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E-grāmata: Data and Analytics Strategy for Business: Unlock Data Assets and Increase Innovation with a Results-Driven Data Strategy

3.95/5 (39 ratings by Goodreads)
  • Formāts: 328 pages
  • Izdošanas datums: 03-Jun-2022
  • Izdevniecība: Kogan Page Ltd
  • Valoda: eng
  • ISBN-13: 9781398606067
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  • Formāts: 328 pages
  • Izdošanas datums: 03-Jun-2022
  • Izdevniecība: Kogan Page Ltd
  • Valoda: eng
  • ISBN-13: 9781398606067
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Design and implement a results-driven data strategy with this five-stage guide to leveraging existing business assets and creating value through data projects.

For many organizations data is a by-product, but for the smarter ones it is the heartbeat of their business. Most businesses have a wealth of data buried in their systems which, if used effectively, could increase revenue, reduce costs and risk and improve customer satisfaction and employee experience.

Beginning with how to choose projects which reflect your organization's goals and how to make the business case for investing in data, this book then takes the reader through the five 'waves' of organizational data maturity. It takes the reader from getting started on the data journey with some quick wins, to how data can help your business become a leading innovator which systematically outperforms competitors.

Data and Analytics Strategy for Business outlines how to build consistent, high-quality sources of data which will create business value and explores how automation, AI and machine learning can improve performance and decision making. Filled with real-world examples and case studies, this book is a stage-by-stage guide to designing and implementing a results-driven data strategy.

Recenzijas

"In my experience taking people somewhere they've not been before requires leadership and trust, whether that's climbing Everest or making a success of your business through the use of data and analytics. In Data and Analytics Strategy for Business, Simon cuts through the jargon and provides a clear route for success." * Kenton Cool has completed 15 successful Everest summits and led Sir Ranulph Fiennes' 2008 and 2009 Expeditions. * "One of the benefits of going digital is that organizations can collect, review and analyse enormous quantities of data. Correctly interpreted, this data provides the intelligence which enables a business to understand the consumer and marketplace in a completely new way. Successful organizations require a clear data strategy and a disciplined set of operational processes. Simon Asplen-Taylor shows in practical detail how to make this happen in the real world. He demonstrates that data is key but reveals that an effective data officer never loses sight of the commercial application and human element of the intelligence created." * Kevin Gaskell, Serial entrepreneur, former MD Porsche GB, BMW GB * "Brilliant book! Genuinely the best and most readable book for existing and aspiring CDOs. Every CEO should read the first chapter. Simon Asplen-Taylor has shared his significant expertise to create the go-to data guide for business and data leaders. Data and Analytics Strategy for Business uses examples from a wide range of organizations to explain why data can revolutionise a business. A genuinely good read, the book's structure superbly guides the reader through all aspects of delivering a data and analytics strategy with vital tools and tips. Whether your organization is struggling with trust in its reports or ready to launch the bots, this book is for you." * Nina Monckton. Head of Data, Just Group PLC * "Businesses operate in an increasingly complex and fast moving environment, where making the right decision at the right time can mean the difference between winning and losing. Key to this is the successful management and use of data underpinned by a robust data strategy. Data and Analytics Strategy for Business provides a structured approach to show how you can succeed - whether you are just embarking on your journey, part way through or just fine tuning. The book is full of practical advice, anecdotes and experiences to help you win and not lose." * Carl Bates, former Senior Partner, Data & Analytics and leader of Deloittes Ventures practice. * "One of the ways we can encourage women into data leadership roles is to provide the advice and methods to help remove barriers, whilst sponsoring next generation leaders. In Data and Analytics Strategy for Business, Simon Asplen-Taylor does just that. He has shared his experiences and strategies for success, to create a level playing field for all data leaders. He also talks specifically about how to build and leverage the strengths of a diverse team." * Roisin McCarthy, Founder, Women in Data. * "As we strive to gain more value from our data assets, we create more risk, opportunity and motivation for breaches. Simon's new book Data and Analytics Strategy for Business provides amazing insight on how you can create more value in your organization's data whilst also ensuring its security! Highly recommended." * Ned Finn, CISO, Currys. * "A very interesting book in such an important and contemporary area of knowledge and skills. Data Analytics is not just an area of knowledge that you need to learn more about, but it is considered to be a crucial skill kit that is required for every business. Therefore, this book is a great addition to the intellectual body of knowledge that can help students, especially those studying post experience executive programmes, such as MBAs and DBAs, to gain clear insights of the key elements of business analytics and to acquire the required set of skills to compete in the changing world of practice." * Professor Amir Michael, Professor of Accounting & Associate Dean (MBA, DBA), Durham University Business School, UK * "The world of a Chief Data Officer requires a full understanding of how a business operates, the sector it works within and the people involved. Simon's book gives a fine insight into the approaches, decisions and specific actions a CDO can use to bring real value to your organization, and make it a critical part of your business strategy." * Helen Crooks, Chief Data Officer, Ofgem * "Beyond his remarkable expertise across all the complexities of today's data sphere, this book clearly demonstrates Simon's mastery of the art of data storytelling. Yet, what makes it even more compelling is that it is so helpfully structured in waves that align to the variety of levels across the entire data maturity spectrum - making it instantly transformative regardless of where an organization currently finds itself in its data journey. This book is an absolute essential for anyone who wants to successfully leverage the abundant value that can be derived from data and analytics." * Edosa Odaro, Chief Data & Analytics Officer at Tawuniya and Author of Making Data Work *

