Business Analytics for Managers: Taking Business Intelligence Beyond Reporting

THE NEW WAYS BIG DATA CAN BE PROCESSED AND APPLIED TO DRIVE PROFITS

Business Analytics for Managers, Second Edition offers up–to–date guidance and fresh applications of its popular framework to enable businesses to gain even more insight from their big data and stay way ahead of the competition with predictive models. Fully revised with comprehensive material on the technologies and practices revolutionizing the field, this single resource is all you need to create and practice high–level business analytics (BA) at the forward edge of innovation. Focused on how BA can optimize business planning, this everyday guidebook gives you a convenient way to:

See how open–source software like Hadoop can open limitless opportunities for data storage and applications Dig into all the innovative ways companies are successfully using social media for both analysis and as a channel to apply the conclusions Act confidently with authoritative explanations of the latest best practices for cloud technologies, data security, and more

Before you decide you know how BA works, look at Business Analytics for Managers, Second Edition and see all the ways it can work for you.

Foreword

Introduction

What Is the Scope of BA? Information Systems Not Technical Solutions

Purpose and Audience

Organization of Chapters

Why the Term Business Analytics?

Chapter 1: The Business Analytics Model

Overview of the Business Analytics Model

Strategy Creation

Business Processes and Information Use

Types of Reporting and Analytical Processes

Data Warehouse

Data Sources: IT Operations and Development

Deployment of the Ba Model

Case Study: How to Make an Information Strategy for a Radio Station

Summary

Chapter 2: Business Analytics at the Strategic Level

Link between Strategy and the Deployment of BA

Strategy and BA: Four Scenarios

Scenario 1: No Formal Link between Strategy and BA

Scenario 2: BA Supports Strategy at a Functional Level

Scenario 3: Dialogue between the Strategy and the BA Functions

Scenario 4: Information as a Strategic Resource

Which Information Do We Prioritize?

The Product and Innovation Perspective

Customer Relations Perspective

The Operational Excellence Perspective

Summary

Chapter 3: Development and Deployment of Information at the Functional Level

Case Study: A Trip to the Summerhouse

Speci cation of Requirements

Your Technical Support

And Now Off We Go to the Summerhouse

Your Lead and Lag information

More about Lead and Lag Information

Establishing Business Processes with the Rockart Model

Example: Establishing New Business Processes with the Rockart Model

Level 1: Identifying the Objectives

Level 2: Identifying an Operational Strategy

Level 3: Identifying the Critical Success Factors

Level 4: Identifying Lead and Lag Information

Optimizing Existing Business Processes

Example: Deploying Performance Management to Optimize Existing Processes

Concept of Performance Management

Which Process Should You Start With?

CRM Activities

Campaign Management

Product Development

Web Log Analyses

Pricing

Human Resource Development

CPM

Finance

Inventory Management

Supply Chain Management

Lean

A Catalogue of Ideas with KPIs for the Company s Different Functions

Summary

Chapter 4:  Business Analytics at the Analytical Level

Data, Information, and Knowledge

Analyst s Role in the BA Model

Three Requirements the Analyst Must Meet

Business Competencies

Tool Kit Must Be in Order (Method Competencies)

Technical Understanding (Data Competencies)

Required Competencies for the Analyst

Analytical Methods (Information Domains)

How to Select the Analytical Method

The Three Imperatives

Descriptive Statistical Methods, Lists, and Reports

HYPOTHESIS–DRIVEN METHODS

Tests with Several Input Variables

Data Mining with Target Variables

Data Mining Algorithms

Explorative Methods

Data Reduction

Cluster Analysis

Cross–Sell Models

Up–Sell Models

Business Requirements

De nition of the Overall Problem

De nition of Delivery

De nition of Content

Summary

Chapter 5:  Business Analytics at the Data Warehouse Level

Why a Data Warehouse?

Architecture and Processes in a Data Warehouse

Selection of Certain Columns to Be Loaded

Staging Area and Operational Data Stores

Causes and Effects of Poor Data Quality

The Data Warehouse: Functions, Components, and Examples

Alternative Ways of Storing Data

Business Analytics Portal: Functions and Examples

Tips and Techniques in Data Warehousing

Master Data Management

Service–Oriented Architecture

How Should You Access Your Data?

Access to BA Portals

Access to Data Mart Areas

Access to Data Warehouse Areas

Access to Source Systems

Summary

Chapter 6: The Company s Collection of Source Data

What Are Source Systems, and What Can They Be Used For?

Which Information Is Best to Use for Which Task?

When There Is More Than One Way to Get the Job Done

When the Quality of Source Data Fails

Summary

Chapter 7: Structuring of a Business Analytics Competency Center

What Is a Business Analytics Competency Center?

Why Set up a Business Analytics Competency Center?

Tasks and Competencies

Establishing an Information Wheel

Creating Synergies between Information Wheels

Educating Users

Prioritizing New BA Initiatives

Competencies

Centralized or Decentralized Organization

Strategy and Performance

When the Analysts Reports to the IT Department

When Should a BACC Be Established?

Applying the analytical factory approach

Summary

Chapter 8:  Assessment and Prioritization of BA Projects

Is It a Strategic Project or Not?

Uncovering the Value Creation of the Project

When Projects Run Over Several Years

When the Uncertainty Is Too Big

The Descriptive Part of the Cost/Bene t Analysis for the Business Case

The Cost/Bene t Analysis Used for the Business Case

Projects as Part of the Bigger Picture

Case Study on How to Make a Information Strategy Roadmap

Summary

Chapter 9:  Business Analytics in the Future

About the Authors

Index

GERT H. N. LAURSEN is a business consultant who builds analytical organizations around the world. He also builds disruptive business strategies for global market leaders and humanitarian organizations. He has an MBA in digital strategy, a master′s degree in marketing, and was named a global thought leader by IBM and SAS Institute.

JESPER THORLUND is a business intelligence consultant and frequent speaker on business intelligence, business analytics, and microeconomics throughout Europe.