دانلود کتاب People and Data: Uniting to Transform Your Business

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Cover
Contents
List of figures and tables
Foreword
Acknowledgements
Introduction
PART ONE The big picture
1 Ann’s data Tuesday
A day in the life
Data defined
Data everywhere
But all is not perfect!
Greasing the skids of commerce
Technology amplifies everything
Most important takeaways
Notes
2 The opportunity and the problem
The perfect storm
Regular people front and centre
Success stories confirm the potential
A yawning gap
Diagnosis
Summary
Most important takeaways
Notes
3 Building a better organization for data
Put regular people front and centre
Fat organizational pipes
Separate the management of data from the management of information technology
Eventually all change is top-down
New roles for data teams
Train to empower people and the company
Create a sea change step-by-step
Most important takeaways
Notes
PART TWO People
4 The data generation and provocateurs
Meet the data generation
Provocateurs take things further
Implications for leaders, managers and data teams
Most important takeaways
Notes
5 All roads lead through quality
When trust leaves the room
A course correction is desperately needed
Data quality is more complex than you might expect
Why data goes bad
A rush to automate
A better way
The business case for data quality
Many find this work transformational
Leadership, core data teams and embedded data managers required
Implications
Most important takeaways
Notes
6 Putting data to work
Regular people and the data science process
The big pleasures of small data
Make better decisions
Informationalize products and services
Exploit asymmetries and/or close them (finance professionals and strategists)
Exploit proprietary data (product managers, strategists)
Strategic data science (senior leaders)
Treat customer privacy as a feature (privacy professionals)
Get data on the balance sheet (finance professionals)
Explore the many other ways to put data to work
Most important takeaways
Notes
PART THREE Data is a team sport
7 Fat organizational pipes
Regular people can’t solve all problems
The suffocating effects of silos
Lack of common language also makes working together more difficult
There are a few bad actors
Do away with silos?
The customer–supplier model
Data supply chain management
The data science bridge
Establishing and maintaining common language
Change management
Most important takeaways
Notes
8 Don’t confuse apples and oranges
Great data programmes need great tech, but there are massive contradictions
Data and information technology and different sorts of assets
Information Technology departments are in tough spots
Digital transformers, transform yourselves
Most important takeaways
Notes
9 Dream big, but change the culture one project at a time
Senior management has stayed on the side-lines
Building a better organization for data
Putting data to work
Most important takeaways
Notes
10 The data teams companies need now
Clear management responsibility
Five factors guiding the design of data teams
Towards more effective data teams
Most important takeaways
Notes
Conclusion: Courage required
Resource Centre 1: Toolkit
Resource Centre 2: Curriculum for training regular people
Index