Thilini Ariyachandra

Critical Success Factors in Business Performance Management-Striving for Success

Abstract Today, organizations recognize the value of business performance management (BPM) as a way of attaining strategic alignments and as a means of effectively creating and implementing business strategy. Yet, many still struggle in implementing a BPM solution that is enterprise focused and that enables strategic alignment. This article presents a framework for BPM and discusses the major critical success factors that will influence the success of a BPM initiative.

The Current State of Business Intelligence in Academia: The Arrival of Big Data

In December 2012, the AIS Special Interest Group on Decision Support, Knowledge and Data Management Systems (SIGDSS) and the Teradata University Network (TUN) cosponsored the Business Intelligence Congress 3 and conducted surveys to assess academia’s response to the growing market need for students with Business Intelligence (BI) and Business Analytics (BA) skill sets. This panel report describes the key findings and best practices that were identified, with an emphasis on what has changed since the BI Congress efforts in 2009 and 2010. The article also serves as a “call to action” for universities regarding the need to respond to emerging market needs in BI/BA, including “Big Data.” The IS field continues to be well positioned to be the leader in creating the next generation BI/BA workforce. To do so, we believe that IS leaders need to continuously refine BI/BA curriculum to keep pace with the turbulent BI/BA marketplace.

Key organizational factors in data warehouse architecture selection

Even though data warehousing has been in existence for over a decade, companies are still uncertain about a critical decision - which data warehouse architecture to implement? Based on the existing literature, theory, and interviews with experts, a research model was created that identifies the various contextual factors that affect the selection decision. The results from the field survey and multinomial logistic regression suggest that various combinations of organizational factors influence data warehouse architecture selection. The strategic view of the data warehouse prior to implementation emerged as a key determinant. The research suggests an overall model for predicting the data warehouse architecture selection decision.

Mobile Business Intelligence

Demand for business intelligence BI applications continues to grow at a rapid pace. Business intelligence via mobile devices is the latest frontier to drive demand among organizations interested in BI applications. However, mobile BI is still in its infancy. There are many opportunities to advance the way users use and interact with BI applications using mobile BI. Nevertheless, there are many challenges and issues that still require attention to attain mobile BI success. This paper highlights the state of mobile BI solutions and strategies to consider during a mobile BI implementation. It also discusses the challenges and opportunities mobile BI presents to organizations.

Competing with BI and Analytics at Monster Worldwide

In the face of stiff competition, many organizations turn to business intelligence tools to successfully compete in the marketplace. However, successfully implementing and growing a business intelligence solution to combat market pressures is an arduous task. The stages of growth models present one approach that could guide organizations in the implementation and growth of successful business intelligence (BI) efforts. At Monster.com, upper management chose to design and implement a business intelligence framework to compete in the online job search arena. While the progressive steps that led to Monsters successful BI solution did not strictly follow established BI stage models, it helped the company effectively steer clear of competition and remain a major player in the online job search marketplace.

Business Intelligence in the Hospitality Industry

The hospitality industry is one that has been driven by customer loyalty. Many customers pick their hotel of choice and will stay with that same hotel because of the experiences, service, and even the price. Customers have recently been rewarded through hotel, credit card, and airline points that help drive and maintain this loyalty. Utilizing data to their advantage, the hotel industry has been actively exploring and implementing business intelligence. While many see IT systems as a foundation utility that can be easily imitated, business intelligence can act as a driver to maintain sustained competitive advantage over competitors in the hospitality industry. It can serve means of preserving existing customer loyalty while facing competitive pressures. This paper discusses the importance of BI to the hospitality industry, indicates how BI can serve as a barrier to competitive pressures and discusses future capabilities harnessed through BI that are not yet main stream but are expected to transform

Introduction to Business Analytics, Business Intelligence, and Big Data Minitrack

Introduction to Minitrack.

Business Intelligence Competency Center: Improving Data and Decisions

This article describes the development of a business intelligence competency center at a multi-line insurance company in the Midwest. It outlines the organization’s problems which led to the creation of the business intelligence competency center and the steps taken to ensure a successful implementation. Through a change in culture and use of an intermediary between end users and the larger information technology area, a significant success was achieved for all involved. Resulting from this experience is a set of best practices for business intelligence competency center implementation that, if followed, can lead to success for any company.

Looking to the Clouds for Business Intelligence

As cloud computing becomes more prevalent, information technology (IT) groups large and small are looking for guidance as to how they can leverage this new resource. This article specifically focuses in on the field of business intelligence (BI) and works to provide a framework for evaluating and moving out of a traditional in-house hosted BI environment to one hosted within the cloud.

Business Intelligence in the Bayou: Recovering Costs in the Wake of Hurricane Katrina

During the 2005 Atlantic hurricane season, Hurricane Katrina wreaked havoc on New Orleans. Significant damage to the Gulf region forced the Federal Emergency Management Agency (FEMA) to begin an unprecedented cleanup effort. The removal and disposal of debris was not only a challenge for landfill capacity but also for the administration of drivers, trucks, and debris type. With the debris removal workforce and certified hauling vehicles changing rapidly, record keeping and fraud detection proved difficult. This paper introduces the results of a data driven manpower audit for one parish in the greater New Orleans area that consolidated records and reconciled multiple record keeping systems. The authors’ findings bring to light the failings in record keeping during this disaster and highlight how a simple business intelligence application can improve the accuracy and quality of data and save costs.