Using Analytical Information for Digital Business Transformation through DataOps: A Review and Conceptual Framework

Organisations are increasingly practising business analytics to generate actionable insights that can guide their digital business transformation. Transforming business digitally using business analytics is an ongoing process that requires an integrated and disciplined approach to leveraging analytics and promoting collaboration. An emerging business analytics practice, Data Operations (DataOps), provides a disciplined approach for organisations to collaborate using analytical information for digital business transformation. We propose a conceptual framework by reviewing the literature on business analytics, DataOps and organisational information processing theory (OIPT). This conceptual framework explains how organisations can employ DataOps as an integrated and disciplined approach for developing the analytical information processing capability and facilitating boundary-spanning activities required for digital business transformation. This research (a) extends current knowledge on digital transformation by linking it with business analytics from the perspective of OIPT and boundary-spanning activities, and (b) presents DataOps as a novel approach for using analytical information for digital business transformation

Enhancing Information Security Risk Management with Security Analytics: A Dynamic Capabilities Perspective

The importance of information security risk management (ISRM) and its potential strategic role in protecting organisational information assets is widely studied in literature. Less attention is given to how ISRM can be enhanced using security analytics to contribute to a competitive advantage. This paper proposes a model showing that security analytics capabilities (the ability to effectively use security data for informed security related decision making) and ISRM capabilities (the ability to effectively identify and protect organizational information assets) indirectly influence competitive advantage in ISRM through two key mediating links: analytics-enabled ISRM capabilities (the ability to effectively leverage insights gleaned from security data to make informed ISRM decisions) and ISRM dynamic capabilities (the ability to reconfigure analytics-enabled ISRM capabilities to address turbulent environments). Environmental turbulence moderates the process by which security analytics and ISRM capabilities influence competitive advantage. The paper concludes by calling for evaluation and refinement of the research model

Leveraging Data and Analytics for Digital Business Transformation through DataOps: An Information Processing Perspective

Digital business transformation has become increasingly important for organisations. Since transforming business digitally is an ongoing process, it requires an integrated and disciplined approach. Data Operations (DataOps), emerging in practice, can provide organisations with such an approach to leverage data and analytics for digital business transformation. This paper proposes a framework that integrates digital business transformation, data analytics, and DataOps through the lens of information processing theory (IPT). The details of this framework explain how organisations can employ DataOps as an integrated and disciplined approach to understand their analytical information needs and develop the analytical information processing capability required for digital business transformation. DataOps-enabled digital business transformation, in turn, improves organisational performance by improving operational efficiency and creating new business models. This research extends current knowledge on digital transformation by bringing in DataOps and analytics through IPT and thereby provides organisations with a novel approach for their digital business transformations

Managing and Making Sense of Data to Drive Digital Transformation: A Case Study

We explore how organizations manage and make sense of data collaboratively to drive digital transformation. We present the results of an in-depth case study of a financial organization that used Data Operations (DataOps) - a collaborative data management practice to transform its digital-first offering initiative and thereby redefining its value proposition. Drawing on sensemaking theory, we develop a process model that explains how organizations use DataOps to perceive cues through data democratization, extract plausible and comprehensive insights from data through data storytelling to make interpretations, and leverage data products to take actions that drive data-driven digital transformation. Our findings have implications for data-driven digital transformation as we show how DataOps constitutes a new class of data management practices that enable collaboration between data managers and data consumers and allow organizations to make evidence-based decisions to drive their digital transformation

TOWARD SUSTAINABLE BEHAVIOUR CHANGE: AN APPROACH FOR CYBER SECURITY EDUCATION TRAINING AND AWARENESS

Effective information security education, training and awareness (SETA) is essential for protecting organisational information resources. Whilst most organisations invest significantly in implementing SETA programs, the number of incidents resulting from employee noncompliance with security policy are increasing. This trend may indicate that many current SETA programs are not as effective as they should be. We argue that existing SETA programs are not optimal in changing employee behaviour to comply with security policy as they lack a theoretical base that can inform and guide the development of SETA programs. This study draws on knowledge from the medical domain on the use of theory to design an intervention to bring about sustainable behaviour change. The paper therefore adopts an intervention design process, based on the behaviour change wheel (BCW) framework, to develop a theory-informed SETA development process. The paper demonstrates the use of BCW in the analysis of the target behaviour and the selection of suitable strategies and techniques to change the target behaviour. The proposed SETA development process provides a sound basis for future empirical work including focus groups and action research

Enhancing Strategic Information Security Management in Organizations through Information Warfare Practices

Today’s organizations use control-centred security management systems as a preventative shield against a broad spectrum of attacks. However, these have proven to be less effective against the customized and innovative strategies and operational techniques used by Advanced Persistent Threats (APTs). In this short paper we argue that to combat APTs, organizations need a strategic-level shift away from a traditional prevention-cantered approach to that of a response-cantered one. Drawing on the information warfare (IW) paradigm in military studies, and using Dynamic Capability Theory (DCT), this research examines the applicability of IW capabilities in the corporate domain. We propose a research framework to argue that conventional prevention-centred response capabilities; such as incident response capabilities and IW-centred security capabilities can be integrated into IW-enabled dynamic response capabilities that improve enterprise security performance

