A practitioner's guide to business analytics using data analysis tools to improve your organization's decision making and strategy
Gain the competitive edge with the smart use of business analytics In today’s volatile business environment, the strategic use of business analytics is more important than ever. A Practitioners Guide to Business Analytics helps you get the organizational commitment you need to get business analytics...
| Otros Autores: | |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York :
McGraw-Hill
[2013]
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| Edición: | 1st edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628001406719 |
Tabla de Contenidos:
- Intro
- Preface
- Acknowledgments
- Part I Introduction and Strategic Landscape
- Big Data
- 1 The Business Analytics Revolution
- Information Technology and Business Analytics
- The Need for a Business Analytics Strategy
- The Complete Business Analytics Team
- Section 1.1 Best Statistical Practice = Meatball Surgery
- Bad News and Good News
- Section 1.2 The Shape of Things to Come-Chapter Summaries
- PART I The Strategic Landscape-Chapters 1 to 6
- PART II Statistical QDR: Three Pillars for Best Statistical Practice-Chapters 7 to 9
- PART III Data CSM: Three Building Blocks for Supporting Analytics-Chapters 10 to 12
- Notes
- 2 Inside the Corporation
- Section 2.1 Analytics in the Traditional Hierarchical Management Offense
- Leadership and Analytics
- Specialization
- Delegating Decisions
- Incentives
- Section 2.2 Corporate Analytics Failures-Shakespearean Comedy of Statistical Errors
- The Financial Meltdown of 2007-2008: Failures in Analytics
- Fannie Mae: Next to the Bomb Blast
- The Great Pharmaceutical Sales-Force Arms Race by Tom "T. J." Scott
- Inside the Statistical Underground-Adjustment Factors for the Pharmaceutical Arms Race by Brian Wynne
- Section 2.3 Triumphs of the Nerds
- Proving Grounds-Model Review at The Associates/Citigroup
- Predicting Fraud in Accounting: What Analytics-Based Accounting Has Brought to "Bare" By Hakan Gogtas, Ph.D.
- Notes
- 3 Decisions, Decisions
- Section 3.1 Fact-Based Decision Making
- Combining Industry Knowledge and Business Analytics9
- Critical Thinking
- Section 3.2 Analytics-Based Decision Making: Four Acts in a Greek Tragedy17
- Act I: Framing the Business Problem
- Act II: Executing the Data Analysis
- Act III: Interpreting the Results
- Act IV: Making Analytics-Based Decisions
- Consequences (of Tragedy).
- Act V: Reviewing and Preparing for Future Decisions
- Section 3.3 Decision Impairments: Pitfalls, Syndromes, and Plagues in Act IV
- Plague: Information and Disinformation Overload
- Pitfall: Overanalysis
- Pitfall: Oversimplifi cation
- Syndrome: Deterministic Thinking
- Syndrome: Overdependence on Industry Knowledge
- Pitfall: Tunnel Thinking
- Syndrome: Overconfi dent Fool Syndrome
- Pitfall: Unpiloted Big Bang Launches
- Notes
- 4 Analytics-Driven Culture
- Left Brain-Right Brain Cultural Clash-Enter the Scientific Method
- Denying the Serendipity of Statistics
- Denying the Source-Plagiarism
- Section 4.1 The Fertile Crescent: Striking It Rich
- Catalysts and Change
- Two-Trick Pony
- Section 4.2 The Blend: Mixing Industry Knowledge and Advanced Analytics
- Cultural Imbalance
- The Gemini Myths
- Notes
- 5 Organization: The People Side of the Equation
- Section 5.1 Analytics Resources
- Business Quants-Denizens of the Deep
- Analytics Power Users
- Business Analysts
- Knowledge Workers
- Section 5.2 Structure of Analytics Practitioners
- Integration Synergies
- Technical Connectivity
- Specialization
- Teamwork
- Technical Compatibility
- Section 5.3 Building Advanced Analytics Leadership
- Leadership and Management Skills
- Business Savvy
- Communication Skills
- Training and Experience
- On-Topic Leadership by Charlotte Sibley
- Expert Leaders (ELs)-Corporate Trump Cards
- The Blood-Brain Barrier
- Advantages of On-Topic Business Analytics Leaders
- Management Types by David Young
- Section 5.4 Location, Location, Location of Analytics Practitioners
- Outsourcing Analytics
- Dispersed or Local Groups
- Central or Enterprise-Wide Groups32
- Hybrid: Outside + Local + Enterprise-Wide
- Notes
- 6 Developing Competitive Advantage
- Approach for Identifying Gaps in Analytics
- Strategy.
