Description
Book SynopsisLearn the secrets to using analytics to grow your business
Analytics continues to trend as one of the hottest topics in the business community today. With ever-growing amounts of business data and evolving performance management/business intelligence architectures, how well your business does analyzing its data will differentiate you from your competition. Killer Analytics explores how you can use the muscle of analytics to measure new business elements. Author Mark Brown introduces 20 new metrics that can drive competitive advantage for your business, including social networks, sustainability, culture, innovation, employee satisfaction, and other key business elements.
- Shows organizations how to use analytics to measure key elements of business performance not traditionally measured
- Introduces 20 new metrics that drive competitive advantage
- Reveals how to measure social networking, sustainability, innovation, culture, and more
Table of Contents
Foreword xv
Preface xix
Acknowledgments xxvii
Introduction: What are Predictive Analytics? 1
Learning from Past Mistakes 1
Organizational Cholesterol 3
Uses of Predictive Analytics 3
Analytics versus Formulas versus Singular Metrics 8
Time Perspectives 10
Past, Present, and Future 10
Analytics are Superior to Individual Metrics 11
Myths and Facts about Analytics 15
Analytics Used for Studies versus Ongoing Performance Measurement 18
Part One Operational Analytics 21
Chapter 1 The Innovation Index 23
What is Important about Innovation? 24
Types of Organizations Where This Metric is Appropriate 28
How Does This Impact Performance? 29
Mostly Worthless Innovation Metrics 30
Cost and Effort to Measure 31
How Do I Measure It? 32
Formula and Frequency 35
Variations 35
Targets and Benchmarks 36
Benefits of Data 36
Note 37
Chapter 2 The Supply Chain Index 39
Types of Organizations Where This Metric is Appropriate 41
How Does This Impact Performance? 42
Cost and Effort to Measure 42
How Do I Measure It? 43
Formula and Frequency 47
Variations 48
Targets and Benchmarks 48
Benefits of Data 49
Chapter 3 The Project Management Index 51
Types of Organizations Where This Metric is Appropriate 53
How Does This Impact Performance? 53
Cost and Effort to Measure 54
How Do I Measure It? 56
Process and Churn: Two Additional Metrics to Consider in a Project Management Analytic 57
Measuring Risk on Projects 59
Variations 60
Formula and Frequency 61
Targets and Benchmarks 62
Benefits of Data 62
Chapter 4 The Enterprise Excellence Index 65
Why Trash All These Sacred Cows? 65
Types of Organizations Where This Metric is Appropriate 67
How Does This Impact Performance? 68
Cost and Effort to Measure 69
How Do I Measure It? 70
Knowledge Management Metrics 71
Lean or Six Sigma Metrics 74
Formula and Frequency 75
Variations 77
Targets and Benchmarks 77
Benefits of Data 77
Note 78
Chapter 5 The Risk Index 79
Types of Organizations Where This Metric is Appropriate 80
How Does This Impact Performance? 80
Cost and Effort to Measure 81
How Do I Measure It? 82
Variations 88
Formula and Frequency 89
Benefits of Data 89
Chapter 6 The Opportunity Management Index 91
Types of Organizations Where This Metric is Appropriate 92
How Does This Impact Performance? 93
Cost and Effort to Measure 95
How Do I Measure It? 95
Formula and Frequency 99
Variations 99
Targets and Benchmarks 100
Benefits of Data 100
Chapter 7 The External Factors Index 103
Types of Organizations Where This Metric is Appropriate 105
How Does This Impact Performance? 106
Cost and Effort to Measure 107
How Do I Measure It? 107
Variations 109
Formula and Frequency 109
Targets and Benchmarks 110
Benefits of Data 110
Chapter 8 The Sustainability Index 113
Types of Organizations Where This Metric is Appropriate 114
How Does This Impact Performance? 115
Cost and Effort to Measure 115
How Do I Measure It? 116
Variations 118
Formula and Frequency 120
Targets and Benchmarks 121
Benefits of Data 121
Note 121
Part Two Customer and Stakeholder Analytics 123
Chapter 9 The Outcomes Index 125
Types of Organizations Where This Metric is Appropriate 127