About the author xiv
Preface xv
Acknowledgements xvii
PART ONE How data and analytics can help you grow your business
1(72)
01 How can this book help you?
3(19)
Introduction
3(4)
CDOs hold the future of their organizations in their hands
7(1)
Task: Ten questions to ask about your business
7(12)
Are you worried?
19(1)
References
20(2)
02 The business case for data
22(11)
Introduction
23(1)
The cost of doing nothing
24(2)
The value of data is only as good as the value of your business case for it
26(2)
Identifying the most pressing data problems
28(2)
Keep it simple
30(1)
Aligning the business case with the business
31(1)
References
32(1)
03 Your data and analytics strategy
33(18)
Introduction
33(2)
What is a `data and analytics strategy'?
35(1)
Defining the CDO role
36(1)
Task: Setting priorities using the data periodic table
37(5)
Task: Using the data periodic table to design projects
42(2)
Five waves of transformation
44(3)
Value, build and improve
47(1)
Task: share the story
48(2)
References
50(1)
04 A team game
51(22)
Introduction
51(2)
Cracking the code as a CDO
53(2)
The resume problem
55(1)
Discovering problem-solvers
56(1)
Task: Recruiting for PQ and AQ
57(3)
Beware of ready-made data teams
60(1)
Diversity
61(2)
Data and analytics capability model
63(7)
References
70(3)
PART TWO Wave 1: Aspire
73(24)
05 A quick win
75(11)
Introduction
75(2)
Anatomy of a quick win
77(2)
Task: Identifying the right project
79(4)
Make sure it's a quick win for everyone
83(1)
Quick wins are not strategic wins
84(1)
References
85(1)
06 Repeat and learn
86(11)
Introduction
86(1)
Why build a repeat-and-learn culture?
87(2)
Listen to what data is telling you
89(2)
Task: Define a data process
91(1)
Task: Develop a business change process
92(1)
Learning and innovating through experimentation
93(2)
References
95(2)
PART THREE Wave 2: Mature
97(80)
07 Data governance
99(17)
Introduction
99(3)
What is data governance?
102(3)
The importance of accountability
105(2)
Data stewards, data owners and the data executive
107(4)
Task: Implementing data governance
111(4)
References
115(1)
Further reading
115(1)
08 Data quality
116(19)
Introduction
116(1)
The risks of low-quality data
117(2)
The upside of high-quality data
119(3)
The four principles of data quality
122(2)
A data quality strategy
124(1)
Task: Setting a baseline and a target
125(4)
Task: Build a data quality team
129(1)
Task: Improving data quality in the short term
130(2)
Task: Improving data quality in the long term
132(2)
References
134(1)
Further reading
134(1)
09 A single customer view
135(16)
Introduction
135(2)
What is a single customer view?
137(6)
Benefits of the SCV
143(1)
Other single views
144(2)
How do you build an SCV?
146(2)
Shadow data is the enemy of the SCV
148(1)
Ownership of the SCV
149(1)
References
150(1)
10 Reports and dashboards
151(17)
Introduction
151(1)
Task: A report audit
152(4)
From static to dynamic decision support
156(2)
Task: Designing your dashboard
158(2)
Task: Dashboard implementation
160(2)
From reporting to insight
162(1)
Task: Information architecture
163(2)
Avoiding short-termism
165(2)
References
167(1)
Further reading
167(1)
11 Data risk management and ethics
168(9)
Introduction
168(1)
Five pillars
169(5)
Task: Working with a regulator
174(2)
References
176(1)
PART FOUR Wave 3: Industrialize
177(36)
