Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture

A Management Maturity Model (MMM) for project-based organisational performance assessment

Common sense suggests that organisations are more likely to deliver successful projects if they have systems in place that reflect a mature project environment based on a culture of continuous improvement. This paper develops and discusses a Management Maturity Model (MMM) to assess the maturity of project management organisations through a customisable, systematic, strategic and practical methodology inspired from the seminal work of Darwin, Deming, Drucker and Daniel. The model presented is relevant to organisations, such as construction and engineering companies, that prefer to use the Project Management Body of Knowledge (PMBOK™ Guide) published by the Project Management Institute (PMI), but without the disadvantages of excessive time and cost commitments and a ‘one size fits all’ approach linked to rigid increments of maturity. It offers a game-changing advance in the application of project-based organisational performance assessment compared to existing market solutions that are unnecessarily complex. The feasibility of MMM is field-tested using a medium-sized data centre infrastructure firm in Tehran

Towards a business-IT alignment maturity model for collaborative networked organizations

Aligning business and IT in networked organizations is a complex endeavor because in such settings, business-IT alignment is driven by economic processes instead of by centralized decision-making processes. In order to facilitate managing business-IT alignment in networked organizations, we need a maturity model that allows collaborating organizations to assess the current state of alignment and take appropriate action to improve it where needed. In this paper we propose the first version of such a model, which we derive from various alignment models and theories

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft

Sustainability transition of production systems in the digital era - a systems perspective for building resilient and sustainable production systems

Locked-in manufacturing industries with highly structured operations and path dependencies are major contributors to the sustainability challenges currently burdening our planet. The effects of the ongoing pandemic, large-scale environmental impacts due to climate change and constant economic and social downturns are just some examples of these sustainability challenges. Increased digitalisation, awareness, global initiatives and regulations are pressuring manufacturing industries to transition towards sustainable development. However, there exists a multitude of interpretations in implementing sustainability in manufacturing industries. This makes proposing tangible actions to translate global initiatives complicated, thus hindering the sustainability transition process.The purpose of this thesis is to support the advancement of resilient production systems which can overcome sustainability challenges in the Industry 4.0 era. Hence, the thesis aims to investigate: (i) the systemic challenges of manufacturing companies which hinder their sustainability transition process and (ii) the mechanisms by which a systems perspective may be applied to support the transition. A mixed-methods approach was used to carry out the research, using qualitative and quantitative data from three (empirical and theoretical) studies. Applying a systems perspective helped reveal the challenges which hinder the sustainability transition of production systems. Understanding the production ‘system’ as a whole (and the underlying web of intricate dependencies and challenges in production operations) required this holistic perspective. Regarding the challenges, it was observed that manufacturing industries across different domains face three main types of challenge: internal (such as organisational routines, strategies and cultural mindset), external (such as regulations and collaboration with stakeholders) and technological (such as maturity levels and data). Three different enabling mechanisms were explored which may help overcome the above sustainability challenges and support the sustainability transition of manufacturing industries: (1) Industry 4.0 technologies, (2) dynamic capabilities and (3) resilience engineering. It was observed that Industry 4.0 technologies (such as artificial intelligence/machine learning, virtual development tools and sensors) are largely implemented to enable sustainable manufacturing in the form of resource efficiency and waste reduction. The results also revealed five microfoundations of dynamic capabilities – communication, organisation, resources, collaboration and technology. Based on Industry 4.0 opportunities to promote sustainability transitions, the results revealed five industrial resilience factors – robustness, agility, resourcefulness, adaptability and flexibility.This research contributes to theory by studying the convergence of emergent research topics, such as Industry 4.0, dynamic capabilities and resilience engineering in the context of sustainability transitions. In terms of a practical contribution, the sustainability transitions model developed in this thesis may support industrial practitioners in gaining a holistic understanding of the systemic challenges to sustainability, plus corresponding mechanisms to promote the sustainability transition of industries and the building of resilient production systems