Mind+Machine

A Decision Model for Optimizing and Implementing Analytics

Gebonden Engels 2016 9781119302919
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

Cut through information overload to make better decisions faster

Success relies on making the correct decisions at the appropriate time, which is only possible if the decision maker has the necessary insights in a suitable format. Mind+Machine is the guide to getting the right insights in the right format at the right time to the right person. Designed to show decision makers how to get the most out of every level of data analytics, this book explores the extraordinary potential to be found in a model where human ingenuity and skill are supported with cutting–edge tools, including automations.

The marriage of the perceptive power of the human brain with the benefits of automation is essential because mind or machine alone cannot handle the complexities of modern analytics. Only when the two come together with structure and purpose to solve a problem are goals achieved.

With various stakeholders in data analytics having their own take on what is important, it can be challenging for a business leader to create such a structure. This book provides a blueprint for decision makers, helping them ask the right questions, understand the answers, and ensure an approach to analytics that properly supports organizational growth.

Discover how to:

Harness the power of insightful minds and the speed of analytics technology
Understand the demands and claims of various analytics stakeholders
Focus on the right data and automate the right processes
·         Navigate decisions with confidence in a fast–paced world

The Mind+Machine model streamlines analytics workflows and refines the never–ending flood of incoming data into useful insights. Thus, Mind+Machine equips you to take on the big decisions and win.

Specificaties

ISBN13:9781119302919
Taal:Engels
Bindwijze:gebonden
Aantal pagina's:320

Lezersrecensies

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Inhoudsopgave

Preface xi
<p>Acknowledgments xvii</p>
<p>List of Use Cases xix</p>
<p>Part I: The Top 12 Fallacies about Mind+Machine 1</p>
<p>Fallacy #1: Big Data Solves Everything 3</p>
<p>Fallacy #2: More Data Means More Insight 17</p>
<p>Fallacy #3: First, We Need a Data Lake and Tools 26</p>
<p>Fallacy #4: Analytics Is Just an Analytics Challenge: Part I: The Last Mile 31</p>
<p>Fallacy #5: Analytics Is Just an Analytics Challenge: Part II: The Organization 36</p>
<p>Fallacy #6: Reorganizations Won t Hurt Analytics 40</p>
<p>Fallacy #7: Knowledge Management Is Easy We Just Need Some Wikis 45</p>
<p>Fallacy #8: Intelligent Machines Can Solve Any Analytic Problem 49</p>
<p>Fallacy #9: Everything Must Be Done In–House! 61</p>
<p>Fallacy #10: We Need More, Larger, and Fancier Reports 66</p>
<p>Fallacy #11: Analytics Investment Means Great ROI 72</p>
<p>Fallacy #12: Analytics Is a Rational Process 78</p>
<p>Part I: Conclusion 82</p>
<p>Part II: 13 Trends Creating Massive Opportunities for Mind+Machine 85</p>
<p>Trend #1: The Asteroid Impact of Cloud and Mobile 87</p>
<p>Trend #2: The Yin and Yang of the Internet of Things 96</p>
<p>Trend #3: One–to–One Marketing 105</p>
<p>Trend #4: Regulatory Flooding of the Ring of Knowledge 111</p>
<p>The European Union and Privacy Rules: The General Data Protection Regulation and the EU US Privacy Shield 114</p>
<p>The Teeth of the General Data Protection Regulation 115</p>
<p>Privacy Impacting the Ring of Knowledge 120</p>
<p>The Nine Questions You Need to Ask Your CIO Regarding Personal Data 121</p>
<p>Trend #5: The Seismic Shift to Pay–as–You–Go or Output–Based Commercial Models 123</p>
<p>Trend #6: The Hidden Treasures of Multiple–Client Utilities 133</p>
<p>Trend #7: The Race for Data Assets, Alternative Data, and Smart Data 136</p>
<p>Trend #8: Marketplaces and the Sharing Economy Finally Arriving in Data and Analytics 144</p>
<p>Trend #9: Knowledge Management 2.0 Still an Elusive Vision? 147</p>
<p>Trend #10: Workfl ow Platforms and Process Automation for Analytics Use Cases 156</p>
<p>Trend #11: 2015 2025: The Rise of the Mind Machine Interface 164</p>
<p>Trend #12: Agile, Agile, Agile 172</p>
<p>Trend #13: (Mind+Machine)2 = Global Partnering Equals More Than 1+1 177</p>
<p>Era 1: Pure Geographic Cost Arbitrage (2000 2005) 178</p>
<p>Era 2: Globalizing Outsourcing (2005 2015) 180</p>
<p>Era 3: Process Reengineering (2007 2015) and Specialization 184</p>
<p>Era 4: Hybrid On–Site, Near–Shore, and Far–Shore Outsourcing (2010 ) 184</p>
<p>Era 5: Mind+Machine in Outsourcing (2010 ) 185</p>
<p>Pricing and Performance Benchmarks 190</p>
<p>The Future of Outsourcing in Knowledge–Intensive Processes 194</p>
<p>Part II: Conclusion 196</p>
<p>Part III: How to Implement the Mind+Machine Approach 197</p>
<p>The Analytics Use Case Methodology: A Change in Mind–Set 198</p>
<p>Perspective #1: Focus on the Business Issue and the Client Benefits 207</p>
<p>Perspective #2: Map Out the Ring of Knowledge 214</p>
<p>Perspective #3: Choose Data Wisely Based on the Issue Tree 218</p>
<p>Perspective #4: The Effi cient Frontier Where Machines Support Minds 226</p>
<p>Perspective #5: The Right Mix of Minds Means a World of Good Options 232</p>
<p>Perspective #6: The Right Workfl ow: Flexible Platforms Embedded in the Process 241</p>
<p>Perspective #7: Serving the End Users Well: Figuring Out the Last Mile 245</p>
<p>Perspective #8: The Right User Interaction: The Art of User Experience 250</p>
<p>Perspective #9: Integrated Knowledge Management Means Speed and Savings 257</p>
<p>Perspective #10: The Commercial Model: Pay–as–You–Go or Per–Unit Pricing 264</p>
<p>Perspective #11: Intellectual Property: Knowledge Objects for Mind+Machine 266</p>
<p>Perspective #12: Create an Audit Trail and Manage Risk 269</p>
<p>Perspective #13: The Right Psychology: Getting the Minds to Work Together 271</p>
<p>Perspective #14: The Governance of Use Case Portfolios: Control and ROI 274</p>
<p>Perspective #15: Trading and Sharing Use Cases, Even across Company Boundaries 279</p>
<p>Part III: Conclusion 281</p>
<p>Notes 283</p>
<p>About the Author 287</p>
<p>Index 289</p>

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