How Does This Impact Performance? 128
Cost and Effort to Measure 129
How Do I Measure It? 129
Formula and Frequency 131
Variations 132
Targets and Benchmarks 132
Benefits of Data 133
Chapter 10 The Customer Engagement Index 135
Types of Organizations Where This Metric is Appropriate 136
How Does This Impact Performance? 137
Cost and Effort to Measure 138
How Do I Measure It? 139
What Factors Should Be Included in a Customer Engagement Index? 141
Variations 146
Formula and Frequency 147
Benefits of Data 147
Note 147
Chapter 11 The Social Network Index 149
Net Promoter Score: The New and Improved Survey Method 151
Types of Organizations Where This Metric is Appropriate 151
How Does This Impact Performance? 153
Cost and Effort to Measure 155
How Do I Measure It? 156
Sorting Out the Beautiful from the Ugly Customers 157
Variations 160
Targets and Benchmarks 160
Benefits of Data 161
Notes 161
Chapter 12 The Service Excellence Index 163
Types of Organizations Where This Metric is Appropriate 164
How Does This Impact Performance? 165
Cost and Effort to Measure 165
How Do I Measure It? 166
Formula and Frequency 172
Variations 173
Targets and Benchmarks 173
Benefits of Data 174
Chapter 13 The Customer Rage Index 175
Problems with Customer Surveys 177
Types of Organizations Where This Metric is Appropriate 178
How Does This Impact Performance? 179
Cost and Effort to Measure 180
How Do I Measure It? 181
Tracking Aggravations at Different Types of Organizations 181
Hospital Rage Index 182
Advantages and Disadvantages of the Aggravation or Rage Index 183
Constructing the Index 183
Formula and Frequency 184
Variations 185
Targets and Benchmarks 185
Benefits of Data 185
Chapter 14 The American Index 187
Types of Organizations Where This Metric is Appropriate 189
How Does This Impact Performance? 189
Cost and Effort to Measure 190
How Do I Measure It? 191
Variations 191
Formula and Frequency 192
Targets and Benchmarks 193
Benefits of Data 193
Chapter 15 The Corporate Citizenship Index 195
Types of Organizations Where This Metric is Appropriate 197
How Does This Impact Performance? 198
Cost and Effort to Measure 199
How Do I Measure It? 199
Formula and Frequency 204
Variations 205
Targets and Benchmarks 205
Benefits of Data 205
Notes 206
Part Three People Analytics 207
Chapter 16 The Human Capital Index 209
Types of Organizations Where This Metric is Appropriate 211
How Does This Impact Performance? 212
Cost and Effort to Measure 214
How Do I Measure It? 215
Formula and Frequency 221
Variations 222
Targets and Benchmarks 223
Benefits of Data 223
Chapter 17 The Workforce Happiness Index 225
What Makes Employees Happy? 226
Types of Organizations Where This Metric is Appropriate 227
How Does This Impact Performance? 228
A Culture of Weirdness and Fun 230
Cost and Effort to Measure 231
How Do I Measure It? 231
Net Promoter Score 233
Using Social Media to Track Employee Happiness 234
Formula and Frequency 235
Variations 236
Targets and Benchmarks 237
Benefits of Data 237
Note 238
Chapter 18 The Culture Index 239
Types of Organizations Where This Metric is Appropriate 240
How Does This Impact Performance? 243
Pets before Profits: Purina’s Corporate Culture 244
Cost and Effort to Measure 245
How Do I Measure It? 245
Variations 248
Formula and Frequency 249
Targets and Benchmarks 250
Benefits of Data 250
Note 251
Chapter 19 The Distraction Index 253
Types of Organizations Where This Metric is Appropriate 254
How Does This Impact Performance? 255
Cost and Effort to Measure 256
How Do I Measure It? 257
Formula and Frequency 258
Variations 258
Targets and Benchmarks 259
Benefits of Data 259
Chapter 20 The Corporate Wellness Index 261
Types of Organizations Where This Metric is Appropriate 263
How Does This Impact Performance? 264
Halfhearted Approaches to Wellness 265
What Really Works: Tough Policies 265
What Really Works: In-House Health and Wellness Centers 266
What Really Works: Hiring the Right People 267
Cost and Effort to Measure 268
How Do I Measure It? 269
Variations 273
Formula and Frequency 274
Targets and Benchmarks 274
Benefits of Data 275
Note 275
About the Author 277
Index 279
