Business Intelligence Strategy and Big Data Analytics

A General Management Perspective
 
 
Morgan Kaufmann (Verlag)
  • 1. Auflage
  • |
  • erschienen am 8. April 2016
  • |
  • 240 Seiten
 
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
978-0-12-809489-1 (ISBN)
 

Business Intelligence Strategy in the Big Data Analytics: A General Management Perspective explains how to deliver competitive advantages and substantial economic benefits by overcoming commonly-encountered barriers to success. It includes lessons learned from leading companies that provide practical ideas for how to use the many different forms of BI to meet key business objectives. Further, it clarifies how BI initiatives are really business initiatives that require business units to change how they use information and analysis to drive and improve business results, particularly profits.

Business intelligence (BI) and business analytics are like a Swiss army knife-they can be used in many different ways to achieve many different business purposes. In working with leading companies in a wide range of industries to help them formulate and execute BI strategies and program plans, the author has seen firsthand that these successful companies struggle in two key areas: BI Strategy, which is understanding how they can leverage BI in core business functions such as marketing, sales, customer service, operations, distribution, supplier management, cost improvement, and financial management; and BI Program Execution, which is effectively aligning and executing the diverse workstreams that are critical for achieving a return on investment (ROI), including change management, business process and BI integration, and BI and data warehousing development.


  • Provides ideas for improving the business performance of one's company or business functions
  • Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies
  • Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans


Steve Williams is the founder and CEO of DecisionPath Consulting. He specializes in helping clients formulate business-driven, technically-savvy strategies for leveraging business intelligence, analytics, and big data to improve profits. Steve blends general management experience and a general management MBA with nearly 30 years' experience in the information systems field - the last fifteen of which have been spent in the business intelligence (BI) and analytics specialty.
As a BI strategy consultant, Steve has had the privilege of working with successful companies in retail, distribution, manufacturing, consumer packaged goods, government, and electric power. His clients have included:

•ArcBest
•Heinens Fine Foods
•Louisville Gas and Electric
•Navy Federal Credit Union
•Northwestern Mutual Life
•Partners Federal Credit Union
•Pinnacle Foods Group
•Principal Financial Group
•Toronto Hydro Electric System
•United Natural Foods
•U.S. Social Security Administration
•Watsco


