Business analytics

About: Business analytics is a research topic. Over the lifetime, 3593 publications have been published within this topic receiving 84601 citations. The topic is also known as: Business Analytics & business analytics.

The impact of big data and business analytics on supply chain management

Abstract: Background: Change is inevitable and as supply chain managers prepare for the future they face many challenges. Two major trends over the last few years are the growing importance of ‘big data’ and analysing these data though ‘analytics’. The data contain much value and companies need to capitalise on the variety of data sources by in-depth and proper analysis through the use of ‘big data’ analytics. Objective: This article endeavours to highlight the evolving nature of the supply chain management (SCM) environment, to identify how the two major trends (‘big data’ and analytics) will impact SCM in future, to show the benefits that can be derived if these trends are embraced and to make recommendations to supply chain managers. Method: The importance of extracting value from the huge amounts of data available in the SCM area is stated. ‘Big data’ and analytics are defined and the impact of these in various SCM applications clearly illustrated. Results: It is shown, through examples, how the SCM area can be impacted by these new trends and developments. In these examples ‘big data’ analytics have already been embraced, used and implemented successfully. Big data is a reality and using analytics to extract value from the data has the potential to make a huge impact. Conclusion: It is strongly recommended that supply chain managers take note of these two trends, since better use of ‘big data’ analytics can ensure that they keep abreast with developments and changes which can assist in enhancing business competitiveness.

Business Performance Analytics: exploring the potential for Performance Management Systems

Abstract: Business Performance Analytics (BPA) entails the systematic use of data and analytical methods (mathematical, econometric and statistical) for performance measurement and management. Although poten...

Eight Issues on Audit Data Analytics We Would Like Researched

Abstract: Data analytics has been emphasized as an effective tool in audit engagements. However, both our understanding and the use of data analytics in audit engagements are limited. The objective of this paper is to draw academic researchers' attentions to the issues of data analytics identified by an experienced practitioner in the field. These issues range from standards and the framework of data analytics to the use of data analytics in different phases of audit engagements and the corresponding consequences. The use of external data, sample versus population, and reliance on the work of internal auditors are also discussed. By addressing these issues, academic researchers can not only provide solutions to the field but also contribute to the knowledge body of academic literature.

Detecting customers knowledge from social media big data: toward an integrated methodological framework based on netnography and business analytics

Abstract: This paper aims to demonstrate how the integration of netnography and business analytics can support companies in the process of value creation from social big data by leveraging on customer relationship management and customer knowledge management (CKM).,This paper adopts the methodology of a single case study by using desk analysis, netnography and business analytics. The context of analysis has been identified into the case of Aurora Company, a well-known producer of fountain pens.,The case demonstrates how the integration of big data analytics and netnography is relevant for the development of a customer relationship management strategy. The results obtained have been categorized according to the three main categories of customer knowledge, such as knowledge for, from and about customer.,This paper presents implications for the advancement of the theory on CKM by demonstrating, as the acquisition, storage and management of data generated by customers on social media require the adoption of a cross-disciplinary approach resulting from the integration of qualitative and quantitative approaches. The framework is structured as methodological tool to detect knowledge in virtual community.,Practical implications arise for managers and entrepreneurs in terms of value creation from knowledge assets generated on social big data through the management of the customers’ relationship and data-driven innovation patterns.,This paper offers an original contribution of integration of well-established research streams. The focus on the knowledge under the perspectives of information assets for, from and about customers in the debate on value creation and management of big data is an element of value offered by this study in addition to the comprehension of strategies of social customer relationship management as actual initiative embraced by a company in the leveraging of innovation and tradition.