- Protecting Intellectual Property
- Section 6.1 Triage: Assessing Business Needs
- Process Mapping of Analytics Needs
- Innovation: Identifying New Killer Apps
- Scrutinizing the Inventory
- Assigning Rigor and Deducing Resources
- Section 6.2 Evaluating Analytics Prowess: The White-Glove Treatment
- Leading and Organizing
- Progress in Acculturating Analytics
- Evaluating Decision-Making Capabilities
- Evaluating Technical Coverage
- Executing Best Statistical Practice
- Constructing Effective Building Blocks
- Business Analytics Maturity Model
- Section 6.3 Innovation and Change from a Producer on the Edge
- Emphasis on Speed
- Continual Improvement15
- Accelerating the Offense-For Those Who Are Struggling
- Notes
- Part II The Three Pillars of Best Statistical Practice
- Blind Man's Russian Roulette Bluff
- 7 Statistical Qualifications
- Section 7.1 Leadership and Communications for Analytics Professionals
- Leadership
- Communication
- Leadership and Communication Training
- Section 7.2 Training for Making Analytics-Based Decisions
- Statistical "Mythodologies"
- Section 7.3: Statistical Training for Performing Advanced Analytics14
- The Benefi ts of Training
- Academic Training23
- Post-Academic Training-Best Statistical Practice
- Training Through Review
- Section 7.4 Certifi cation for Analytics Professionals
- The PSTAT® (ASA) (Professional Statistician)-ASA's New Accreditation by Ronald L. Wasserstein, Ph.D.
- Professionalism
- Notes
- 8 Statistical Diagnostics
- The Model Overfitting Problem
- Section 8.1 Overview of Diagnostic Techniques
- External Numbers
- Juxtaposing Results
- Data Splitting (Cross-Validation)
- Resampling Techniques with Replacement
- Standard Errors for Model-Based Group Differences: Bootstrapping to the Rescue7 by James W. Hardin, Ph.D.
- Simulation/Stress Testing.
- Tools for Performance Measurement
- Tests for Statistical Assumptions
- Tests for Business Assumptions
- Intervals and Regions
- DoS (Design of Samples)
- DoE (Design of Experiments)
- Section 8.2 Juxtaposition by Method
- Paired Statistical Models
- Section 8.3 Data Splitting
- Coping with Hazards
- K-Fold Cross-Validation
- Sequential Validation (with Three or More Splits)
- Notes
- 9 Statistical Review-Act V
- Élan
- Qualifi cations and Roles of Reviewers
- Statistical Malpractice
- Section 9.1 Purpose and Scope of the Review
- Purpose
- Scope
- Context
- Section 9.2 Reviewing Analytics-Based Decision Making-Acts I to IV
- Reviewing Qualifi cations of Analytics Professionals-Checking the Q in QDR
- Restrictions Imposed on the Analysis
- Appropriate and Reliable Data
- Analytics Software
- Reasonableness of Data Analysis Methodology
- Reasonableness of Data Analysis Implementation
- Statistical Diagnostics-Checking the D in QDR
- Interpreting the Results (Transformation Back), Act III
- Reviewing Analytics-Based Decision Making, Act IV
- Closing Considerations-Documentation, Maintenance, Recommendations, and Rejoinder
- Notes
- Part III Building Blocks for Supporting Analytics
- 10 Data Collection
- Randomization
- Interval and Point Estimation
- Return on Data Investment
- Measuring Information
- Measurement Error12
- Section 10.1 Observational and Censual Data (No Design)
- Section 10.2 Methodology for Anecdotal Sampling
- Expert Choice
- Quota Samples
- Dewey Defeats Truman
- Focus Groups14
- Section 10.3 DoS (Design of Samples
- Sample Design
- Simple Random Sampling
- Systematic Sampling
- Advanced Sample Designs
- The Nonresponse Problem
- Post-Stratifying on Nonresponse
- Panels, Not to Be Confused with Focus Groups
- Section 10.4 DoE (Design of Experiments)
- Experimental Design.
- Completely Randomized Design
- Randomized Block Design
- Advanced Experimental Designs
- Experimental Platforms
- Notes
- 11 Data Software
- Section 11.1 Criteria
- Functional and Technical Capabilities
- Maintenance
- Governance and Misapplication
- Fidelity
- Efficiency and Flexibility
- Section 11.2 Automation
- Data Management
- Data Analysis
- Presenting Findings
- Monitoring Results
- Decision Making
- Notes
- 12 Data Management
- Information Strategy
- Data Sources
- Security
- Section 12.1 Customer-Centric Data Management
- Customer Needs
- Data Quality-That "Garbage In, Garbage Out" Thing
- Inspection
- Data Repair
- Section 12.2 Database Enhancements
- Database Encyclopedia
- Data Dictionaries
- Variable Organization
- Notes
- Concluding Remarks
- Appendix Exalted Contributors: Analytics Professionals
- References
- Index.
