Agile Way Research Articles

A Distributed Model for Stressors Monitoring Based on Environmental Smart Sensors

Nowadays, in many countries, stress is becoming a problem that increasingly affects the health of people. Suffering stress continuously can lead to serious behavioral disorders such as anxiety or depression. Every person, in his daily routine, can face many factors which can contribute to increase his stress level. This paper describes a flexible and distributed model to monitor environmental variables associated with stress, which provides adaptability to any environment in an agile way. This model was designed to transform stress environmental variables in value added information (key stress indicator) and to provide it to external systems, in both proactive and reactive mode. Thus, this value-added information will assist organizations and users in a personalized way helping in the detection and prevention of acute stress cases. Our proposed model is supported by an architecture that achieves the features above mentioned, in addition to interoperability, robustness, scalability, autonomy, efficient, low cost and consumption, and information availability in real time. Finally, a prototype of the system was implemented, allowing the validation of the proposal in different environments at the University of Alicante.

Succeeding in an increasingly Agile world

Purpose As Agile management thinking spreads to every part and every kind of organization, including their competitors, corporate leaders need to take steps to ensure they get and keep a good seat at the Agile table. Design/methodology/approach The author’s first hand research finds that firms are learning the hard way that software process and value innovation requires a different way of running the organization to be successful. The whole firm has to become nimble, adaptable and able to adjust on the fly to meet the shifting whims of a marketplace driven by dynamic changes in customer value. Findings The Agile way of working is provoking a revolution in business that affects almost everyone. Agile organizations are connecting everyone and everything, everywhere, all the time. They are capable of delivering instant, intimate, frictionless value on a large scale. Practical implications Examples of the new way of running organizations are everywhere apparent. It’s not just the five biggest firms by market capitalization: Amazon, Apple, Facebook, Google and Microsoft. It’s also firms like Airbnb, Etsy, Lyft, Menlo Innovations, Netflix, Saab, Samsung, Spotify, Tesla, Uber and Warby Parker. Social implications A new kind of management was needed to enable this new kind of worker -- a fundamentally different way of running organizations. Agile is economically more productive and a better fit with the new marketplace. And it had immense potential benefit for the human spirit. It could create workplaces that enabled human beings to contribute their full talents on something worthwhile and meaningful – creating value for other human beings. Originality/value Continuing the management practices and structures of the lumbering industrial giants of the 20th Century is no longer a viable option for today’s firms. To survive, let alone thrive, leaders today must recognize that Agile is not something happening in software alone.

Firm Readiness Level for Innovation Projects: A New Decision-Making Tool for Innovation Managers

Innovation projects represent a major challenge for business managers due to their associated uncertainty degree. The already existing methodologies to support the innovation projects are aimed at piloting them and establishing the management stages in a flexible and agile way during their deployment. This paper proposes a complementary ex-ante methodology that seeks to aid the decision-making of companies to choose whether or not to launch a potential innovation project. This methodology evaluates to what extent the technological system of the company has the minimum required maturity degree of competencies to successfully achieve the innovation project. Thus, in first instance, an innovation project is characterized according to its novelty degree; both inside the company and in its environment. Subsequently, according to the previous characterization, the future project will have an impact on the technological system of the company. The capabilities of the firm are represented by a set of good practices associated with the innovation projects’ management that the company is able to deploy. Finally, the minimum maturity degree required by a particular project of these practices is determined. Then, the gap between the maturity requirement profile and the current profile of the company is established enabling to decide on the implementation of the project or not.

IM2, un Modelo de Madurez para la innovación en PYMEs

Este artículo presenta una herramienta para evaluar de una forma rápida los enfoques y prácticas de innovación de una PYME. Para el desarrollo del modelo de madurez propuesto (IM2), se ha realizado una revisión de la literatura que se ha centrado en las buenas prácticas relacionadas con la innovación y su gestión. La experiencia de implantación muestra la bondad de la herramienta a la hora de focalizar la innovación en áreas estratégicas de la empresa, así como un método práctico para el fomento de la innovación en las PYMEs a través de una “receta paso a paso”.

Human-centered design of upcoming human missions to Mars

Human missions to Mars are not only a matter of technology-centered engineering, it is foremost a matter of human-centered design (HCD) where technology, organizations and people roles should be co-designed in a participatory and agile way. Major human-centered components are trajectory and propulsion (defining HCD in terms of time), life-support (physiological, psychological and social factors), exploration (jobs during flights and on the planet) and anticipation of a Martian civilization (governance, natural and artificial resource management). I will review a few experiments that were conducted so far, such as Mars-500, MDRS and what we are doing in HCD, such as key cognitive and social concepts of operations that rely on situation awareness and decision-making, complexity analysis, dealing with the unexpected, automation and autonomy, and collaborative work. I will develop the perspective that human-systems integration (HSI) is a matter of integrating HCD and systems engineering. We then need to orchestrate the design of the various structures and functions involved in human Mars operations. This orchestration can be made using modeling and human-in-the-loop simulations looking for emerging cognitive and physical functions towards the definition of underlying cyber-physical systems. HSI can be managed in terms of design flexibility, resource commitments, and human-systems knowledge.

