...Architecture and components 8 4.2 Enterprise Resource Planning (ERP) 9 4.3 Levels Of Strategy Within An Organisation And Linkage To Bi 11 4.3.1 The Corporate Level Strategy 11 4.3.2 Business-Level Strategy 12 4.3.4 Operational Strategy 13 4.3.5 Bi implementation strategies 14 4.3.5 Balance Scorecard (BSC) 15 5. The Macro Environment of Sensible Solution Ltd 17 5.1 Swot Analysis 17 5.2 Pestle Analysis 18 6. CONCLUSION/RECOMMENDATIONS 19 7. REFERENCES 21 LIST OF FIGURES Figure 1:Linking Sensible Solution Ltd strategy and goals with Business Intelligence 5 Figure 2:Linkage in Organisation & Functional Benefits of Business Intelligence 6 Figure 3:What business intelligence means in practice 7 Figure 4:The Road Map of BPM define the steps that the company needs to follow as a guide to ensure that the I.T Strategic has the same goals as business strategy 9 Figure 5:ERP integration of all departments within organisation 10 Figure 6:The Enterprise Data Model is the Foundation for Linking Strategy and Analytic Capabilities - it Links the Data to the Business Strategy 11 Figure 7:Business Strategy and BI capabilities 12 Figure 8:The layout of Corporate Strategy, Business Strategy and Operational strategy Links to BI 13 Figure 9:The BI Pathway Methods 14 Figure 10:Business intelligence development process flow from requirements through implementation. 15 Figure 11: The logic of the balanced scorecard 16 Figure 12: SWOT analysis 17 Figure...
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...IS5111:Integration of IS & Business Business Intelligence and Analytics Abhishek Kumar Singh Anbarasan Thangapalam R Deepak Chattani Naadiya Danapal Ram Vibhakar S [A0120022] [A0119959] [A0119975] [A0119961] [A0120054] A Case study on Business Intelligent and Analytics Systems in NTUC FairPrice Table of Contents Executive Summary ............................................................................................................................. 3 Acknowledgments ............................................................................................................................... 4 1. Introduction ...................................................................................................................................... 5 2. Business Intelligence in Retail Industry: ................................................................................. 6 3. Combining BI in CRM ...................................................................................................................... 7 3.1 Analytical CRM ..........................
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...Running Head: BUSINESS INTELLIGENCE A REVIEW OF LITERATURE Business Intelligence: A Review of Literature Richard Clark Liberty University Abstract An explorative and descriptive review of literature on Business Intelligence (BI). It presents various definitions of the term “Business Intelligence” and determines that regardless the definition is a “means” to “end”, which sound business or organizational decision making, specifically in strategic planning and management. It also presents several important differentiation of Business Intelligence from data-centric technologies, and enterprise applications. It describes business intelligence architecture and its components. It identifies capabilities and benefits to be derive from it, barriers to its successful implementation, and critical success factors. It identifies BI software vendors, trends and forecast, and ethical considerations. It concludes with a conceptual framework that shows business intelligence as a process that produces intelligence necessary for strategic planning and management, that in turn results to a strategy that creates competitive advantages. This paper is an explorative and descriptive review of literature on Business Intelligence (BI). An exploratory research as the name suggests explores a problem or a situation with the purpose of defining an ambiguous problem. It is undertaken from the perspective of a student in management and of an IT “dummy”. Consequently, the review strategy is to look...
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...Chapter 12 Business Intelligence and Decision Support Systems Goals of the Chapter The primary objective of this chapter is to recognize the importance of data, the management issues that relate to it, and its life cycle. Other objectives include relating data management to multimedia and document management, explaining the concept of data warehousing, data mining, analytical processing, and knowledge discovery management. An Overview Section 12.1 – The Need for Business Intelligence – The section serves as an overview of Business Intelligence and its use in business. It discusses the problems associated with disparate data stores where data are not integrated into a single reporting system. The section discusses the technologies involved in Business Intelligence and the vendors involved. It also talks about predictive analytics, alerts and decision support. Section 12.2 – BI Architecture, Reporting and Performance Management – This section discusses the modes of data extraction and integration into a standardized, usable and trustworthy one. It also discusses the different types of reporting systems available to organizations, data mining, query and analysis. The section provides an insight into Business Performance Management (BPM) as a way for business managers to know if their organizations are achieving their strategic goals Section 12.3 – Data, Text and Web Mining and BI Search – This section discusses data mining technology, tools, and techniques. Information types...
