Towards evaluation design for smart city development

Smart city developments integrate digital, human, and physical systems in the built environment. With growing urbanization and widespread developments, identifying suitable evaluation methodologies is important. Case-study research across five UK cities - Birmingham, Bristol, Manchester, Milton Keynes and Peterborough - revealed that city evaluation approaches were principally project-focused with city-level evaluation plans at early stages. Key challenges centred on selecting suitable evaluation methodologies to evidence urban value and outcomes, addressing city authority requirements. Recommendations for evaluation design draw on urban studies and measurement frameworks, capitalizing on big data opportunities and developing appropriate, valid, credible integrative approaches across projects, programmes and city-level developments

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Investigation of Leading Indicators for Systems Engineering Effectiveness in Model-Centric Programs

Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsThis technical report summarizes the research conducted by Massachusetts Institute of Technology under contract award HQ0034-19-1-0002 during July 22, 2019 – August 31, 2021. Involved research team members include: Dr. Donna H. Rhodes, Principal Investigator; Dr. Eric Rebentisch, Research Associate; and Mr. Allen Moulton, Research Scientist. Systems engineering practice is evolving under the digital engineering paradigm, including use of model-based systems engineering and newer approaches such as agile. This drives a need to re-examine the existing use of metrics and leading indicators. Early engineering metrics were primarily lagging measures, whereas more recent leading indicators draw on trend information to provide more predictive analysis of technical and programmatic performance of the engineering effort. The existing systems engineering leading indicators were developed under the assumption of paper-based (traditional) systems engineering practice. This research investigates the model-based implications relevant to the existing leading indicators. It aims to support program leaders, transitioning to model-based engineering on their programs, in continued use of leading indicators. It provides guiding insights for how current leading indicators can be adapted for model-based engineering. The study elicited knowledge from subject matter experts and performed literature review in identifying these implications. An illustrative case was used to investigate how four leading indicators could be generated directly from a model-based toolset. Several recommendations for future research are proposed extending from the study. A companion research study (“phase 2”) under contract HQ0034-20-1-0008 provides insights for the art of the possible for future systems engineering leading indicators and their use in decision-making on model-centric programs. For completeness, selected background information and illustrative case are included in the technical reports in both studies. This research aims to provide insights for current practice within programs transforming to digital engineering, for continued use of systems engineering leading indicators. Several recommendations for future research are proposed extending from results of the study.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Multi-domain maturity model for AI and analytic capability in power generation sector: A case study of ABB PAEN Oy

As more smart devices and smart meters are available on the market, industry actors offer AI and analytic suites and platforms where the data streams can be contextualized and leveraged in pre-made industry specific templates and model, together with self-serving machine learning environments. How can a traditional EPC company, use its domain knowledge in offering these AI and analytic suites. The assumption made is that there is no inherent value in the AI and analytics suite without data. How should this assumption be incorporated in projects executed before the operation phase where data from operation is non-existent.This thesis investigate which elements provide a value proposition in the AI and analytic suite and map this against the domain knowledge of the EPC company. The findings is a novel design in where both operational data is integrated into design for new projects. A survey is also conducted on the data utilization in the power generation sector based on the same elements. The findings is that while the granularity is low, the quality is good, with an overall maturity between managed and proactive data utilization, which indicate that there are few automated data streams, but that the data is available structurally and in a defined way

Problem reports and team maturity in agile automotive software development

Background: Volvo Cars is pioneering an agile transformation on a large scale in the automotive industry. Social psychological aspects of automotive software development are an under-researched area in general. Few studies on team maturity or group dynamics can be found specifically in the automotive software engineering domain. Objective: This study is intended as an initial step to fill that gap by investigating the connection between issues and problem reports and team maturity. Method: We conducted a quantitative study with 84 participants from 14 teams and qualitatively validated the result with the Release Train Engineer having an overview of all the participating teams. Results: We find that the more mature a team is, the faster they seem to resolve issues as provided through external feedback, at least in the two initial team maturity stages. Conclusion: This study suggests that working on team dynamics might increase productivity in modern automotive software development departments, but this needs further investigation.Comment: 5 page

Software process assessment and improvement using Multicriteria Decision Aiding - Constructivist

Software process improvement and software process assessment have received special attention since the 1980s. Some models have been created, but these models rest on a normative approach, where the decision-maker's participation in a software organization is limited to understanding which process is more relevant to each organization. The proposal of this work is to present the MCDA-C as a constructivist methodology for software process improvement and assessment. The methodology makes it possible to visualize the criteria that must be taken into account according to the decision-makers' values in the process improvement actions, making it possible to rank actions in the light of specific organizational needs. This process helped the manager of the company studied to focus on and prioritize process improvement actions. This paper offers an empirical understanding of the application of performance evaluation to software process improvement and identifies complementary tools to the normative models presented today

What determines product ramp-up performance? : a review of characteristics based on a case study at Nokia Mobile Phones

We present a conceptual model to explore the essential characteristics that affect product ramp-up performance in the consumer electronics industry, specifically in the mobile phones sector. Our findings are based on data analysis within Nokia’s mobile phones business group. Fast product ramp-ups are particularly critical for companies in which short product lifecycles prevail and in which development teams are required to work on new development projects than spending time with ramp-up support. Our model analyzes, extends and structures the results from other studies into five main characteristics: the product architecture, the product development process, the logistics system, the manufacturing capability and the external environment. We discuss the factors that describe and represent these five main characteristics on a quantitative basis and assess the impact of these characteristics on ramp-up performance with different measures in the model