Analytics – The Agile Way by Phil Simon

Analytics – The Agile Way by Phil Simon

Approximation of An Experimental Model Obtained in A Testing Machine for use in an Industrial Production Machine

Design of experiments (DOE) is a powerful tool that allows performing the modeling and analysis of the influence of factors of the process on the specified variables, which are often called response variables. Being a systematic procedure to analyze the effect of the response variables, and the controllable factor s that are modified during the execution of the experiment.Within the different strategies of the design of experiments, the factorial design is one of the most widely used. The problem with factorial designs is a large number of experiments that may be ne cessary.It is not convenient to perform the tests of experimental designs in an industrial machine, because it is more difficult to control and measure the variables accurately and in an agile way. Moreover, if an industrial machine has to be used, it is n ot feasible to perform a large number of trials, because it would be necessary to interrupt production.Therefore it was decided to conduct an investigation in which experimental models were obtained in a testing machine that was specially developed for tha t purpose. Later, data were collected from an industrial machine that performed the same process, and with the same machining conditions. The problem to be solved is to what extent the models obtained in the testing machine can be adjusted or not to predic t the process in industrial machines.A study was done by means of regression analysis of the correlation between the valuesobtained in the test machine and those obtained in the industrial machine. It was observed that the trends of roughness parameters gi ven by the models obtained in the testing machine are similar to those obtained in the industrial process. For this reason it is feasible to adapt the models obtained in the testing machine for the industrial machine

Energy Efficiency Aware Task Assignment with DVFS in Heterogeneous Hadoop Clusters

While Hadoop ecosystems become increasingly important for practitioners of large-scale data analysis, they also incur tremendous energy cost. This trend is driving up the need for designing energy-efficient Hadoop clusters in order to reduce the operational costs and the carbon emission associated with its energy consumption. However, despite extensive studies of the problem, existing approaches for energy efficiency have not fully considered the heterogeneity of both workload and machine hardware found in production environments. In this paper, we find that heterogeneity-oblivious task assignment approaches are detrimental to both performance and energy efficiency of Hadoop clusters. Our observation shows that even heterogeneity-aware techniques that aim to reduce the job completion time do not guarantee a reduction in energy consumption of heterogeneous machines. We propose a heterogeneity-aware task assignment approach, E-Ant, that aims to improve the overall energy consumption in a heterogeneous Hadoop cluster without sacrificing job performance. It adaptively schedules heterogeneous workloads on energy-efficient machines, without a priori knowledge of the workload properties. E-Ant employs an ant colony optimization approach that generates task assignment solutions based on the feedback of each task’s energy consumption reported by Hadoop TaskTrackers in an agile way. Furthermore, we integrate DVFS technique with E-Ant to further improve the energy efficiency of heterogeneous Hadoop clusters. It relies on a DVFS controller to dynamically scale the CPU frequency of each slave machine in response to time-varying resource demands. Experimental results on a heterogeneous cluster with varying hardware capabilities show that E-Ant with DVFS improves the overall energy savings for a synthetic workload from Microsoft by 23 and 17 percent compared to Fair Scheduler and Tarazu, respectively.

Enabling Normalized Systems in Practice – Exploring a Modeling Approach

Contemporary organizations are required to adapt to a changing environment in an agile way, which is often deemed very challenging. Normalized Systems (NS) theory attempts to build highly evolvable software systems by using systems theory as its theoretical underpinning. A modeling method which supports the identification of the NS elements, required for building NS sofware in practice, is currently missing. Therefore, the paper introduces an approach for creating both data models and processing models in the context of NS, as well as their integration. It is discussed how these models can be taken as the input for the actual creation of evolutionary prototypes by using an earlier developed supporting tool. The modeling approach and its suitability for feeding the tool are evaluated to discover their current strengths and weaknesses.

EXPLORING ENHANCEMENTS TO THE AGILE APPROACH FOR MID-SIZED ENTERPRISES IN THE SERVICES SECTOR

Companies need to thrive in a dynamic environment, responding to it in an agile way. Within a company’s ICT domain, a key to achieving agility is to use agile software development. Experience, together with a literature review, has shown that the agile software development family of methods does not naturally fit into the context of medium to large enterprises. This article focuses on the challenges associated with agile software development. The main contribution of the article is to affirm that a class-of-problems exists – i.e., that many practitioners face challenges in implementing existing agile software development approaches successfully in medium to large enterprises. We also gather data via multiple interviews to show that the class-of-problems exists in a real-world enterprise that currently applies agile software development in medium-sized governmental bodies.