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...Jacob Moore GBA 673 Business Intelligence Jacob Moore GBA 673 Dr. Lara Preiser-Houy, CDP August 20th, 2013 1|Page Jacob Moore GBA 673 Table of Contents Abstract ....................................................................................................................................................... 3 Introduction ............................................................................................................................................... 3 Background ................................................................................................................................................ 4 Conceptualization ..................................................................................................................................... 4 BI 1.0 ......................................................................................................................................................... 4 BI 2.0 ......................................................................................................................................................... 5 BI 3.0 ......................................................................................................................................................... 5 Opportunities ............................................................................................................................................ 6 Challenges ........................................
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...clients in order to deliver value-added products. To do this, organizations attempt to engage the business with a mindset of continuous improvement through business process management. Business process management has four key components: 1. Process engine – a platform for executing process-based applications 2. Business analytics – identifying business trends through reports and dashboards 3. Content management – allows a system to store secure documents, files, etc. 4. Collaboration tools – removes communication barriers via forums, message boards, etc. Senior executives now want business run on data-driven decisions (Hopkins et al 2011). For the purpose of this paper we will focus on business analytics and how technology is used to create business intelligence for the company. Enterprises are increasingly adopting BI technology to boost the analytical and decision-making processes that underpin their overall success (Decker 2010). Business intelligence is not a new concept; it was derived from computer-aided models during the 1970’s and 1980’s. Howard Dresner (formerly of the Gartner Group) is considered the father of business intelligence and saw the need for companies to create performance-directed cultures in which the business and IT worked together. Adoption of BI technologies is likely to double in the next five years (Brannon 2010). Business intelligence (BI) is a technology-based decision support system used to serve different organizational levels in...
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...HR Analytics: Driving Return on Human Capital Investment An Oracle White Paper September 2011 HR Analytics: Driving Return on Human Capital Investment HR Analytics: Driving Return on Human Capital Investment The Business Need for Improved HR Analytics ................................. 3 Leading Practices for Improved Organizational Performance ............ 4 HR Analytics Contributes by Driving Insights to Action ...................... 5 Addressing Information Needs through Analytic Workflows ........... 5 About Oracle Business Intelligence Applications ............................... 7 The Foundation: OBIEE 11g .......................................................... 8 HR Analytics Subject Areas ........................................................... 9 A Case Story ................................................................................... 15 Benefits and ROI ............................................................................. 17 The Value of a Pre-Built Solution ................................................. 17 Business Value Adds Up ............................................................. 17 Maximizing Success – Next Steps ................................................... 19 Conclusion ...................................................................................... 20 The Business Need for Improved HR Analytics As worldwide economic and political conditions continue to concern business leaders, their attention...
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...cu MOVEIN BUSINESS INTELLIGENCE AND ANALYTICS REPORT me nt ap A Business Plan on the Role of Business Intelligence and Analytics for MoveIn Pty Ltd Th ink sw Do TABLE OF CONTENTS Executive Summary ........................................................................................................................ 2 1 -‐ Introduction .............................................................................................................................. 3 2 -‐ Role of Business Intelligence ..................................................................................................... 3 2.1 -‐ Business Intelligence -‐ Overview ............................................................................................... 3 2.2 -‐ Business Intelligence Tools ........................................................................................................ 4 2.2.1 -‐ On-‐line Analytical Processing .............................................................................................. 4 2.2.2 -‐ Data Mining ........................................................................................................................ 5 ...
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...and if managed efficiently, it drives positive business and enables sustainable advantage, Matthew A and Stanley E (2013). If we observe carefully, huge amount of data is getting generated at each and every stages of the supply chain. In today’s digital world we are generating around 200 Exabyte of data each year, Silva R, Bogdan F and Marcin R (2013). Organizations are increasingly questioning their own ability to realize full potential from the huge amount of data they have within their supply chain, Steve...
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...Making Business Intelligence Easy White Paper Mobile Business Intelligence and Analytics Mobile Business Intelligence & Analytics Contents Overview ...................................................................................................................................................... 3 What is Mobile Business Intelligence?......................................................................................................... 4 Who is it for? ................................................................................................................................................ 5 What are the external factors driving Mobile Business Intelligence? ........................................................... 6 What are the internal drivers for Mobile Business Intelligence? .................................................................. 7 What benefits are sought? ........................................................................................................................... 8 What organizational factors are required? ................................................................................................... 9 What technology has to underpin a Mobile Business Intelligence initiative? ............................................. 10 Security is paramount ................................................................................................................................ 11 Yellowfin’s Mobile Business Intelligence platform...