While the industries and companies are different, there are many common challenges when it comes to leveraging BI, analytics, and big data to enhance profitability. Steve understands these challenges, and he provides proven methods for meeting them.
In addition to his consulting work, Steve is also an active contributor to the field of business intelligence, analytics, and big data. He and Nancy Williams wrote The Profit Impact of Business Intelligence in 2006, and Steve has continued to write for magazines such as Strategic Finance, Business Intelligence Journal, and MWorld (The Journal of the American Management Association). In addition to widely-sharing his thinking about BI, analytics, and big data, Steve has also served as a judge since 2001 for the annual TDWI Best Practices in Business Intelligence and Data Warehousing Competition.
Prior to founding DecisionPath, Steve worked for twenty years in several specialized consulting companies where he developed expertise in program management, systems integration, software engineering, and management accounting. He holds an MBA in General Management from the Darden School at the University of Virginia and a B.S. in Business Management from the University of Maryland.
  • Englisch
  • San Francisco
  • |
  • USA
Elsevier Science
  • 5,84 MB
978-0-12-809489-1 (9780128094891)
0128094893 (0128094893)
weitere Ausgaben werden ermittelt
  • Front Cover
  • Business Intelligence Strategy and Big Data Analytics
  • Copyright Page
  • Contents
  • About the Author
  • Foreword
  • Acknowledgments
  • Introduction
  • The Challenge of Formulating Business Intelligence Strategy
  • Overview of the Book
  • Organization of the Book
  • Closing the Loop
  • 1 The Personal Face of Business Intelligence
  • 1.1 BI Case Study Setting
  • 1.1.1 Industry Setting
  • 1.1.2 Company Situation
  • 1.2 BBF BI Opportunities
  • 1.2.1 The CEO's View of Business Challenges and BIOs
  • 1.2.2 The Chief Operating Officer's View of Business Challenges and BIOs
  • 1.2.3 The Chief Marketing Officer's View of Business Challenges and BIOs
  • 1.2.4 The Chief Sales Officer's View of Business Challenges and BIOs
  • 1.2.5 The Chief Financial Officer's View of Business Challenges and BIOs
  • 1.2.6 The CIO's View of Business Challenges and BIOs
  • 1.3 The BBF BI Vision and BI Opportunity Portfolio & Business Case
  • 1.3.1 The BBF BI Vision
  • 1.3.2 The BBF BIO Portfolio
  • 1.4 Generalizing From the BBF Case-BI Applications for Manufacturers
  • 1.5 Lessons Learned for BI Strategy-BBF BI Progress
  • 1.5.1 Lesson 1-Lack of Understanding of BI Makes the Value Hard to Determine
  • 1.5.2 Lesson 2-The Mission and Importance of BI Is Not Clear
  • 1.5.3 Lesson 3-No Sense of Urgency Among Upper Management
  • 1.6 Questions to Consider for Your Company or Function
  • 2 Business Intelligence in the Era of Big Data and Cognitive Business
  • 2.1 Getting Clear About Terminology-Business Definitions of Business Intelligence and Related Terms
  • 2.2 The Hype Around BI, Big Data, Analytics, and Cognitive Business
  • 2.3 A Business View of Big Data
  • 2.4 A Business View of Cognitive Business
  • 2.5 BI and Analytics-Is There a Difference?
  • 2.6 Beyond the Hype-What BI Success Looks Like
  • 2.6.1 Industry Views of BI Success
  • 2.7 Summary-Industry Views of BI Success
  • 2.7.1 Job Function Views of BI Success
  • 2.8 Recap of Some Key Points
  • 3 The Strategic Importance of Business Intelligence
  • 3.1 A Business View of BI
  • 3.1.1 Styles of BI
  • 3.1.2 An Effective BI Environment Provides Integrated Operational and Financial Views of Facts About Business Performance
  • 3.2 How BI Enhances Business Processes and Business Performance
  • 3.2.1 Review of Business Processes Improvement Thinking
  • 3.2.2 Decision-Making Can Be a BI-Enabled, Defined Business Process
  • 3.3 The Strategic Importance of BI
  • 3.3.1 Some Examples of the Strategic Importance of BI
  • 3.3.1.1 Financial Services Industry
  • 3.3.1.2 Grocery Stores
  • 3.3.1.3 Government Agencies
  • 3.3.1.4 Manufacturers
  • 3.4 Skill Development Opportunity: The Strategic Importance of BI
  • 3.4.1 Objectives
  • 3.5 Summary of Some Key Points
  • 4 BI Opportunity Analysis
  • 4.1 BI Opportunity Analysis Provides the Economic Rationale for BI
  • 4.2 Top-Down BI Opportunity Analysis
  • 4.3 Using Strategy Maps to Discover Bios
  • 4.4 Using Structured Interviews to Discover BIOs
  • 4.4.1 Typical "Conversation Starters" for Structured Interviews
  • 4.5 Factoring in Big Data and Cognitive Business Opportunities
  • 4.6 Documenting BIOs
  • 4.7 Skill Improvement Opportunity: Discovering BIOs and Mapping to BI Styles
  • 4.7.1 Key Objectives
  • 4.7.2 Case Study Information (Sourced From Public Documents)
  • 4.8 Summary of Some Key Points
  • 5 Prioritizing BI Opportunities (BIOs)
  • 5.1 BI Portfolio Planning and the BI Portfolio Map
  • 5.1.1 Business Impact Versus Execution Risk
  • 5.1.2 The BIO Portfolio Map (Also Known As BI Portfolio Map or BI Portfolio)
