What do Employers expect from Business Analysts and is it captured by the “Business Analysis Body of Knowledge” (BABOK)?

Emerging professions need to define their role and contributions to business and society. An important part of this is setting policies and definitions of what constitutes a professional and professional practice in their discipline. This information is increasingly being captured and codified using tools such as Bodies of Knowledge, Quality Frameworks and Codes of Practice. The International Institute for Business Analysis defined a Body of Knowledge for Business Analysis (BABOK). This paper reports on a longitudinal survey of 240 SEEK advertisements over a six year period investigating how closely the skills and knowledge required for Business Analysis positions matched those defined within BABOK. This exploratory and qualitative study used secondary sources, so generalizability of results has limitations. Nevertheless, interesting patterns were observed. There was strong evidence that the “Competencies” defined within BABOK are sought by employers. However, surprisingly little reference was made to many of the BABOK Knowledge Areas

Investigating the Role of Enterprise Architecture in Big Data Analytics Implementation: A Case Study in a Large Public Sector Organization

Big Data Analytics (BDA) offers capabilities that can support a wide range of business areas across an organization. Organizations are increasingly turning to Enterprise Architecture (EA) to manage BDA implementation complexities. Through a case study in a large public sector organization, how EA supports various stages of BDA implementation is examined. The findings show that EA can address BDA challenges through 18 specific roles, which are categorised into four domains: Strategy (6 roles), Technology (4 roles), Collaboration (3 roles) and Governance (5 roles). While EA appears to have the most prominent role in strategy planning process, our study also identifies factors that can lead to the ineffectiveness of EA roles, such as frequent changes in business strategy. This study offers important implications to research and practice in EA and BDA implementation

Data Analytics Capabilities for Digital Service Development: A Case Study

Data analytics capabilities (DAC) have become important for business organizations in delivering successful digital services to their customers. The success of digital services depends on how efficiently business organizations can deploy DAC in association with other organizational capabilities. Prior information systems (IS) literature has also argued the importance of IS capabilities for digital service development. However, few studies have examined how DAC and IS capabilities will work together for digital service development. To address the research gap, we conducted a case study in a forest machine manufacturing organization. The research findings revealed that IS capabilities such as IS skills, IS infrastructure, and IS-enabled intangibles facilitated DAC’s technical, managerial, and organizational dimension for digital service development. This study contributes to the DAC literature by investigating the role of DAC and IS capabilities in developing digital services in business organizations

Four facets of a process modeling facilitator

Business process modeling as a practice and research field has received great attention in recent years. However, while related artifacts such as models, tools or grammars have substantially matured, comparatively little is known about the activities that are conducted as part of the actual act of process modeling. Especially the key role of the modeling facilitator has not been researched to date. In this paper, we propose a new theory-grounded, conceptual framework describing four facets (the driving engineer, the driving artist, the catalyzing engineer, and the catalyzing artist) that can be used by a facilitator. These facets with behavioral styles have been empirically explored via in-depth interviews and additional questionnaires with experienced process analysts. We develop a proposal for an emerging theory for describing, investigating, and explaining different behaviors associated with Business Process Modeling Facilitation. This theory is an important sensitizing vehicle for examining processes and outcomes from process modeling endeavors

Entering the Digital Era – The Impact of Digital Technology-related M&As on Business Model Innovations of Automobile OEMs

Digital technologies have reached the sphere of industrial-age, primarily physical industries, thus forcing incumbent firms to digitally innovate their business models. Employing a longitudinal dataset of the world’s largest automobile manufacturers from 2000 to 2013, we found empirical evidence of a positive effect of digital technology–related mergers and acquisitions (M&As) on digital business model innovativeness. Moreover, this effect is enhanced by previous non-digital M&A experience, a diversified M&A history, as well as early experience with digital technology–related M&As. Consequently, our findings reveal that OEMs acquiring complementary and heterogeneous external knowledge on digital technologies and possessing the absorptive capacity to integrate as well as commercialize this type of knowledge are better prepared to master the digital transformation of their business. Furthermore, we find indications of a positive influence of digital business model innovations on the expected future firm performance of automobile manufacturers, thus substantiating the importance of digital transformation

Improving Information Sharing: Local Fusion Centers and Their Role in the Intelligence Cycle

Abstract My Master’s Project focuses on local fusion centers and the need for improved information sharing practices among law enforcement partners. After the tragic event of September 11th in 2001, the Department of Homeland Security and the Department of Justice recognized a communication gap between law enforcement agencies and a lack of effective information sharing efforts. Fusion centers play a significant role in supporting both criminal and terrorist investigations due to their ability to act as a conduit between various law enforcement partners. Due to their important responsibilities as information sharing hubs that provide valuable analysis and dissemination of information and intelligence, it is essential to enhance information practices among the centers. My Master’s Project details a strategy that will assist in advancing information sharing capabilities among local fusion centers to better detect, investigate, mitigate, and avert threats. Specifically, this paper proposes a two-part strategy that entails strengthening current partnerships among fusion centers and law enforcement agencies and developing and implementing a standardized training program for intelligence analysts. Through improved collaborative efforts, fusion centers will be able to better identify, mitigate, and prevent threats to ensure public safety and the security of the country

Siri Humphrey: Design Principles for an AI Policy Analyst

This workgroup considered whether the policy analysis function in government could be replaced by an artificial intelligence policy analyst (AIPA) that responds directly to requests for information and decision support from political and administrative leaders. We describe the current model for policy analysis, identify the design criteria for an AIPA, and consider its limitations should it be adopted. A core limitation is the essential human interaction between a decision maker and an analyst/advisor, which extends the meaning and purpose of policy analysis beyond a simple synthesis or technical analysis view (each of which is nonetheless a complex task in its own right). Rather than propose a wholesale replacement of policy analysts with AIPA, we reframe the question focussing on the use of AI by human policy analysts for augmenting their current work, what we term intelligence-amplified policy analysis (IAPA). We conclude by considering how policy analysts, schools of public affairs, and institutions of government will need to adapt to the changing nature of policy analysis in an era of increasingly capable AI