How do top- and bottom-performing companies differ in using business analytics?

Purpose Business analytics (BA) has attracted growing attention mainly due to the phenomena of big data. While studies suggest that BA positively affects organizational performance, there is a lack of academic research. The purpose of this paper, therefore, is to examine the extent to which top- and bottom-performing companies differ regarding their use and organizational facilitation of BA. Design/methodology/approach Hypotheses are developed drawing on the information processing view and contingency theory, and tested using multivariate analysis of variance to analyze data collected from 117 UK manufacture companies. Findings Top- and bottom-performing companies differ significantly in their use of BA, data-driven environment, and level of fit between BA and data-drain environment. Practical implications Extensive use of BA and data-driven decisions will lead to superior firm performance. Companies wishing to use BA to improve decision making and performance need to develop relevant analytical strategy to guide BA activities and design its structure and business processes to embed BA activities. Originality/value This study provides useful management insights into the effective use of BA for improving organizational performance

How Business Analytics Systems Provide Benefits and Contribute to Firm Performance?

Organisations invest in Business analytics (BA) systems to improve firm performance and gain competitive advantage. BA systems use advanced analytical tools and techniques to analyse organisational data and generate insights. Decision makers at different levels of the organisations leverage the insights and take competitive actions. In this paper, we utilise Resource-based View (RBV) and business value of IT literature to develop a research model to explain the firm performance impacts of BA systems in customer relations. The research model proposes that BA capability creates informational benefits in customer relations using two pathways: (1) Direct creation of informational benefits, and (2) Indirect creation of informational benefits through developing higher-order Analytical CRM capability. Informational benefits once created, contribute to superior firm performance. The research model is evaluated using survey data in Large US-based organisations

Unified Approach in the DSS Development Process

The structure of today's decision support environment become very complex due to new generation of Business Intelligence applications and technologies like Data Warehouse, OLAP (On Line Analytical Processing) and Data Mining. In this respect DSS development process are not simple and needs an adequate methodology or framework able to manage different tools and platforms to achieve manager's requirements. The DSS development process must be view like a unified and iterative set of activities and operations. The new techniques based on Unified Process (UP) methodology and UML (Unified Modeling Language) it seems to be appropriate for DSS development using prototyping and RAD (Rapid Application Development) techniques. In this paper we present a conceptual framework for development and integrate Decision Support Systems using Unified Process Methodology and UML.Decision Support Systems, Unified Process, UML, Prototyping, DSS Tools

Essential Micro-foundations for Contemporary Business Operations: Top Management Tangible Competencies, Relationship-based Business Networks and Environmental Sustainability

Although various studies have emphasized linkages between firm competencies, networks and sustainability at organizational level, the links between top management tangible competencies (e.g., contemporary relevant quantitative-focused education such as big data analytics and data-driven applications linked with the internet of things, relevant experience and analytical business applications), relationship-based business networks (RBNs) and environmental sustainability have not been well established at micro-level, and there is a literature gap in terms of investigating these relationships. This study examines these links based on the unique data collected from 175 top management representatives (chief executive officers and managing directors) working in food import and export firms headquartered in the UK and New Zealand. Our results from structural equation modelling indicate that top management tangible competencies (TMTCs) are the key determinants for building RBNs, mediating the correlation between TMTCs and environmental sustainability. Directly, the competencies also play a vital role towards environmental practices. The findings further depict that relationship-oriented firms perform better compared to those which focus less on such networks. Consequently, our findings provide a deeper understanding of the micro-foundations of environmental sustainability based on TMTCs rooted in the resource-based view and RBNs entrenched in the social network theory. We discuss the theoretical and practical implications of our findings, and we provide suggestions for future research

