Posts

Digital Transformation in the Resource and Energy Sectors

New paper co-authored with Parisa Maroufkhani, Robert K.Perrons, and Mohammad Iranmanesh published in Resources Policy.

The forces of digital transformation have delivered significant benefits like sustainable development and economic growth in a range of early adopter industries such as retail and manufacturing but, despite these potential benefits, the resource and energy sectors have been relative latecomers to digitalization simply because they are frequently slower to absorb new technologies. Here we present the results of a systematic literature review identifying the ways in which digital technologies have been applied in the oil and gas, mining, and energy domains. We applied content and descriptive analysis to evaluate and discuss 151 academic articles selected from the Scopus database. Two particularly interesting trends emerge from the analysis. First, over 75% of the papers were about the energy sector excluding the oil & gas industry, and only a small minority were from the mining or oil & gas sectors. Second, the most frequently discussed objective of digital transformation was the reduction of operational expenses. By surveying the different ways in which these innovations have been used in these industries and identifying trends and patterns in how digital technologies have been applied, the findings of this review deepen our understanding of the current state of digital technologies within the resource and energy sectors and, in so doing, shine a useful amount of light on the contributions that digital transformation has made to businesses in these sectors. This paper also highlights for future scholars, practitioners, and policymakers the six research areas that they should focus on in the future to help the resource and energy sectors accelerate the digital transformation process and improve their ability to deliver value with these innovations.

To access the article, please click [LINK]

International Dialogue: Emerging Technology for Response and Recovery

In a post-pandemic world, homeland security and border control agencies are being tasked with transforming how they respond and operate in a highly digitalized environment, while ensuring safety and prosperity of citizens and country.

Critical challenges that agencies face include the increasing volume of incidents and emergencies, overly complex trade and immigration processes, and evolving threats to borders and customs. Governments can leverage data, AI, intelligent automation, and other emerging technologies to address these complex challenges—while also freeing up critical human resources for high value missions.

To address these key issues, the IBM Center for The Business of Government hosted an international dialogue in September 2021 attended by CIOs and IT leaders with the Australia Department of Home Affairs, the Singapore Ministry of Home Affairs, and U.S. Department of Homeland Security Customs and Border Protection. These three dynamic leaders engaged in an interactive dialogue, joined by nearly 50 attendees from across the globe.

I draw on this discussion to produce a report providing keen insights about leveraging technologies to improve operations and security across borders. Participants addressed supply chain assurance, opening borders amidst the global fight against COVID-19, and the role of data, AI, and other technologies to support border security. The wide-ranging discussion also touched on addressing the needs of the future, anticipating new threats, and developing response strategies. These strategies—which rest on hybrid, multi-cloud environments—include operational capabilities that can stand up “on demand” to address rapidly shifting threats.

To read the report, please click here.

Interagency Collaboration within the City Emergency Management Network

New paper co-authored with Bo Fan and Zhoupeng Li published in Disasters.

Interagency collaboration within the city emergency management network: a case study of Super Ministry Reform in China

Emergencies continue to become ever more complex; responding to them, therefore, often is beyond the capabilities and capacities of any single public agency. Hence, collaboration among these actors is necessary to prepare for, respond to, and recover from such events. This seldom occurs in an effective or efficient manner, however. Drawing on resource dependence theory and the concept of social capital, this paper reveals that different types of collaborative relationships exist within the collaborative network. Super Ministry Reform of Emergency Management in China serves as a case in point. By evaluating network efficiency and classifying the collaborative relationships of involved government agencies, four types are identified: resource-redundant; resource-complementary; resource-dependent; and resource-isolated. The different influences of collaborative relationships explain why the reform is not that effective, although it has led to the merger of several core departments in the emergency management network. The findings are a reminder to consider network structure and collaboration types when engaging in institutional design.

To access the article: [LINK]
To access a full-text, read-only version of the article: [LINK]

 

Will AI ever sit at the C-suite table? The future of senior leadership

Graeme J. Watson, Vincent M. Ribiere, JakaLindi? and I have an article accepted in Business Horizons.

As the sophistication of artificial intelligence (AI) systems develop and AI becomes a key element of organizational strategy across a wide spectrum of industries, new demands are being placed on senior leaders. To understand the growing challenges leaders will face in the age of AI, we conducted interviews with 33 senior leaders in several countries across a wide range of industries. Our research highlights key capabilities and skills that leaders will require. Underlying these capabilities is a mindset oriented toward continuous learning and self-development, which will enable ongoing and rapid adaptation to change. Our findings identified the following key capabilities: digital know-how, data-driven focus, networking, ethics, and agility. To successfully navigate the coming era, senior leaders will need to focus on reskilling the workforce, recruiting and retaining highly skilled talent, building an intrapreneurial culture, and managing unprecedented changes in technologies and the nature of work.

To access the article [LINK]

Demystifying Analytical Information Processing Capability: Cybersecurity Incident Response

New paper published in Decision Support Systems

Little is known about how organizations leverage business analytics (BA) to develop, process, and exploit analytical information in cybersecurity incident response (CSIR). Drawing on information processing theory (IPT), we conducted a field study using a multiple case study design to answer the following research question: How do organizations exploit analytical information in the process of cybersecurity incident response by using business analytics? We developed a theoretical framework that explains how organizations respond to the dynamic cyber threat environment by exploiting analytical information processing capability in the CSIR process. This, in turn, leads to positive outcomes in enterprise security performance, delivering both strategic and financial benefits. Our findings contribute to the BA and cybersecurity literature by providing useful insights into BA applications and the facilitation of analytics-driven decision making in CSIR. Further, they contribute to IPT by providing new insights about analytical information needs, mechanisms to seek analytical information, and analytical information use in the process of CSIR.

To access the paper, please click here.

Data Governance – Cutter Business Technology Journal

An article I co-authored with Gregory S. Dawson (Arizona State University) and James S. Denford (Royal Military College of Canada) appears in the current issue of the Cutter Business Technology Journal. 

We focus our article on a fundamental organizational question: in a medium-to-large organization, should data governance be centralized or decentralized (or, possibly, federated)? There are pros and cons for both centralization and decentralization. The overall business strategy needs to be considered: in some conglomerates of disparate business lines, there may be little commonality to the information being managed by the various divisions. However, decentralization still causes duplication of effort and risks inconsistencies across the enterprise. The authors give concrete examples that link the IT governance modality — centralized or decentralized — with performance outcomes. They generally favor a centralized model and provide the reader with specific recommendations on how to centralize data governance in organizations and how to implement this model successfully.

The article is available here.

Coverage – Delivering Artificial Intelligence in Government – Government Matters

Dan Chenok, executive director of the IBM Center for the Business of Government, discussed my recently released report - Delivering Artificial Intelligence in Government: Challenges and Opportunities - on Government Matters

Also covered in Government Executive, Routefifty.comNextgov