Software como um Serviço: uma plataforma eficaz para oferta de sistemas holísticos de gestão da performance

This study main objective was to assess the viability of development of a Performance Management (PM) system, delivered in the form of Software as a Service (SaaS), specific for the hospitality industry and to evaluate the benefits of its use. Software deployed in the cloud, delivered and licensed as a service, is becoming increasingly common and accepted in a business context. Although, Business Intelligence (BI) solutions are not usually distributed in the SaaS model, there are some examples that this is changing. To achieve the study objective, design science research methodology was employed in the development of a prototype. This prototype was deployed in four hotels and its results evaluated. Evaluation of the prototype was focused both on the system technical characteristics and business benefits. Results shown that hotels were very satisfied with the system and that building a prototype and making it available in the form of SaaS is a good solution to assess BI systems contribution to improve management performance.O objetivo principal deste estudo é avaliar a viabilidade de desenvolvimento de um sistema de Gestão da Performance, entregue sob a forma de “Software como Serviço” (SaaS), específico para o setor hoteleiro, e também avaliar os benefícios de seu uso. O software implantado na cloud, entregue e licenciado como um serviço, é cada vez mais aceite num contexto de negócios. Todavia, não é comum que soluções de Business Intelligence (BI) sejam distribuídas neste modelo SaaS. No entanto, existem alguns exemplos de que isso se está a alterar. Para atingir o objetivo do estudo, foi utilizada Design Science Research como metodologia de pesquisa científica para desenvolvimento de um protótipo. Este protótipo foi implementado em quatro hotéis para que os seus resultados pudessem ser avaliados. A avaliação foi focada tanto nas características técnicas do sistema como nos benefícios para o negócio. Os resultados mostraram que os hotéis estavam muito satisfeitos com o sistema e que construir um protótipo e disponibilizá-lo sob a forma de SaaS é uma boa solução para avaliar a contribuição dos sistemas de BI para melhorar o desempenho da gestão.info:eu-repo/semantics/publishedVersio

Learning and Work: Professional Learning Analytics

Learning for work takes various forms, from formal training to informal learning through work activities. In many work settings, professionals collaborate via networked environments leaving various forms of digital traces and “clickstream” data. These data can be exploited through learning analytics (LA) to make both formal and informal learning processes traceable and visible to support professionals with their learning. This chapter examines the state-of-the-art in professional learning analytics (PLA) by considering how professionals learn, putting forward a vision for PLA, and analyzing examples of analytics in action in professional settings. LA can address affective and motivational learning issues as well as technical and practical expertise; it can intelligently align individual learning activities with organizational learning goals. PLA is set to form a foundation for future learning and work

Extracting Personal Behavioral Patterns from Geo-Referenced Tweets

This paper presents an exploratory study of the potential of geo-referenced Twitter data for extracting knowledge about significant personal places, behaviors and potential interests of people. The study was done analysing two months’ worth of tweets from residents of the greater Seattle area

Creating business value from big data and business analytics : organizational, managerial and human resource implications

This paper reports on a research project, funded by the EPSRC’s NEMODE (New Economic Models in the Digital Economy, Network+) programme, explores how organizations create value from their increasingly Big Data and the challenges they face in doing so. Three case studies are reported of large organizations with a formal business analytics group and data volumes that can be considered to be ‘big’. The case organizations are MobCo, a mobile telecoms operator, MediaCo, a television broadcaster, and CityTrans, a provider of transport services to a major city. Analysis of the cases is structured around a framework in which data and value creation are mediated by the organization’s business analytics capability. This capability is then studied through a sociotechnical lens of organization/management, process, people, and technology. From the cases twenty key findings are identified. In the area of data and value creation these are: 1. Ensure data quality, 2. Build trust and permissions platforms, 3. Provide adequate anonymization, 4. Share value with data originators, 5. Create value through data partnerships, 6. Create public as well as private value, 7. Monitor and plan for changes in legislation and regulation. In organization and management: 8. Build a corporate analytics strategy, 9. Plan for organizational and cultural change, 10. Build deep domain knowledge, 11. Structure the analytics team carefully, 12. Partner with academic institutions, 13. Create an ethics approval process, 14. Make analytics projects agile, 15. Explore and exploit in analytics projects. In technology: 16. Use visualization as story-telling, 17. Be agnostic about technology while the landscape is uncertain (i.e., maintain a focus on value). In people and tools: 18. Data scientist personal attributes (curious, problem focused), 19. Data scientist as ‘bricoleur’, 20. Data scientist acquisition and retention through challenging work. With regards to what organizations should do if they want to create value from their data the paper further proposes: a model of the analytics eco-system that places the business analytics function in a broad organizational context; and a process model for analytics implementation together with a six-stage maturity model

A review and future direction of agile, business intelligence, analytics and data science

Agile methodologies were introduced in 2001. Since this time, practitioners have applied Agile methodologies to many delivery disciplines. This article explores the application of Agile methodologies and principles to business intelligence delivery and how Agile has changed with the evolution of business intelligence. Business intelligence has evolved because the amount of data generated through the internet and smart devices has grown exponentially altering how organizations and individuals use information. The practice of business intelligence delivery with an Agile methodology has matured; however, business intelligence has evolved altering the use of Agile principles and practices. The Big Data phenomenon, the volume, variety, and velocity of data, has impacted business intelligence and the use of information. New trends such as fast analytics and data science have emerged as part of business intelligence. This paper addresses how Agile principles and practices have evolved with business intelligence, as well as its challenges and future directions

Carving out new business models in a small company through contextual ambidexterity: the case of a sustainable company

Business model innovation (BMI) and organizational ambidexterity have been pointed out as mechanisms for companies achieving sustainability. However, especially considering small and medium enterprises (SMEs), there is a lack of studies demonstrating how to combine these mechanisms. Tackling such a gap, this study seeks to understand how SMEs can ambidextrously manage BMI. Our aim is to provide a practical artifact, accessible to SMEs, to operationalize BMI through organizational ambidexterity. To this end, we conducted our study under the design science research to, first, build an artifact for operationalizing contextual ambidexterity for business model innovation. Then, we used an in-depth case study with a vegan fashion small e-commerce to evaluate the practical outcomes of the artifact. Our findings show that the company improves its business model while, at the same time, designs a new business model and monetizes it. Thus, our approach was able to take the first steps in the direction of operationalizing contextual ambidexterity for business model innovation in small and medium enterprises, democratizing the concept. We contribute to theory by connecting different literature strands and to practice by creating an artifact to assist managemen

Shaping Problems, Not Decisions:When Decision Makers Leverage Visual Analytics

Just as modern software development strategies have introduced agile methods and rapid prototyping to organizations. Visual analytic tools now bring the same spirit of prototyping and iteration directly into the decision-making process. Yet decision makers and analysts may not yet be as “agile” as the tools they are using and instead tend to remain in their traditional roles during analytic tasks. _x000D_ _x000D_ The emerging analytic leaders are managers who do not merely act on the findings of others but rather find and shape problems by constantly interacting with data and scrutinizing and adjusting to changes in real-time data. Our research found that: 1) managers need to develop new competencies to cognitively adapt to visual decision making; 2) managers need to become more humble and share data widely across their organizations in order to facilitate a comprehensive analytic culture; and 3) roles and responsibilities of analysts and managers need to be reconsidered