  • 5.2 Factors to Consider When Prioritizing BIOs
  • 5.2.1 Some Business Factors to Consider
  • 5.2.2 Some Technical Factors to Consider
  • 5.3 Approaches to Prioritizing BIOs
  • 5.3.1 Multiattribute Scoring Model With Voting
  • 5.3.2 Discounted Cash Flow ROI Model
  • 5.4 Skill Development Opportunity: Develop and Justify a BI Portfolio Map
  • 5.4.1 Key Objectives
  • 5.4.2 BIO Summaries
  • 5.4.3 BIO Execution Risk Summaries
  • 5.5 Summary of Some Key Points
  • 6 Leveraging BI for Performance Management, Process Improvement, and Decision Support
  • 6.1 BI as a Key Enabler of BPM
  • 6.1.1 Characteristics of an Effective, BI-Enabled BPM System
  • 6.1.2 BPM System Example: BI-Enabled Production Performance Management
  • 6.1.3 Using a Performance Scorecard to Present Performance Variances
  • 6.1.4 Using BI to Analyze Unfavorable Performance Variances
  • 6.1.5 BI-Enabled BPM: A Tool for Decision Support
  • 6.1.6 BI Enhances Close-Looped BPM
  • 6.1.7 Summary: BI Enables Efficient and Effective BPM
  • 6.2 BI as a Key Enabler of Business Process Improvement
  • 6.2.1 BI Is a Key Tool in the Business Process Improvement Toolkit
  • 6.2.2 Determining How to Leverage BI for Business Process Improvement
  • 6.2.3 Leveraging BI for Improving Performance Management Processes
  • 6.2.4 Leveraging BI to Improve Revenue Generation Processes
  • 6.2.4.1 Leveraging BI for Enhanced Revenue Generation in the Financial Services Industry
  • 6.2.4.2 Leveraging BI for Enhanced Revenue Generation in the Consumer Packed Goods Industry
  • 6.2.4.3 Leveraging Big Data and Cognitive Business Techniques for Shopper Marketing in the Retail Industry
  • 6.2.5 Leveraging BI to Improve Operating Processes
  • 6.2.5.1 Leveraging BI to Enhance Operating Processes in the CPG Industry
  • 6.2.5.2 Leveraging BI to Enhance Operating Processes in the Grocery Industry
  • 6.2.6 Summary-Leveraging BI for Business Process Improvement
  • 6.3 BI as a Key Enabler of High-Impact Business Decisions
  • 6.3.1 The Evolution of Computer-Assisted Decision Support Systems
  • 6.3.2 BI as a Decision Support Tool
  • 6.4 Skill Development Opportunity
  • 6.4.1 Insert BI Into a Business Process
  • 6.4.1.1 Key Objectives
  • 6.4.2 Design a Performance Scorecard
  • 6.4.2.1 Key Objectives
  • 6.5 Summary of Some Key Points
  • 7 Meeting the Challenges of Enterprise BI
  • 7.1 A General Management View About BI Success
  • 7.1.1 Major Workstreams Required for Enterprise BI Success
  • 7.1.2 Workstream Details
  • 7.1.3 Identifying Risks and Barriers to Success
  • 7.1.3.1 Risk Factor #1-Ability to Align and Govern
  • 7.1.3.2 Risk Factor #2-Ability to Leverage
  • 7.1.3.3 Risk Factor #3-Ability to Execute
  • 7.1.4 Summary: General Management for BI Success
  • 7.2 Challenges for BI Success
  • 7.2.1 Challenge: Lack of a Business-Driven BI Strategy
  • 7.2.1.1 BI Mission
  • 7.2.1.2 Link Between BIOs, Business Performance, and Business Process Improvement
  • 7.2.1.3 BI Barriers and Risks
  • 7.2.2 Challenge: Higher IT Priorities Slow BI Deployment
  • 7.2.3 Challenge: Higher Priorities Impede Business Engagement
  • 7.2.4 Challenge: BI Enveloped by a Broader Data Management Initiative
  • 7.2.5 Challenge: BI Managed Under Typical IT Policies and Methods
  • 7.2.5.1 The IT Shared Services Mindset
  • 7.2.5.2 Best Practices Development Methodologies for IT Projects and BI Projects are Different
  • 7.2.5.3 What is Being Optimized?
  • 7.2.6 Challenge: Barriers to Data Access
  • 7.2.7 Summary-Challenges for BI Success
  • 7.3 Organizational Design for BI Success
  • 7.3.1 Organizational Approaches to BI
  • 7.3.2 Organizational Experimentation and Exploitation of Big Data and Cognitive Business Techniques
  • 7.4 Skill Development Opportunity: Assess BI Challenges, Risks, and Barriers
  • 7.4.1 Key Objectives
  • 7.4.2 Topic List: BI Challenges, Risks, and Barriers
  • 7.5 Summary of Some Key Points
  • 8 General Management Perspectives on Technical Topics
  • 8.1 The Technical Landscape for BI Program Execution
  • 8.2 Technical Infrastructure for BI
  • 8.2.1 IT Infrastructure for BI
  • 8.2.1.1 The Challenge of IT Infrastructure as a Shared Service to the BI Program
  • 8.2.1.2 Providing Autonomous and Dedicated IT Infrastructure Assets to the BI Program
  • 8.2.1.3 Considering Cloud-Based IT Infrastructure for BI
  • 8.2.2 BI Infrastructure for BI Programs
  • 8.2.2.1 Contribution to Competitive Differentiation
  • 8.2.2.2 Switching Costs
  • 8.2.2.3 Total Cost of Ownership (TCO)
  • 8.2.2.4 BI and Data Warehousing Appliances
  • 8.2.3 Big Data Technical Considerations
  • 8.2.4 Summary-Technical Infrastructure for BI
  • 8.3 Data Infrastructure for BI
  • 8.3.1 Establishing the Data Flow Value Chain for BI
  • 8.3.2 Designing the BI Data Infrastructure
  • 8.3.2.1 Business-Driven Data Architecture
  • 8.3.2.2 Methods for Providing BI to Business Users
  • 8.4 BI and the Cloud
  • 8.5 Summary
  • Bibliography
  • Index
  • Back Cover

