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Business Analytics for Managers: Taking Business Intelligence beyond Reporting

Book Description

"While business analytics sounds like a complex subject, this book provides a clear and non-intimidating overview of the topic. Following its advice will ensure that your organization knows the analytics it needs to succeed, and uses them in the service of key strategies and business processes. You too can go beyond reporting!"—Thomas H. Davenport, President's Distinguished Professor of IT and Management, Babson College; coauthor, Analytics at Work: Smarter Decisions, Better Results

Deliver the right decision support to the right people at the right time

Filled with examples and forward-thinking guidance from renowned BA leaders Gert Laursen and Jesper Thorlund, Business Analytics for Managers offers powerful techniques for making increasingly advanced use of information in order to survive any market conditions.

Take a look inside and find:

  • Proven guidance on developing an information strategy

  • Tips for supporting your company's ability to innovate in the future by using analytics

  • Practical insights for planning and implementing BA

  • How to use information as a strategic asset

  • Why BA is the next stepping-stone for companies in the information age today

  • Discussion on BA's ever-increasing role

Improve your business's decision making. Align your business processes with your business's objectives. Drive your company into a prosperous future. Taking BA from buzzword to enormous value-maker, Business Analytics for Managers helps you do it all with workable solutions that will add tremendous value to your business.

Table of Contents

  1. Copyright
  2. Foreword
  3. Introduction
    1. WHAT DOES BA MEAN? INFORMATION SYSTEMS—NOT TECHNICAL SOLUTIONS
    2. PURPOSE AND AUDIENCE
    3. ORGANIZATION OF CHAPTERS
    4. WHY THE TERM BUSINESS ANALYTICS?
  4. 1. The Business Analytics Model
    1. 1.1. OVERVIEW OF THE BUSINESS ANALYTICS MODEL
      1. 1.1.1. Strategy Creation
      2. 1.1.2. Business Processes and Information Use
      3. 1.1.3. Types of Reporting and Analytical Processes
      4. 1.1.4. Data Warehouse
      5. 1.1.5. Data Sources: IT Operations and Development
    2. 1.2. DEPLOYMENT OF THE BA MODEL
      1. 1.2.1. Case Study: How to Make an Information Strategy for a Radio Station
      2. 1.2.2. Overall Strategic Targets of the Business
      3. 1.2.3. Functional Strategy and Business Case
      4. 1.2.4. Business Processes and Actions
      5. 1.2.5. Analytical Processes and Front-ends
      6. 1.2.6. Data Warehouse
      7. 1.2.7. Data Sources: IT Operations and Development
      8. 1.2.8. Evaluation of the BA Process
    3. 1.3. CONCLUSIONS
  5. 2. Business Analytics at the Strategic Level
    1. 2.1. LINK BETWEEN STRATEGY AND THE DEPLOYMENT OF BA
    2. 2.2. STRATEGY AND BA: FOUR SCENARIOS
      1. 2.2.1. Scenario 1: No Formal Link between Strategy and BA
      2. 2.2.2. Scenario 2: BA Supports Strategy at a Functional Level
      3. 2.2.3. Five Requirements for Targets
      4. 2.2.4. Scenario 3: Dialogue between the Strategy and the BA Functions
      5. 2.2.5. Scenario 4: Information as a Strategic Resource
    3. 2.3. WHICH INFORMATION DO WE PRIORITIZE?
      1. 2.3.1. The Product and Innovation Perspective
      2. 2.3.2. Customer Relations Perspective
      3. 2.3.3. The Operational Excellence Perspective
    4. 2.4. SUMMARY
  6. 3. Development and Deployment of Information at the Functional Level
    1. 3.1. CASE STUDY: A TRIP TO THE SUMMERHOUSE
      1. 3.1.1. Specification of Requirements
      2. 3.1.2. Your Technical Support
      3. 3.1.3. And Now Off We Go to the Summerhouse
      4. 3.1.4. Your Lead and Lag information
      5. 3.1.5. More about Lead and Lag Information
    2. 3.2. ESTABLISHING BUSINESS PROCESSES WITH THE ROCKART MODEL
    3. 3.3. EXAMPLE: ESTABLISHING NEW BUSINESS PROCESSES WITH THE ROCKART MODEL
      1. 3.3.1. Level 1: Identifying the Objectives
      2. 3.3.2. Level 2: Identifying an Operational Strategy
      3. 3.3.3. Level 3: Identifying the Critical Success Factors
      4. 3.3.4. Level 4: Identifying Lead and Lag Information
    4. 3.4. OPTIMIZING EXISTING BUSINESS PROCESSES
