Achieving Competitive Sustainable Advantages (CSAs) by Applying a Heuristic-Collaborative Risk Model

Author:

Nunes Marco,Bagnjuk Jelena,Abreu AntónioORCID,Saraiva Célia,Nunes Edgar,Viana Helena

Abstract

Increasing disruption and turmoil continuously challenges organizations regarding the achievement of short- and long-term objectives. Such a hostile environment results from both the natural evolution of the business landscape complexity and the emergence of unpredictable disruptive evets such as the COVID-19 pandemic. More than ever, organizations should continuously develop business strategies that help them to become more agile, adaptative, sustainable, and effectively respond to the countless business risks (threats and opportunities). Innovation, such as the development and implementation of new technology, new ways of thinking and executing work, are just some of the major factors that can help organizations to increase their likelihood of success. In this work, is proposed the incorporation of a heuristic risk model into a typical organizational business intelligence architecture, to identify collaborative critical success factors across the different phases of a project life cycle which can be used to guide, monitor, and increase the success outcome likelihood of ongoing and upcoming projects. Some benefits of the incorporation include: a higher speed regarding the collection and treatment process of project collaborative data, the output of more accurate results with residual bias associated, a timely and efficient 360° view regarding the identification of project collaborative risks, and the impact (positive or/and negative) of these on a project’s outputs and outcomes. Finally, the model capabilities of performing descriptive, predictive, and prescriptive analysis, enables the generation of unique and actionable project’s lessons learned which can be used to make more data-informed decisions, and thus enhances the achievement of sustainable competitive advantages. The development and implementation of the proposed incorporation is illustrated with a with a real case study.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development

Reference60 articles.

1. Transforming physical enterprise into a remote organization : Transformation impact: digital tools, processes and people

2. Leading change: why transformation efforts fail

3. Principles of Big Data Preparing, Sharing, and Analyzing Complex Information;Berman,2013

4. The CRISP-DM model: The new blueprint for data mining;Shearer;J. Data Warehous.,2000

5. Data Science Foundations: Data Mining LinkedIn Learninghttps://www.linkedin.com/learning/data-science-foundations-data-mining/text-mining-algorithms?u=77012418

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