Measurement Madness - Recognizing and Avoiding the Pitfalls of Performance Measurement
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More About This Title Measurement Madness - Recognizing and Avoiding the Pitfalls of Performance Measurement

English

DINA GRAY, PhD is a Strategic Business Consultant lecturing on Cranfield University's Executive Education programmes, and she is also Chair of the Regional Advisory Boards for the Innovation Group plc. advising on strategic performance implementation.

PIETRO MICHELI, PhD is Associate Professor of Organizational Performance at Warwick Business School. As a management consultant, he has worked with over 30 organizations, private and public. As a researcher, he has published widely on the subjects of performance measurement and innovation.

ANDREY PAVLOV, PhD is a Lecturer in Business Performance Management at Cranfield School of Management and Director of the Executive MSc in Managing Organisational Performance at Cranfield. He is a regular speaker at conferences around the world, and his work has been published in numerous industry and academic journals.

English

From the Authors xi

PART I INTRODUCTION 1

1 The Road to Insanity 3

2 Performance and Measurement 13

What is performance measurement? 14

What is performance? 15

What is measurement? 17

Getting the number or changing the behaviour? 20

PART II PERFORMANCE MEASUREMENT 21

3 Measurement for Measurement’s Sake 23

Making things measurable 25

Measures and more measures 27

Competitive measuring 27

Sticky measures 27

Conflicting measures 28

Losing the link to performance 29

Excessive reliance on measures 30

Fixating on measures 31

Getting desensitized to numbers 33

Getting lost in performance data 34

Paying the price 35

Preventing learning and change 37

Learning points 37

Deciding what to measure 38

Designing a robust indicator 40

Managing with measures 41

And finally… 41

4 All I Need is the Right Measure! 43

How difficult can this be? 46

What’s in a name? 46

Knowing the purpose 47

Poor relations 48

It’s in the formula 49

Frequency 50

Where does the data come from? 51

What will you do with the results? 53

How strong are your indicators? 54

Is the indicator measuring

what it is meant to measure? 55

Is the indicator only measuring

what it is meant to measure? 56

Is the indicator definitely the right indicator? 57

Is the indicator consistent regardless of

who measures and when? 58

Can the data be readily communicated

and easily understood? 59

Is any ambiguity possible in the

interpretation of the results? 60

Can and will the data be acted upon? 61

Can the data be analyzed soon enough

for action to be taken? 62

Is the cost of collecting and analyzing data justified? 63

Will the measure encourage any undesirable behaviours? 64

Learning points 66

It’s not just a KPI 66

Pass or fail 67

And finally… 67

5 Comparing Performance 69

Apples and pears 73

Differences in data collection 73

Different datasets 75

Different methodologies 76

Interpretation and presentation 78

Timeliness 80

Special variation 81

Choice and relevance 82

Using data unintended for comparative purposes 83

Yes, but… 84

Moving up the rankings 85

Unintended consequences 89

Learning points 92

Which data to collect? 93

Collection mechanisms 93

Consistency 94

Handling ambiguity 94

And finally… 95

PART III PERFORMANCE MANAGEMENT 97

6 Target Turmoil 99

What are performance targets? 102

When targets go bad 104

Are targets so bad? 106

The main pitfalls 107

When targets do good 114

Clarity and commitment 116

Unexpected benefits 118

Learning points 119

Types of targets 121

Setting targets 122

Feedback 123

Targets and incentives 124

In summary 124

And finally… 126

7 Gaming and Cheating 127

Gaming: what is it? 129

Gaming and cheating 133

What drives gaming and cheating? 137

The pressure to perform 139

Targets – the wrong kind and in the wrong way 141

The climate of competitiveness 142

Types of gaming 144

The number and predictability of gaming behaviours 145

Learning points 149

Relieving the pressure 150

Setting the right kind of target 150

Foreseeing the future 151

Improving data management systems 151

Changing the culture 152

And finally... 154

8 Hoping for A Whilst Rewarding B 157

Common management reward follies 160

Hoping for teamwork whilst rewarding individual effort 160

Hoping for the long term whilst rewarding

short-term gain 162

Hoping for truth whilst rewarding lies 163

Hoping for contribution whilst rewarding outcomes 166

Hoping for budget control whilst rewarding overspend 167

Learning points 169

Targets, rewards and measures 169

Reward people later 171

Avoid negative spillover 171

Systems thinking 172

And finally… 173

9 Failing Rewards and Rewarding Failure 175

Top rewards for top performers 178

Rewarding failure 179

Failing rewards 180

Measurement, rewards and motivation 182

When financial rewards backfire 185

What motivates us? 188

Learning points 192

Motivation and long-term goals 192

Different strokes for different folks 193

The right measures 194

The time to reward 195

Team vs. individual rewards 195

And finally… 196

PART IV CONCLUSIONS 197

10 Will Measurement Madness Ever Be Cured? 199

And finally… 203

References 205

Index 217

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