    5. 3.5. EXAMPLE: DEPLOYING PERFORMANCE MANAGEMENT TO OPTIMIZE EXISTING PROCESSES
      1. 3.5.1. Concept of Performance Management
    6. 3.6. WHICH PROCESS SHOULD YOU START WITH?
      1. 3.6.1. CRM Activities
      2. 3.6.2. Campaign Management
      3. 3.6.3. Product Development
      4. 3.6.4. Web Log Analyses
      5. 3.6.5. Pricing
      6. 3.6.6. Human Resource Development
    7. 3.7. CPM
      1. 3.7.1. Finance
      2. 3.7.2. Inventory Management
      3. 3.7.3. Supply Chain Management
      4. 3.7.4. Lean
    8. 3.8. A CATALOGUE OF IDEAS WITH KPIs FOR THE COMPANY'S DIFFERENT FUNCTIONS
    9. 3.9. SUMMARY
  7. 4. Business Analytics at the Analytical Level
    1. 4.1. DATA, INFORMATION, AND KNOWLEDGE
    2. 4.2. ANALYST'S ROLE IN THE BA MODEL
    3. 4.3. THREE REQUIREMENTS THE ANALYST MUST MEET
      1. 4.3.1. Business Competencies
      2. 4.3.2. Tool Kit Must Be in Order (Method Competencies)
      3. 4.3.3. Technical Understanding (Data Competencies)
    4. 4.4. REQUIRED COMPETENCIES FOR THE ANALYST
      1. 4.4.1. Analytical Methods (Information Domains)
      2. 4.4.2. How to Select the Analytical Method
      3. 4.4.3. The Three Imperatives
      4. 4.4.4. Descriptive Statistical Methods, Lists, and Reports
      5. 4.4.5. Ad Hoc Reports
      6. 4.4.6. Manually Updated Reports
      7. 4.4.7. Automated Reports: On Demand
      8. 4.4.8. Automated Reports: Event Driven
      9. 4.4.9. Reports in General
    5. 4.5. HYPOTHESIS-DRIVEN METHODS
      1. 4.5.1. Tests with Several Input Variables
    6. 4.6. DATA MINING WITH TARGET VARIABLES
      1. 4.6.1. Data Mining Algorithms
    7. 4.7. EXPLORATIVE METHODS
      1. 4.7.1. Data Reduction
      2. 4.7.2. Cluster Analysis
      3. 4.7.3. Cross-Sell Models
      4. 4.7.4. Up-Sell Models
    8. 4.8. BUSINESS REQUIREMENTS
      1. 4.8.1. Definition of the Overall Problem
      2. 4.8.2. Definition of Delivery
      3. 4.8.3. Definition of Content
    9. 4.9. SUMMARY
  8. 5. Business Analytics at the Data Warehouse Level
    1. 5.1. WHY A DATA WAREHOUSE?
    2. 5.2. ARCHITECTURE AND PROCESSES IN A DATA WAREHOUSE
      1. 5.2.1. Selection of Certain Columns to Be Loaded
      2. 5.2.2. Staging Area and Operational Data Stores
      3. 5.2.3. Causes and Effects of Poor Data Quality
      4. 5.2.4. The Data Warehouse: Functions, Components, and Examples
      5. 5.2.5. Business Analytics Portal: Functions and Examples
    3. 5.3. TIPS AND TECHNIQUES IN DATA WAREHOUSING
      1. 5.3.1. Master Data Management
      2. 5.3.2. Service-Oriented Architecture
      3. 5.3.3. How Should You Access Your Data?
      4. 5.3.4. Access to BA Portals
      5. 5.3.5. Access to Data Mart Areas
      6. 5.3.6. Access to Data Warehouse Areas
      7. 5.3.7. Access to Source Systems
    4. 5.4. SUMMARY
  9. 6. The Company's Collection of Source Data
    1. 6.1. WHAT ARE SOURCE SYSTEMS, AND WHAT CAN THEY BE USED FOR?
    2. 6.2. WHICH INFORMATION IS BEST TO USE FOR WHICH TASK?
    3. 6.3. WHEN THERE IS MORE THAN ONE WAY TO GET THE JOB DONE
    4. 6.4. WHEN THE QUALITY OF SOURCE DATA FAILS
    5. 6.5. SUMMARY
  10. 7. Structuring of a Business Intelligence Competency Center
    1. 7.1. WHAT IS A BUSINESS INTELLIGENCE COMPETENCY CENTER?
    2. 7.2. WHY SET UP A BUSINESS INTELLIGENCE COMPETENCY CENTER?
    3. 7.3. TASKS AND COMPETENCIES
      1. 7.3.1. Establishing an Information Wheel
      2. 7.3.2. Creating Synergies between Information Wheels
      3. 7.3.3. Educating Users
      4. 7.3.4. Prioritizing New BA Initiatives
      5. 7.3.5. Competencies
    4. 7.4. CENTRALIZED OR DECENTRALIZED ORGANIZATION
      1. 7.4.1. Strategy or Performance
      2. 7.4.2. When the Analysts Reports to the IT Department
    5. 7.5. WHEN SHOULD A BICC BE ESTABLISHED?
    6. 7.6. SUMMARY
  11. 8. Assessment and Prioritization of BA Projects
    1. 8.1. IS IT A STRATEGIC PROJECT OR NOT?
    2. 8.2. UNCOVERING THE VALUE CREATION OF THE PROJECT
    3. 8.3. WHEN PROJECTS RUN OVER SEVERAL YEARS
    4. 8.4. WHEN THE UNCERTAINTY IS TOO BIG
      1. 8.4.1. The Descriptive Part of the Cost/Benefit Analysis for the Business Case
      2. 8.4.2. The Cost/Benefit Analysis Used for the Business Case
    5. 8.5. PROJECTS AS PART OF THE BIGGER PICTURE
    6. 8.6. SUMMARY
  12. 9. Business Analytics in the Future