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...BI Norwegian School of Management – Thesis Master of Science in Innovation and Entrepreneurship GRA 19002 Convergence, Complementarity or Disruption: Enterprise Search and Business Intelligence By Vedrana Jez Hand-in date: 01.09.2009 Supervisor: Dr. Espen Andersen This thesis is a part of the MSc programme at BI Norwegian School of Management. The school takes no responsibility for the methods used, results found and conclusions drawn. Acknowledgments I would like to thank my supervisor, Dr. Espen Andersen, for his support and guidance throughout the project. I am also grateful to all participants in this research for their contribution and time. Finally, I thank my family for their understanding, encouragement and patience. Thesis 01.09.2009 Content Content ..................................................................................................................... i Abstract .................................................................................................................. iv Introduction ............................................................................................................ 1 Research Methodology ........................................................................................... 2 Research Question .........................................................................................................2 Method Used ..................................................................
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...BUSINESS INTELLIGENCE SOLUTIONS Executive Summary Business Intelligence, abbreviated as BI, is a general term, which refers to various software applications used in the analysis of an organization’s raw data. Business Intelligence as a discipline comprises of various related activities, which include data mining, internet-based analytical processing, reporting, and querying. Business organizations use BI in order to improve in decision-making, reduce costs of operation, and identify new business opportunities. Companies use BI in order to identify inefficient business processes, which need re-engineering. With the current BI tools, business organizations can take the role of analyzing their data by themselves instead of waiting for IT systems to run complex reports. BI enhances the democratization of information access, which is helpful for users when it comes to information back-up. Even though BI holds the future of business solutions, its implementation in a business organization can pose technical and cultural challenges. The organization’s administration must ensure that BI applications used to feed data are clean and consistent in order to be trusted. BI is made up of a set of theories, procedures, technologies, and architectures, which are used to transform raw data and information into meaningful and useful data and information for use in business operations. BI is effective in handling huge amounts of unstructured data and information. It helps in identifying...
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...IV APPENDIX - V Introduction Predictive analytics has its origin from a famous saying: Past performance is the basic indicator of future results. It looks at historical cases and builds models which can then be applied to benefit present scenarios or predict future scenarios. Predictive Analytics is the best way for a business to predict customer responses in the future. It provides solutions for businesses facing main problems like ‘What segment of potential consumers will respond best to our message’ and ‘how can I stop my customers from leaving, and why am I losing them?’(Curtis, 2010). Predictive analytics is not just for providing a solution for a business problem but involves techniques mainly to improve the focus of company towards customers and customers towards company. The magnificence of predictive analytics is that a business characteristically perceives a win-win situation. In other words, a business not only benefits from higher returns but also gets to save on cost (Colin, 2009). Predictive analytics is becoming a competitive necessity and an important aspect of many types of business, particularly in this type of economy where an organization is trying to increase its efficiency and at the same time maintain and grow the business. The choice of this topic comes from the fact that prediction is always interesting and challenging. One needs to analyse the history in depth to predict accurately. From the business point of view, predicting and taking decisions...
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...Chapter # 1. Introduction to CRM 1.1 Evolution of CRM Customer Relationship Management (CRM) is one of those magnificent concepts that swept the business world in the 1990’s with the promise of forever changing the way businesses small and large interacted with their customer bases. In the short term, however, it proved to be an unwieldy process that was better in theory than in practice for a variety of reasons. First among these was that it was simply so difficult and expensive to track and keep the high volume of records needed accurately and constantly update them. In the last several years, however, newer software systems and advanced tracking features have vastly improved CRM capabilities and the real promise of CRM is becoming a reality. As the price of newer, more customizable Internet solutions have hit the marketplace; competition has driven the prices down so that even relatively small businesses are reaping the benefits of some custom CRM programs. 1.2 In the beginning… The 1980’s saw the emergence of database marketing, which was simply a catch phrase to define the practice of setting up customer service groups to speak individually to all of a company’s customers. In the case of larger, key clients it was a valuable tool for keeping the lines of communication open and tailoring service to the clients needs. In the case of smaller clients, however, it tended to provide repetitive, survey-like information that cluttered databases and didn’t provide much...
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...update the researchers in specific fields. Facilitating them with latest Research Paper, Bibliography of research papers and books. The goal of AJMR is to bring fresh perspective to research in management and take research to masses through its open access, internet based technology. AJMR is a quarterly journal, and every quarter a new topic/theme is chosen and paper pertaining to it are called for and subsequently reviewed for publication. We take this opportunity to invite research papers, case studies, monographs on the below stated theme. The theme for the August issue is “Business Intelligence, Analysis and Strategy” Background Theme The key to thriving in a competitive marketplace is staying ahead of the competition. Making sound business decisions based on accurate and current information takes more than intuition. Business success depends upon opportunities availed, strategy designed and action taken. But in most of the situation like in retail where Fifty-Three percent (53%) of large retailers indicate that customer analysis is difficult due to enormity of data from different channels. Retailers have more data than they are capable of processing. More often than not retailers blame disparate sources and enormity of customer data as the primary reason for lack of adequate consumer insights that inhibits new customer acquisition, customer retention and reactivation....
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