Operationalising Analytics for Action: A Conceptual Framework Linking Embedded Analytics with Decision-Making Agility

Organisations are increasingly practising Business analytics (BA) to make data-driven business decisions amidst environmental complexities and fierce global competition. However, organisations find it challenging to operationalise BA outputs (such as analytical models, reports, and visualization) primarily due to a lack of (a) integrated technology, (b) collaboration and (c) governance. These factors inhibit organisations’ ability to make data-driven decisions in an agile manner. Embedded analytics, an emerging BA practice, has the potential to address these issues by integrating BA outputs into business applications and workflows, thereby promoting the culture of data-driven decision-making. In this research-in-progress paper, we integrate the diverse areas of literature on BA, embedded analytics, and dynamic capabilities theory and propose a research model that links embedded analytics to decision-making agility through the development of dynamic capabilities. The details of the framework highlight how organisations can get maximum value from data and analytics initiatives through operationalisation of BA outputs

A framework of dynamic cybersecurity incident response to improve incident response agility

© 2018 Dr. Humza NaseerThe modern enterprise uses risk-driven and control-centered security management systems to protect information resources and sustain competitive advantage. Such systems have proven to be quite effective in the prevention of threats such as those exploiting common vulnerabilities. However, they are not very well suited to response against threats that are unpredictable, complex and evolving such as Advanced Persistent Threats. The complex and dynamic nature of these threats demands a sophisticated, timely and agile response capability to collect, integrate and analyse information to direct strategic and operational security measures. Real-time analytics is a specialized business analytics capability that helps organizations to collect, integrate, and analyse business events as they occur. While the ability of real-time analytics to deliver instant business insights has gained much attention in the literature, there has been limited research on how it can help enterprises improve agility in their cybersecurity incident response. This study addresses the aforementioned research gap through investigating the research question: How can organizations improve agility in their cybersecurity incident response process using real-time analytics? Drawing from dynamic capabilities theory, the study collected qualitative data from three large financial organizations and used a process of data comparison that engages in simultaneous analysis and exploration. The results informed a framework of dynamic cybersecurity incident response that explains how organizations using real-time analytics are able to develop higher order real-time analytics-enabled dynamic capabilities in incident response such as real-time situation awareness, dynamic risk assessment, and cyber threat intelligence generation. These dynamic capabilities help organizations to execute dynamic incident response strategies including active defence, continuous monitoring, and active reconnaissance. The real-time analytics enabled dynamic capabilities together with dynamic incident response strategies infuse agile characteristics such as swiftness, flexibility and innovation in the cybersecurity incident response process, which in turn, lead to positive outcomes in enterprise security performance and delivers both strategic and economic benefits. The framework also provides a comprehensive view of the factors that support and hinder the development of dynamic capabilities in the cybersecurity incident response process and execution of dynamic incident response strategies. The details of the framework contribute to the literature on business analytics capabilities, dynamic capabilities, cybersecurity incident response strategies, and business process agility. The findings of the study provide a useful stepping stone for future studies on how to improve agility in cybersecurity incident response process

BUSINESS ANALYTICS IN INFORMATION SECURITY RISK MANAGEMENT: THE CONTINGENT EFFECT ON SECURITY PERFORMANCE

The process of information security risk management (ISRM) enables an organization to not only identify risks specific to its information and assets, but also to assess the impact and likelihood of a threat occurrence. Despite significant interest and investment in ISRM, its organizational practice still has deficiencies since it is not considered a standard management process of an organization and lacks evidence based decision making. Business analytics (BA) presents organizations with a unique opportunity to base their ISRM upon continuous monitoring and data analysis, thereby helping executives make timely, data driven security decisions in a proactive manner. In this research in progress paper, we utilize Resource-based Theory (RBT) to develop a research model that explains how interaction between the capabilities of security analytics and ISRM results in the development of an enhanced, high level analytics enabled ISRM. This in turn impacts overall security performance. We define the model based on an extensive analysis of the BA and ISRM literature. The model also provides a basis for future empirical work including focus groups, case studies and a survey

Weaponizing information systems for political disruption: The Actor, Lever, Effects, and Response Taxonomy (ALERT)

Information systems continue to be used by actors who want to undermine public institutions and disrupt political systems. In recent times, actors have engaged in acts of information warfare ranging from attempts to compromising voting systems, to spreading false propaganda and even direct attacks on public infrastructure via information systems. Initial analysis points to the fact that most of these attempts have been successful in achieving their intended objectives. Given this reality, we expect them to intensify and be more creative in the future. In this paper we draw on a critical analysis of the role of information systems in creating political disruption to propose that information systems can be ‘weaponized’ by compromising their goals and values even while they remain protected. Building on this proposition we develop a risk-based Actor, Lever, Effects and Response Taxonomy (ALERT) to assist security practitioners and policymakers to analyze and respond to attacks enabled by information systems aimed at political disruption. We illustrate the utility of ALERT using representative examples of weaponized attacks from credible news sources. Finally, we leverage the insights gained from ALERT to propose a theoretical framework where we assert that over time as actors gain maturity and experience using levers to disrupt political systems, so too does the public sector gain experience in response thus building their response capacity. This dynamic relationship increasingly pushes both actors and defenders to come up with more innovative, agile and sophisticated methods to weaponize and respond to information systems enabled attacks.</p