Between a rock and a hard place: Management and implementation teams’ expectations of project managers in an agile information systems delivery environment

Background: To address the low success rate in information system (IS) projects, organisations in South Africa are adopting agile implementation methodologies. Agile delivery environments advocate an iterative approach where autonomous, self-organising teams share project management (PM) activities. This encroaches on the traditional project manager role. Are project managers still relevant in agile delivery environments and how should they adapt?Objectives: This case study investigated how project managers could adapt to agile IS implementation environments to remain relevant. Specifically, the views of their key stakeholders (the management and implementation teams) were elicited to provide insights into what is expected from agile project managers.Method: A qualitative, inductive content analysis approach using purposive sampling was used to identify 13 participants (comprising management and implementation team members) within a large South African insurance company. Semi-structured interviews were conducted with all participants.Results: The management and implementation teams agreed that PM remains highly relevant in an agile environment for ensuring project governance including delivery, risk management, reporting and budgeting. There was, however, disagreement between the management and implementation teams on project management interaction with the implementation team. Management preferred a command and control type project manager, while the implementation team favoured a more inclusive, facilitative PM style.Conclusion: To remain viable in an agile IS project implementation environment within large corporates, project managers need to be aware of what various stakeholders expect of them. They need to retain some of the classic PM functions while adapting to the interpersonal and collaborative requirements of the agile way.

A Novel Nested Assignment Algorithm for Agile Command and Control Organization

The Command and Control (C2) system plays the dominant role in the military organization. With the incensement of military mission’s complexity, the uncertainty and unfamiliar are the major challenges for the tasks and planners assignment in C2 organization. Recently, the agility is highlighted in the next generation of C2 organization, called agile C2. In order to address on assignment for decision-maker and tasks in the agile way, we present a novel assignment algorithm based the nested optimization. We discretize the time-domain in the way of horizon partition. Based the smaller time scale, the nested assignment for decision-maker and tasks can be improved in both time and space complexity. In a simulated case of multi-force joint operation, the proposed algorithm shows the significant improvement compared to the baseline assignment of C2 organization.

Towards emergence phenomenon in business process management

Abstract A standard solution regarding business process management automation in enterprises is the use of workflow management systems working by the Rule-Based Reasoning approach. In such systems, the process model which is designed entirely before the implementation has to meet all needs deriving from business activity of the organization. In practice, it means that great limitations arise in process control abilities, especially in the dynamic business environment. Therefore, new kinds of workflow systems may help which typically work in more agile way e.g. following the Case-Based Reasoning approach. The paper shows another possible solution – the use of emergence theory which indicates among other conditions required to fulfill stimulation of the system (for example the business environment) to run grass-roots processes that lead to arising of new more sophisticated organizing forms. The paper also points the using opportunity of such techniques as the processing of complex events to fulfill key conditions pointed by the emergence theory.

Imbalanced target prediction with pattern discovery on clinical data repositories

BackgroundClinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted. We specifically target for interpretability for domain users where the model can be conveniently explained and applied in clinical practice.MethodsWe propose an interpretable pattern model which is noise (missing) tolerant for practice data. To address the challenge of imbalanced targets of interest in clinical research, e.g., deaths less than a few percent, the geometric mean of sensitivity and specificity (G-mean) optimization criterion is employed, with which a simple but effective heuristic algorithm is developed.ResultsWe compared pattern discovery to clinically interpretable methods on two retrospective clinical datasets. They contain 14.9% deaths in 1 year in the thoracic dataset and 9.1% deaths in the cardiac dataset, respectively. In spite of the imbalance challenge shown on other methods, pattern discovery consistently shows competitive cross-validated prediction performance. Compared to logistic regression, Naïve Bayes, and decision tree, pattern discovery achieves statistically significant (p-values < 0.01, Wilcoxon signed rank test) favorable averaged testing G-means and F1-scores (harmonic mean of precision and sensitivity). Without requiring sophisticated technical processing of data and tweaking, the prediction performance of pattern discovery is consistently comparable to the best achievable performance.ConclusionsPattern discovery has demonstrated to be robust and valuable for target prediction on existing clinical data repositories with imbalance and noise. The prediction results and interpretable patterns can provide insights in an agile and inexpensive way for the potential formal studies.

