In the first part, we conducted two surveys. The first survey aimed to explore why the frameworks were developed, and how they were evolved, their benefits and challenges directly from the practitioners who developed them. Later, in second survey, we collected data from 204 software practitioners using scaling frameworks to understand the reasons, expected benefits and satisfaction of using them. In the second part, we conducted a multivocal literature review (MLR) due to the lack of scientific evidence on SAFe, to understand the benefits and challenges of SAFe adoption. Next, we conducted an indepth case study to explore the reasons, transformation process, benefits and challenges of SAFe. To get a wider overview of the benefits and challenges of SAFe we conducted a survey, to explore the benefits and challenges of SAFe. Our results for the first part show that majority of the frameworks were designed to improve agility, collaboration, coordination,and synchronization between agile teams. The most common reasons for their adoption were to scale more people and deal with existing challenges and pain points. The benefits of adopting these frameworks were categorized intoto business, product, organizational, and culture and the challenges were categorized to implementation, organizational,and scope. Our results for the second part show that reasons for SAFe adoption are related to organizational, business,and framework-specific. SAFe transformation activities typically map with the SAFe roadmap activities. The most common benefits of SAFe adoption are improved transparency, collaboration and faster time to market. The most significant challenges of SAFe adoption are identifying value streams and forming ARTs, change resistance, and inculcating an agile mindset. More in-depth research on scaling frameworks is needed to establish the effectiveness oftheir usage in practice. We encourage researchers to conduct in-depth case studies on their usage and adoption

Agile Processes in Software Engineering and Extreme Programming

This open access book constitutes the proceedings of the 22nd International Conference on Agile Software Development, XP 2021, which was held virtually during June 14-18, 2021. XP is the premier agile software development conference combining research and practice. It is a unique forum where agile researchers, practitioners, thought leaders, coaches, and trainers get together to present and discuss their most recent innovations, research results, experiences, concerns, challenges, and trends.  XP conferences provide an informal environment to learn and trigger discussions and welcome both people new to agile and seasoned agile practitioners. This year’s conference was held with the theme “Agile Turns Twenty While the World Goes Online”. The 11 full and 2 short papers presented in this volume were carefully reviewed and selected from 38 submissions. They were organized in topical sections named: agile practices; process assessment; large-scale agile; and short contributions

Applying Machine Learning to Root Cause Analysis in Agile CI/CD Software Testing Environments

This thesis evaluates machine learning classification and clustering algorithms with the aim of automating the root cause analysis of failed tests in agile software testing environments. The inefficiency of manually categorizing the root causes in terms of time and human resources motivates this work. The development and testing environments of an agile team at Ericsson Finland are used as this work's framework. The author of the thesis extracts relevant features from the raw log data after interviewing the team's testing engineers (human experts). The author puts his initial efforts into clustering the unlabeled data, and despite obtaining qualitative correlations between several clusters and failure root causes, the vagueness in the rest of the clusters leads to the consideration of labeling. The author then carries out a new round of interviews with the testing engineers, which leads to the conceptualization of ground-truth categories for the test failures. With these, the human experts label the dataset accordingly. A collection of artificial neural networks that either classify the data or pre-process it for clustering is then optimized by the author. The best solution comes in the form of a classification multilayer perceptron that correctly assigns the failure category to new examples, on average, 88.9\% of the time. The primary outcome of this thesis comes in the form of a methodology for the extraction of expert knowledge and its adaptation to machine learning techniques for test failure root cause analysis using test log data. The proposed methodology constitutes a prototype or baseline approach towards achieving this objective in a corporate environment

Finnish Enterprise Agile Transformations : A Survey Study

Peer reviewe

Innovate and prosper: ensuring Australia's future competitiveness through university-industry collaboration

Executive summary The continuation of Australia’s economic growth is under threat. In order to sustain the levels of prosperity we have previously experienced, we have to build on our competitive edge in key industries to remain globally competitive. Alongside these developments, Australia’s higher education system is under increased pressure to become more productive and develop courses that address employability. Innovation represents the most reliable and sustainable solution to transition into a high value, high wage economy. Yet Australia ranks 29th out of 30 in the Organisation for Economic Co-operation and Development (OECD) in terms of the proportion of large businesses and small to medium enterprises (SMEs) collaborating with higher education and public research institutions on innovation.   This report acts as the next level of detail to publications such as the Department of Industry’s Boosting the Commercial Returns from Research report and the Business Council of Australia’s Building Australia’s Comparative Advantages, which have highlighted Australia’s poor performance in collaborative innovation. We present five recommendations that are a call to action to universities, industry and Government to take the necessary steps to build an innovation economy. They are not a call for additional funding from Government, rather a more effective way of using our existing resources. PricewaterhouseCoopers (PwC) have engaged with leading figures from industry, including the Australian Industry Group (Ai Group), and partnered with the ATN to develop this five point action plan for Government, the university sector and industry 5 that will provide incentives and impetus for collaboration. Our recommendations include: Rebalance the national research agenda to underpin Australia\u27s economy and future prosperity Create incentives for university-industry collaboration Train researchers for diverse careers Enhance career mobility between industry, academia and government Provide incentives for co-investment in research infrastructure between universities, industry and state and federal government Each recommendation contains a number of practical strategies for consideration by Government, universities and industry. The hope is that the report will encourage dialogue between the three groups and prompt bold policy changes in the coming 12 months and beyond. &nbsp

Why and How do Large-scale Organizations Operationalize DevOps

An essential part of organizational efforts is to provide products to customers. To sustain competitive positions on existing markets, and to expand into new markets, firms utilize and continuously optimize approaches to efficiently provide effective products. Meanwhile, applying agile practices is a commoditized way for organizations to better adapt to changes during the development of their products. For bringing products to customers, more than their development is required. Typically, multiple organizational functions, all with individual goals and practices, are included in the development and delivery of products. This is often associated with friction points between those functions, and hinders the optimization of effectiveness and efficiency in providing products to customers. In retrospective, not all firms were able to recalibrate themselves and find back to former success after they had once missed to (again) innovate by timely addressing changes on their existing markets, discovering unmet or changed customer needs, and providing new products that bring together emerging technology with evolving customer demands. This potential threat now appears to be omnipresent with the ongoing proliferation of digitalization through the practical world of all of us. The emerging phenomenon of DevOps, a portmanteau word of “development” and “operations”, describes approaches to streamline development and delivery of products across organizational functions, to efficiently provide effective products, and to enable organizational digitalization efforts. This dissertation sheds light on reasoning, configurational factors, and dynamics behind DevOps implementations in large-scale. The composition of four independent yet interrelated scientific papers, the cornerstones of this dissertation, answers why and how large-scale organizations operationalize DevOps. In sum, this dissertation adds systematic and foundational knowledge, presents new applications and nuanced concretizations of scientific empiric approaches, connects allied but distinct research communities, and provides guidance for practitioners acting in this timely, relevant and interesting domain