12 Automation, automation, automation
179(13)
Introduction
179(1)
What can we automate?
180(2)
How much can we automate?
182(2)
Task: The business case for automation
184(3)
Task: Manageable automation projects
187(2)
Will I use a tool?
189(2)
References
191(1)
13 Scaling up and scaling out
192(12)
Introduction
192(1)
From quick wins to big wins
193(1)
Be dull and repetitive
194(1)
Task: Choosing how and when to scale
195(2)
Use your resource multipliers
197(3)
Task: Implementing your hackathon
200(2)
The dividend from scaling
202(1)
References
203(1)
14 Optimizing
204(9)
Introduction
204(1)
Best intentions are not optimal
205(1)
Task: Plot a path to optimization
206(2)
Task: Overcoming resistance
208(1)
The limits of automation
209(1)
This is a tipping point
210(1)
References
211(2)
PART FIVE Wave 4: Realize
213(42)
15 The voice of the customer
215(17)
Introduction
215(1)
Hearing their voice
216(2)
Reasons to use other sources of data
218(1)
Understanding competitors
219(2)
Customer behaviour
221(1)
Social listening
222(1)
Task: Applying insights from social listening
223(3)
Task: Creating a reliable Net Promoter Score
226(3)
Integration
229(1)
Hear the bad news
229(1)
References
230(2)
16 Maximizing data science
232(10)
Introduction
232(1)
Data science, not data magic
233(1)
How not to do data science
234(2)
Task: Integrating data science
236(2)
Task: Sustaining data science
238(2)
Embrace the potential for failure
240(1)
References
241(1)
17 Sharing data with suppliers and customers
242(13)
Introduction
242(1)
Widespread exposure
243(1)
Exposing data to business partners and suppliers
244(2)
Blockchain in the supply chain
246(1)
Sharing improves markets
247(2)
Exposing data to customers
249(1)
Task: Prepare to share
250(2)
Exposure is inevitable, so do it your way
252(1)
References
253(2)
PART SIX Wave 5: Differentiate
255(34)
18 From data-driven to Al-driven
257(21)
Introduction
257(3)
What does AI do?
260(1)
A hierarchy of data value
261(2)
The AI journey
263(1)
Task: Detection
264(2)
Task: Process automation
266(2)
Task: Improved clustering
268(1)
Data bias
269(1)
Task: Complex analysis and prediction
270(3)
The limits of AI as a guide or manager
273(1)
Task: Creating commitment to AI for independent real-time decision-making
274(1)
From data-driven transformation to Al-driven business
275(1)
References
276(2)
19 Data products
278(8)
Introduction
278(2)
What is a data product?
280(1)
A data and analytics centre of excellence (CoE)
281(2)
Task: Creating a data CoE
283(1)
Three functions of research
284(1)
A continuous improvement life cycle
284(1)
References
285(1)
20 Right leadership, right time
286(3)
Introduction
286(1)
Leading a sustainable data culture
287(1)
Which leader are you?
288(1)
Reference
288(1)
Epilogue: Data success 289(2)
Glossary 291(7)
Abbreviations and acronyms 298(2)
Index 300
Simon Asplen-Taylor is an experienced and successful data and analytics leader based in London, UK, having served as Chief Data Officer for multiple FTSE firms and led some of the largest data led transformations in Europe. He specialises in transforming business through the use of data, analytics and artificial intelligence and is currently leading the data transformation at Lloyd's of London. He was included in the dataIQ 100 Most Influential People in Data in both 2020 and 2021.