Organisational Barriers to Including Web Data in Traditional BI Practice Henri Knoesen CITANDA, Department of Information Systems University of Cape Town Rondebosch South Africa +27216504259 KNSHEN001@myuct.ac.za Lisa F Seymour CITANDA, Department of Information Systems University of Cape Town Rondebosch South Africa +27216504259 Lisa.Seymour@uct.ac.za ABSTRACT The importance of Business Intelligence (BI) within organisations is increasing with insights being used across organisations for tasks ranging from daily management decision support to executive strategic planning. With the increasingly important role the internet plays in consumers’ lives, an abundance of valuable data is to be found online. This data can be used to enhance the ability of BI to deliver important information to all levels within the organisation. Yet including web data in traditional BI practice has not yet delivered value seamlessly. Hence the primary question asked in this paper is: What are the organisational barriers which prevent the inclusion of unstructured web data in BI practice? By means of a single case study within an Insurance company in the Western Cape, and by using a hybrid inductive and deductive research approach, this research identifies the key barriers in this organisation to the adoption of this advanced BI innovation. The major factors were found to be the lack of management support, poor understanding of the potential benefits of using web data, the reliability and privacy concerns related to this data, and no innovation champion driving the adoption. The resultant causal model of barriers can be used by organisations wanting to adopt this BI innovation to suggest possible actions which can be undertaken to eliminate some of the barriers. Categories and Subject Descriptors • Information systems~ Database management systems~ Information integration Keywords Business Intelligence; Unstructured data; Web data; Big Data 1. INTRODUCTION Tough economic times demand rapid and well-informed decisions from management. The tool which enables this ability to react to a changing environment is Business Intelligence (BI). BI is critical to compete efficiently and effectively and to make decisions which guide business strategy. In the past these insights were gleaned from data from corporate transactional systems. Yet the internet has introduced a change in the behaviour of customers which in turn provides new opportunities for organisations that are willing to mine online data. This new source of information can be used to generate insights about customers and their shopping behaviour as well as competitor information, product information and company sentiment amongst other uses. By including this unstructured internet data alongside structured traditional data in established BI architectures, BI has the potential to allow for better management decision support and corporate performance management. Yet combining structured and unstructured data has not yet delivered the promised value in a seamless way [1]. Hence the purpose of this study is to understand which factors serve as barriers to the adoption of this data source within the traditional BI practice in the organisation. 2. LITERATURE REVIEW The purpose of BI is to collect data and transform it into information which can be used to generate insights to guide strategy [8]. Traditionally BI insights were derived from analyzing transaction data gathered from corporate systems such as enterprise resource planning (ERP), customer relationship management (CRM) systems, supply-chain management (SCM), and knowledge management systems [14]. The complete BI process is comprised of data collection, data extraction and data analysis technologies with data warehousing (DW) being the foundation of BI. The BI function is defined mostly by the act of reporting on, querying and using predictive analytics on the data in the DW to gain insights and knowledge which add value to the organisation [53]. The tools used to investigate and glean insights from this data are used for corporate performance management (CPM) to analyse performance metrics, to perform database segmentation and clustering, anomaly detection, and predictive modelling in human resources, accounting, finance, and marketing applications [14]. Using external information is not a new concept to organisations. The importance and use of unstructured data has been discussed as a data source in BI for many years [10]. What is new however, is the abundance of freely available data on the internet. Internet data or web data has become a data source for organisations seeking to understand customers and their behaviour towards the company or brand. Web 2.0 has enabled the proliferation of user-generated content from social media sites, blogs, online groups and forums. Customers share their opinions about all aspects of their lives including their opinions about company products, customer service, and brand. What makes this data so important to companies is that the data is created by consumers themselves. This data is often not anonymous as it is posted on social media sites and can be used as a real-time indicator of people’s attitudes towards a firm, product or a service [28]. There is economic value contained in this data [26] as this user-generated content can be seen as a driver for future sales [22]. Data from social media sites can assist SAMPLE: Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Conference’10, Month 1–2, 2010, City, State, Country. Copyright 2010 ACM 1-58113-000-0/00/0010 …$15.00. DOI: http://dx.doi.org/10.1145/12345.67890