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[null,"1.","Record Nr.",null,"UNINA9910554855403321"]
[null,null,"Autore",null,"Kaufmann Uwe H."]
[null,null,"Titolo",null,"Data analytics for organisational development : unleashing the potential of your data / / Uwe H. Kaufmann, Amy BC Tan"]
[null,null,"Pubbl/distr/stampa",null,"West Sussex, England : , : Wiley, , [2021]"]
[{"$nulls":4},"©2021"]
[null,null,"ISBN",null,"1-119-75837-8"]
[{"$nulls":4},"9781119758334"]
[{"$nulls":4},"1-119-75832-7"]
[{"$nulls":4},"1-119-75831-9"]
[null,null,"Descrizione fisica",null,"1 online resource (364 pages)"]
[null,null,"Disciplina",null,"658.0557"]
[null,null,"Soggetti",null,"Business enterprises - Data processing"]
[{"$nulls":4},"Organizational change"]
[{"$nulls":4},"Electronic books."]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Cover -- Title Page -- Copyright Page -- Contents -- Foreword -- Preface -- About the Authors -- Introduction: Why Data Analytics is Important -- Why This Book Has Been Written -- How This Book Is Structured -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- What Tools Are Used -- Activating and Using MS Excel's Analysis ToolPak -- Downloading and Using MS Power BI -- Downloading and Using R and R Studio -- What Is Provided -- Which Cases Should I Study? -- References -- List of Figures and Tables -- Chapter 1 Introduction to Data Analytics and Data Science -- Components of Data Analytics -- Big Data and its Relationship to Data Analytics -- Data Analytics - The Foundation for Data Science and Artificial Intelligence -- Practice -- Phases of Data Analytics -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- Analytical Story Telling -- Deploying Analytics Tools -- Practice -- Competencies of a Data Scientist -- Competencies Needed in Data Analytics Phases -- Key Roles of Today's Managers and Leaders -- References -- List of Figures and Tables -- Chapter 2 Customer Domain - Customer Analytics -- Why Customer Analytics? -- Listen to the Voice of Your Existing Customers -- Understanding Customer Expectations -- "]
[{"$nulls":4},"Studying the Complete Customer Experience -- Designing Customer Surveys -- Determine the Purpose of your Survey -- Use Proven Questionnaires -- Use Proven Scales -- Test Your Survey Questionnaire -- Decide on the Distribution of the Questionnaire -- Select an Appropriate Timing for your Survey -- Begin with the End in Mind -- Some More Considerations -- Conclusion -- Practice -- Case 1: Great, We Have Improved . . . or Not? -- The Problem with Sampling -- Understanding Confidence Intervals -- Means Are Lies -- Business Question."]
[{"$nulls":4},"Data Collection -- Data Processing -- Data Analysis -- Business Decision -- Analytical Storytelling -- What If We Had All The Data? -- Deploying Analytics Tools -- Practice -- Case 2: What Drives our Patient Satisfaction? -- Patient Satisfaction in an Outpatient Clinic -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- Analytical Storytelling -- Practice -- Deploying Analytics Tools -- Case 3: How to Create a Patient Satisfaction Dashboard -- Deciding about Metrics to Illustrate our Clinic Performance -- Building a Clinic Dashboard with MS Power BI and R -- Using MS Power BI for Analytical Storytelling -- Conclusion -- Practice -- References -- List of Figures andTables -- Chapter 3 Process Domain - Operations Analytics -- Why Operations Analytics? -- Dimensions of Operations Analytics -- Process Design Using Analytics -- Defining Measures for Analytics -- Process Management Using Analytics -- Process Improvement Using Analytics - The Power of DMAIC -- Roles and Deployment of Operations Analytics -- Conclusion -- Practice Questions -- Case 4: Which Supplier has the Better Product Quality? -- Business Question -- Data Acquisition -- Data Analysis -- Business Decision -- Deploying Analytics Tools -- Practice -- Case 5: Why Does Finance Pay Our Vendors Late? -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- Deploying Analytics Tools -- Practice -- Case 6: Why Are We Wasting Blood? -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- Deploying Analytics Tools -- Practice -- References -- List of Figures and Tables -- Chapter 4 Workforce Domain - Workforce Analytics -- Why Workforce Analytics? -- Why has the topic \"workforce analytics\" developed into a priority? -- Dimensions of Workforce Analytics."]
[{"$nulls":4},"Putting Workforce Analytics into Practice -- Using Descriptive and Predictive Workforce Analytics in Workforce Planning -- Workforce Planning for Transactional Processes -- Workforce Planning for Less Transactional Processes -- Workforce Planning from the Workforce Perspective -- Getting the Intent Right -- a) Connect HR Data and Business Outcomes -- b) Determine Information Needed and Collect Data -- c) Analyse the Data -- d) Derive and Formulate a Business Answer - Tell a Story -- Workforce Analysts' Paradise is Employees' Nightmare - Managing the Change -- Summary -- Practice -- Case 7: Do We Have Enough People to Run Our Organisation? - Workforce Planning Inside-Out -- Data Acquisition and Data Wrangling -- Understanding the Demand Pattern -- Predicting a Potential Future Problem -- Understanding the Activity Pattern -- Planning the Workforce -- \"Fighting Variation\" -- Rethinking and Innovating the Process -- Conclusion -- Practice -- Deploying Analytics Tools -- Case 8: What Makes Our Staff Innovate? -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision and Storytelling -- Deploying Analytics Tools -- Background -- Case 9: What Does Our Engagement Survey Result Mean? -- Why We Should not Trust this Data Easily -- Performing a Proper Data Analysis -- Making a Better Decision -- Practice -- Deploying Analytics Tools -- Case 10: "]
[{"$nulls":4},"What Drives Our Staff Out? - Logistic Regression for Prediction and Decision Making -- Business Question -- Data Acquisition -- Data Preparation -- Data Analysis -- Business Decision -- Summary -- Practice -- Deploying Analytics Tools -- References -- Table of Equations, Figures, Tables -- Chapter 5 Implementing Data Analytics for Organisational Development -- Making Better Decisions - Knowing the Risk of Being Wrong -- There is No Difference, and We Decide There Is None."]
[{"$nulls":4},"There is No Difference, and We Decide There Is One - Type I Error -- There Is a Difference, and We Decide There Is One -- There Is a Difference, but We Decide There Is None - Type II Error -- Making Better Decisions - Do not Trust Statistics Blindly -- Significant Difference Does Not Mean Important Difference -- A Non-Significant Difference Could Be Important for The Organisation -- Data Analytics Does Not Take Over Decision Making -- Ensuring the Success of Your Data Analytics Journey -- Steps for Implementing Data Analytics -- Ensuring the Management Walks and Talks Analytics -- Creating Excitement for Data Analytics and its Benefits -- Developing a Body of Knowledge - Start Small -- Using Analytics to Breakdown Silos -- Closing the Analytics Loop - Sustaining the Gains -- Calibrating Your Data Analytics Implementation -- Outlook -- References -- List of Figures and Tables -- Materials for Download -- Index -- EULA."]