Dateiformat: EPUB
Kopierschutz: Adobe-DRM (Digital Rights Management)

Systemvoraussetzungen:

Computer (Windows; MacOS X; Linux): Installieren Sie bereits vor dem Download die kostenlose Software Adobe Digital Editions (siehe E-Book Hilfe).

Tablet/Smartphone (Android; iOS): Installieren Sie bereits vor dem Download die kostenlose App Adobe Digital Editions (siehe E-Book Hilfe).

E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m. (nicht Kindle)

Das Dateiformat EPUB ist sehr gut für Romane und Sachbücher geeignet - also für "fließenden" Text ohne komplexes Layout. Bei E-Readern oder Smartphones passt sich der Zeilen- und Seitenumbruch automatisch den kleinen Displays an. Mit Adobe-DRM wird hier ein "harter" Kopierschutz verwendet. Wenn die notwendigen Voraussetzungen nicht vorliegen, können Sie das E-Book leider nicht öffnen. Daher müssen Sie bereits vor dem Download Ihre Lese-Hardware vorbereiten.

Weitere Informationen finden Sie in unserer E-Book Hilfe.


Dateiformat: PDF
Kopierschutz: Adobe-DRM (Digital Rights Management)

Systemvoraussetzungen:

Computer (Windows; MacOS X; Linux): Installieren Sie bereits vor dem Download die kostenlose Software Adobe Digital Editions (siehe E-Book Hilfe).

Tablet/Smartphone (Android; iOS): Installieren Sie bereits vor dem Download die kostenlose App Adobe Digital Editions (siehe E-Book Hilfe).

E-Book-Reader: Bookeen, Kobo, Pocketbook, Sony, Tolino u.v.a.m. (nicht Kindle)

Das Dateiformat PDF zeigt auf jeder Hardware eine Buchseite stets identisch an. Daher ist eine PDF auch für ein komplexes Layout geeignet, wie es bei Lehr- und Fachbüchern verwendet wird (Bilder, Tabellen, Spalten, Fußnoten). Bei kleinen Displays von E-Readern oder Smartphones sind PDF leider eher nervig, weil zu viel Scrollen notwendig ist. Mit Adobe-DRM wird hier ein "harter" Kopierschutz verwendet. Wenn die notwendigen Voraussetzungen nicht vorliegen, können Sie das E-Book leider nicht öffnen. Daher müssen Sie bereits vor dem Download Ihre Lese-Hardware vorbereiten.

Weitere Informationen finden Sie in unserer E-Book Hilfe.


Download (sofort verfügbar)

34,45 €
inkl. 19% MwSt.
Download / Einzel-Lizenz
ePUB mit Adobe DRM
siehe Systemvoraussetzungen
PDF mit Adobe DRM
siehe Systemvoraussetzungen
Hinweis: Die Auswahl des von Ihnen gewünschten Dateiformats und des Kopierschutzes erfolgt erst im System des E-Book Anbieters
E-Book bestellen

Unsere Web-Seiten verwenden Cookies. Mit der Nutzung des WebShops erklären Sie sich damit einverstanden. Mehr Informationen finden Sie in unserem Datenschutzhinweis. Ok