A Business Analytics Maturity Perspective on the Gap between Business Schools and Presumed Industry Needs

Business analytics is a fast-growing job market for business school graduates. Hence, researchers have made many calls to enhance business analytics training in business schools to meet the growing market demand for analytics-savvy employees. A growing set of business analytics courses have begun to address these calls. In this paper, we examine the maturity of business analytics offerings in business schools in the United States by analyzing current business analytics-related course offerings of the top 104 business schools (363 courses) and 20 unranked business schools (51 courses) in the United States. We analyze these data by examining the types of courses offered and rank the schools based on their maturity levels in terms of business analytics offerings. Our findings indicate that, to the extent that these schools reflect what is happening across the nation, business schools still have a long way to go before they reach higher levels of business analytics maturity and that they are not yet in an ideal position to serve the presumed industry needs. We offer actionable recommendations

Impact of MBA Programs’ Business Analytics Breadth on Salary and Job Placement: The Role of University Ranking

Although many business schools have started to offer business analytics programs and courses for their MBA students, they lack understanding about how these efforts translate into job market gains for their graduates and whether all business schools have a level playing field. To bridge this gap, we use signaling theory to investigate the impacts that the business analytics breadth (BAB) level and university ranking of MBA programs have on graduates’ future employment success in terms of salary and job placement. We collected and analyzed data on business analytics-relevant courses that the top 89 business schools in the United States according to Bloomberg (bloomberg.com) offered. Our findings show the vital role of university ranking in determining the efficacy of BAB to produce job market gains for students: university ranking moderated the effect of business analytics offerings on post-graduation salary and job placement. These findings provide interesting insights for researchers and business schools interested in understanding the return on investment in business analytics programs

Building a Business Data Analytics Graduate Certificate

In this paper we present the evolution of the Business Data Analytics Graduate Certificate (BDA Certificate) at our institution, Loyola University Chicago. This certificate is a successful and expanding program that attracts a diverse group of dynamic professionals from local, national, and international populations. The program evolution described in this paper involves multiple revisions of the curriculum, additions, and subtractions of individual courses, expansions of delivery methods, and program name changes. The core principles of acknowledging the centrality of data, mandating the modeling-based course sequencing, and recognizing the proper role of software tools, are outlined and recognized as the foundation of the program’s success

Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

A Longitudinal Analysis of Job Skills for Entry-Level Data Analysts

The explosive growth of the data analytics field has continued over the past decade with no signs of slowing down. Given the fast pace of technology changes and the need for IT professionals to constantly keep up with the field, it is important to analyze the job skills and knowledge required in the data analyst and business intelligence (BI) analyst job market. In this research, we examine over 9,000 job postings for entry-level data analytics jobs over five years (2014-2018). Using a text mining approach and a custom text mining dictionary, we identify a preliminary set of analytic competencies sought in practice. Further, the longitudinal data also demonstrates how these key skills have evolved over time. We find that the three biggest trends include proficiency with Python, Tableau, and R. We also find that an increasing number of jobs emphasize data visualization. Some skills, like Microsoft Access, SAP, and Cognos, declined in popularity over the time frame studied. Using the results of the study, universities can make informed curriculum decisions, and instructors can decide what skills to teach based on industry needs. Our custom text mining dictionary can be added to the growing literature and assist other researchers in this space

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

Towards a Framework for Smart Manufacturing adoption in Small and Medium-sized Enterprises

Smart Manufacturing (SM) paradigm adoption can scale production with demand without compromising on the time for order fulfillment. A smart manufacturing system (SMS) is vertically and horizontally connected, and thus it can minimize the chances of miscommunication. Employees in an SME are aware of the operational requirements and their responsibilities. The machine schedules are prepared based on the tasks a machine must perform. Predictive maintenance reduces the downtime of machines. Design software optimizes the product design. Production feasibility is checked with the help of simulation. The concepts of product life cycle management are considered for waste reduction. Employee safety, and ergonomics, identifying new business opportunities and markets, focus on employee education and skill enhancement are some of the other advantages of SM paradigm adoption. This dissertation develops an SM paradigm adoption framework for manufacturing SMEs by employing the instrumental research approach. The first step in the framework identified the technical aspects of SM, and this step was followed by identifying the research gaps in the suggested methods (in literature) and managerial aspects for adopting SM paradigm. The technical and the managerial aspects were integrated into a toolkit for manufacturing SMEs. This toolkit contains seven modular toolboxes that can be installed in five levels, depending on an SME’s readiness towards SM. The framework proposed in this dissertation focuses on how an SME’s readiness can be assessed and based on its present readiness what tools and practices the SMEs need to have to realize their tailored vision of SM. The framework was validated with the help of two SMEs cases that have recently adopted SM practices

Analytics in the Pursuit of Knowledge: Adapting the Knowledge Pyramid

Advances in storage leading to the Internet of Things (IOT) and Big Data has exponentially increased the Data aspect of the traditional Knowledge Pyramid - Data-Information-Knowledge-Wisdom (DIKW). This paper presents an adaptation of the Knowledge Pyramid as an Analytics Pyramid in which Time is posited to represent Wisdom as the pinnacle achievement when pursuing knowledge. Analogies of the DIKW are presented from the Analytics Pyramid as Description-Aggregation-Modeling-Time. Implementing the premise of the Analytics Pyramid focuses on an interative/repetitive movement of both individuals and organizations through all Description-Aggregation-Modeling-Time stages in order to build and obtain the Wisdom pursued in the traditional Knowledge Pyramid. This model reinforces organizational learning and the importance of adaptability when pursuing knowledge. In addition, the wisdom gained from analytics is only recognized when monitored business processes are longitudinal in nature. Organizational analytics must rely on the recognition of a changing environment (Time) in order to adapt

Servitization research: A review and bibliometric analysis of past achievements and future promises

Manufacturing firms are increasingly adopting a strategy known as 'servitization' to add services to existing product-based offerings to stimulate additional revenue and growth. While the emerging research domain of servitization is mobilizing relevant knowledge across academic establishments, the present study aims to perform a comprehensive bibliometric analysis to organize the prior knowledge in this area, more importantly, highlights areas for future research. This study acknowledges important contributions from authors and organizations, as identified through analyses of citation chains and co-authorship networks. Next, a co-citation analysis of the prior literature is used to identify four main thematic areas relating to capability development, customer involvement, business models, and transformational challenges for servitization. Finally, the dynamic co-citation analysis technique reveals the development of these thematic areas. This study assumes importance in the extant literature by delivering valuable insights from the prior research on servitization and by providing guidance for future avenues of study.publishedVersio

Servitization research : A review and bibliometric analysis of past achievements and future promises

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