Two Essays on Analytical Capabilities: Antecedents and Consequences

Although organizations are rapidly embracing business analytics (BA) to enhance organizational performance, only a small proportion have managed to build analytical capabilities. While BA continues to draw attention from academics and practitioners, theoretical understanding of antecedents and consequences of analytical capabilities remain limited and lack a systematic view. In order to address the research gap, the two essays investigate: (a) the impact of organization’s core information processing mechanisms and its impact on analytical capabilities, (b) the sequential approach to integration of IT-enabled business processes and its impact on analytical capabilities, and (c) network position and its impact on analytical capabilities. Drawing upon the Information Processing Theory (IPT), the first essay investigates the relationship between organization’s core information processing mechanisms–i.e., electronic health record (EHRs), clinical information standards (CIS), and collaborative information exchange (CIE)–and its impact on analytical capabilities. We use data from two sources (HIMSS Analytics 2013 and AHA IT Survey 2013) to test the theorized relationships in the healthcare context empirically. Using the competitive progression theory, the second essay investigates whether organizations sequential approach to the integration of IT-enabled business processes is associated with increased analytical capabilities. We use data from three sources (HIMSS Analytics 2013, AHA IT Survey 2013, and CMS 2014) to test if sequential integration of EHRs –i.e., reflecting the unique organizational path of integration–has a significant impact on hospital’s analytical capability. Together the two essays advance our understanding of the factors that underlie enabling of firm’s analytical capabilities. We discuss in detail the theoretical and practical implications of the findings and the opportunities for future research

Integration of business intelligence based on three-level ontology services

Usually, integration of business intelligence (BI) from realistic telecom enterprise is by packing data warehouse (DW), OLAP, data mining and reporting from different vendors together. As a result, BI system users are transferred to a reporting system with reports, data models, dimensions and measures predefined by system designers. As a result of survey, 85% of DW projects failed to meet their intended objectives. In this paper, we investigate how to integrate BI packages into an adaptive and flexible knowledge portal by constructing an internal link and communication channel from top-level business concepts to underlying enterprise information systems (EIS). An approach of three-level ontology services is developed, which implements unified naming, directory and transport of ontology services, and ontology mapping and query parsing among conceptual view, analytical view and physical view from user interfaces through DW to EIS. Experiments on top of real telecom EIS shows that our solution for integrating BI presents much stronger power to support operational decision making more user-friendly and adoptively compared with those simply combining BI products presently available together. © 2004 IEEE

Optimizing Data Warehousing Startegies

Database technologies have evolved over the last two decades into different constructs to support the ever-growing information needs for organizations spanning the spectrum of operational and analytical processing. The paper examines the characteristics of transactional databases, operational data stores, data warehouses and virtual data warehouses. A framework is developed for an optimal data warehousing strategy based on organizational needs classified by the types of business processes defined by the requirements of supporting functional areas and the levels of decision structures. Enterprise architecture is described to provide an integrated and complimentary view of various data warehousing constructs

Discontinuities in the Distribution of Great Wealth: Sectoral Forces Old and New

National surveys of household economics and well-being in the United States usually focus on income. In those income surveys with supplemental wealth modules, the very rich are underrepresented if not unrepresented. Typically, wealth data are truncated such that they do not afford a view of the extreme top of the distribution. Therefore, we attempt to supplement our knowledge about elite wealth holdings by compiling data on the richest individuals and families in the United States. To do so, we draw from the rosters of the "Forbes Four Hundred," which have been published annually by Forbes magazine since 1982. Along with information from other business press reports and standard biographical sources, rosters of the very rich enable research on inequality at the extreme of the wealth distribution during a period of dramatic change in the composition and concentration of wealth. In this study, we focus analytically on economic sectors because we are interested less in the maldistribution of wealth by demographic groups than in inequality between different economic sectors. We will first specify our analytical approach, then examine issues in the use of business press rosters of the very rich as a data source, and follow with a discussion of the dimensions and categories of our sector typology. After presenting our results, we will address how sectoral forces old and new affect economic opportunity and great wealth outcomes.

Recent Developments in Data Warehousing

Data warehousing is a strategic business and IT initiative in many organizations today. Data warehouses can be developed in two alternative ways -- the data mart and the enterprise-wide data warehouse strategies -- and each has advantages and disadvantages. To create a data warehouse, data must be extracted from source systems, transformed, and loaded to an appropriate data store. Depending on the business requirements, either relational or multidimensional database technology can be used for the data stores. To provide a multidimensional view of the data using a relational database, a star schema data model is used. Online analytical processing can be performed on both kinds of database technology. Metadata about the data in the warehouse is important for IT and end users. A variety of data access tools and applications can be used with a data warehouse - SQL queries, management reporting systems, managed query environments, DSS/EIS, enterprise intelligence portals, data mining, and customer relationship management. A data warehouse can be used to support a variety of users - executive, managers, analysts, operational personnel, customers, and suppliers. Data warehousing concepts are brought to life through a case study of Harrah\u27s Entertainment, a firm that became a leader in the gaming industry with its CRM business strategy supported by data warehousing