eBook - ePub
Data Strategy
How to Profit from a World of Big Data, Analytics and Artificial Intelligence
Bernard Marr
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eBook - ePub
Data Strategy
How to Profit from a World of Big Data, Analytics and Artificial Intelligence
Bernard Marr
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About This Book
BRONZE RUNNER UP: Axiom Awards 2018 - Business Technology Category (1st edition) Data is an integral strategic asset for all businesses. Learn how to leverage this data and generate valuable insights and true business value with bestselling author and data guru Bernard Marr. Data has massive potential for all businesses when used correctly, from small organizations to tech giants and huge multinationals, but this resource is too often not fully utilized. Data Strategy is the must-read guide on how to create a robust, data-driven approach that will harness the power of data to revolutionize your business. Explaining how to collect, use and manage data, this book prepares any organization with the tools and strategies needed to thrive in the digital economy.Now in its second edition, this bestselling title is fully updated with insights on understanding your customers and markets and how to provide them with intelligent services and products. With case studies and real-world examples throughout, Bernard Marr offers unrivalled expertise on how to gain the competitive advantage in a data-driven world.
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Appendix 1
Data use case template
SOURCE Bernard Marr & Co
Figure details
1. Link to strategic goal
What is the strategic business goal that this data use case will support?
2. Objective and business questions
What is the objective of this data use case? Can you articulate any business questions this data use case will help you answer?
3. Measures of success (KPIs)
How will success be measured? What business metrics will this initiative impact? What will be the key results?
4. Use case owners
Who will be the owner or sponsor of this data use case?
5. User and data customers
Who will be the users or data customers? Who will be the consumers of the insights?
6. Required data
What data will be required? (internal slash external, new slash existing, data diversity, structure slash unstructured)
7. Data governance
What data governance, data privacy, data access, data ownership and data security challenges are there?
8. Data analysis and analytics
How will the data be turned into insights? What are the proposed analytics approaches?
9. Technology
What are the technology challenges and requirements? (data collection, data storage, data processing, data output
10. Skills and capacity
What are the challenges about skills, capabilities, capacity and resourcing? Who will deliver? (in-house slash outsourced slash hybrid
11. Implementation and change management
What are the implementation and change management challenges and requirements?
A blank box titled extra notes is given at the end.
Appendix 2
Data strategy template
SOURCE Bernard Marr & Co
Figure details
The illustration shows five strategic use cases at the top where there are three major use cases, use case 1, use case 2, use case 3 and 2 quick wins, use case 4 and use case 5. The list of cross cutting goals with examples of respective strategic use cases are:
- Data requirements
(data availability, internal slash external, new slash existing, data diversity, structured slash unstructured): for example: cross-cutting data Issue 1, for example: cross-cutting data Issue 2
- Data governance
(data quality, ethics, privacy, ownership, access and security): for example: cross-cutting data Gov. Issue 1, for example: Cross-cutting data Gov. Issue 2, for example: cross-cutting data Gov. Issue
- Technology
(data collection, data storage, data processing, data output): for example: cross-cutting technology Issue 1, for example: cross-cutting technology Issue
- Skills and capacity
(skill gaps, training requirements, insourcing, outsourcing, partnering): for example: cross-cutting skills and capacity issue 1, for example: cross-cutting skills and capacity issue 2.
- Implementation slash change management
(privacy, ownership, access and security): for example: cross-cutting data implementation and change management issue 1.
Index
3D printing 103
360-degree customer view 42, 46–48
ABB 102
ability to extract va...