Achieving agility using business model stress testing

Business Model (BM) Innovations aim at making systemic changes in the business logic of companies when they are bringing innovative products and services to the market. Companies should be sensitive to changes in their business environment and able to modify their BMs in an agile way. To assess the agility of BMI during specific market entry situations, this paper uses a method that stress tests the value proposition and the components of a BM against contingent uncertainties. We present three qualitative case studies of companies that differ in their market entry approach. Starting from their strategic orientation, these case companies’ stress test their Business models and BM components, using a scenario-based identification of uncertainties. The BM Stress Test method contributes to a quick understanding of the components their BM needs to monitor, reconsider, or improve. Such stress testing helps enhance business agility. The research contributes to market strategy and business modelling research by introducing BM Stress Testing as a new method that can achieve and maintain agility regarding BM uncertainties.

Short-Term Physiological Strain and Recovery among Employees Working with Agile and Lean Methods in Software and Embedded ICT Systems

ABSTRACTAgile work practices have become popular. Although they hold great promise regarding well-being at work, systematic scientific research on this connection is scarce. This article aims to capture the current situation by measuring the state of mental workload using physiological indicators and by comparing high and low perceived agile work. Is the agile way of working associated with well-being at work? Three software teams and four embedded development teams were used in the different phases of applying agile methods. We conducted a baseline survey on perceived agile work in the team and carried out physiological measurements three times in a working period. Repeated-measure procedure was used to analyze the effects. The results provide evidence that agile work could even out workload during a working period, i.e. maintain sustainable pace. The results of the low agile work were in line with the assumption that work will accumulate at the end of the period because of loose planning and a lack of frequent checking. Therefore, workers also felt more strain from the pressure of deadlines.

An Agile Business Process Improvement Methodology

Adoption of business process improvement strategies are now a concern of most organisations. Organisations are still facing challenges and finding transient solutions to immediate problems. The misalignment between IT solutions and organisational aspects evolves across space and time showing discrepancies. Unfortunately, existing business process approaches are not according with continuous business process improvement involving business stakeholders. Considering this limitation in well-known Business Process (BP) methodologies, this paper presents a comparative study of some approaches and introduces agility in the Business Process and Practice Alignment Methodology (BPPAM). Our intention is to present observed problems in existing approaches and introduce agility in our proposal to address features, like the alignment between daily work practices and business process descriptions, in a simple and agile way.

A model-driven approach to generate and deploy videogames on multiple platforms

Currently, videogame development for mobile devices is a highly profitable and competitive industry worldwide. This profitability can be ascribed to the popularity that new technologies such as smartphones and tablets have acquired over the last few years. To increase competitiveness, we use a model driven engineering (MDE) approach to develop multi-platform videogames in a quick and easy manner. MDE helps us to reduce the number of errors, the amount of time required and the development costs and favors a productivity increment. The aim of this work is to present an approach for the agile development of multi-platform videogames by using high-level abstraction models. We offer a feasible solution supported by a tool that allows the development of videogames in a simple and agile way. An empirical validation is presented through a use case where the viability of our approach is shown in comparison with that of other tools. Finally, a survey shows the users’ perception of the solution with the objective of validating the use case results. The given use case indicates that our approach is suitable for improving videogame development. The survey indicates that users think that it is possible to model videogames and generate the corresponding applications with our approach.

An Approach to Reduce Commissioning and Ramp-up time for Multi-variant Production in Automated Production Facilities

A key requirement for future production facilities is to perform new production processes in a flexible and adaptive way with available and known resources. In this context, a comprehensive description (ontology) of involved components has a high significance. If certain technological aspects are missing during a production process, the production control should respond in a dynamic, versatile and adaptive (agile) manner to the overall value network. The possibility to describe the requirements of products for the necessary processes in the same namespace like the requirements of the necessary processes for the resources is a prerequisite to enable this behavior. Afterwards the different requirements will be placed in relation to the respective requirements. The aim is to define the necessary processes for the production based on the description of the product and the known resources in an agile way. Due to this a framework for a comprehensive description of automated production facilities, products and processes is described in this paper. The idea is that based on this framework a production facility can change the produced products without dedicated commissioning and ramp-up phases.

Traditional and Agile Product Development in a Hyperconnected World: Turning Weaknesses into Strengths

Globalization and its inherent need to be highly connected lead to increasing application of information technology in business practice. Business Intelligence, Enterprise Resource Planning, Application Development, Cloud Computing and Customer Relationship Management have currently been rated to be the most important trends in this context. By using SWOT analysis, the paper presents potential ways to improve traditional and agile product development approaches by means of hyperconnectivity. For that, we assume two organizations (one developing products traditionally and another one developing products in an agile way), firstly, in a connected and, secondly, in a hyperconnected environment. The results show strategical improvement potentials towards a more extensive usage of hyperconnectivity in product development. Consequently, hyperconnectivity is both the pain and the medicine.