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Key Business Analytics: The 60+ Business Analysis Tools Every Manager Needs to Know
作者 Bernard Marr
出版社 FT Publishing
ISBN 9781292017433
分類 Business & Finance > Management & Leadership
價格 HK$375.00
 
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Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimize their internal processes and identify cost savings and growth opportunities.

It includes analysis techniques within the following categories:

* Financial analytics – cashflow, profitability, sales forecasts
* Market analytics – market size, market trends, marketing channels
* Customer analytics – customer lifetime values, social media, customer needs
* Employee analytics – capacity, performance, leadership
* Operational analytics – supply chains, competencies, environmental impact
* Bare business analytics – sentiments, text, correlations

Each tool will follow the bestselling Key format of being 5-6 pages long, broken into short sharp advice on the essentials:

* What is it?
* When should I use it?
* How do I use it?
* Tips and pitfalls
* Further reading

This essential toolkit also provides an invaluable section on how to gather original data yourself through surveys, interviews, focus groups, etc.


About the Author:

Bernard Marr is a leading global authority on organisational performance & business success. He regularly advises organisations & governments across the globe & is an acclaimed, award-winning keynote speaker, researcher, consultant & teacher. He's acknowledged by the CEO Journal as one of today’s leading business brains.


Introduction

The Raw Material - Data

Data Types and Format

How to use this book

Part One: Bare Analytics
1: Business Experiments / Experimental Design / AB testing
2: Visual Analytics
3: Correlation Analysis
4: Scenario Analysis
5: Forecasting / Time Series Analysis
6: Data mining
7: Regression Analysis
8: Text Analytics
9: Sentiment analysis
10: Image Analytics
11: Video Analytics
12: Voice Analytics
13: Monte Carlo Simulation
14: Linear Programming
15: Cohort Analysis
16: Factor analysis
17: Neural Network Analysis
18: Meta Analytics - Literature Analysis

Part II: Analytics Input Tools or Data Collection Methods
19: Quantitative Surveys
20: Qualitative Surveys
21: Focus Groups
22: Interviews
23: Ethnography
24: Text Capture
25: Image Capture
26: Sensor Data
27: Machine data capture

Part Three: Financial Analytics
28: Predictive sales analytics
29: Customer Profitability analytics
30: Product Profitability analytics
31: Cashflow analytics
32: Value Driver Analytics
33: Shareholder value analytics
34: Risk Reward Analytics
35: Unmet need analytics
36: Market Size Analytics
37: Demand Forecasting
38: Market Trend Analytics
39: Non-customer analytics
40: Competitor analytics
41: Pricing analytics
42: Marketing channel analytics
43: Brand Analytics

Part Five: Customer Analytics
44: Customer satisfaction analysis
45: Customer Lifetime Value Analytics
46: Customer segmentation analytics
47: Sales Channel Analytics
48: Web Analytics
49: Social Media Analytics
50: Customer Engagement Analytics
51: Customer Churn Analytics
52: Customer acquisition analytics

Part Six: Employee Analytics
53: Capability Analytics
54: Capacity Analytics
55: Employee Churn Analytics
56: Recruitment channel analytics
57: Competency acquisition analytics
58: Employee Performance Analytics
59: Corporate culture analytics
60: Leadership Analytics

Part Seven: Operational Analytics
61: Fraud Detection Analytics
62. Core Competency Analytics
63: Supply Chain Analytics
64: Lean Six Sigma Analytics
65. Capacity Utilisation Analytics
66: Project and Program Analytics
67. Environmental Impact Analytics
68: Corporate Social Responsibility (CSR) Analytics

Index


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