{"product_id":"minding-the-machines-isbn-9781119785323","title":"Minding the Machines","description":"\u003cp\u003e\u003cb\u003eOrganize, plan, and build an exceptional data analytics team within your organization\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn \u003ci\u003eMinding the Machines: Building and Leading Data Science and Analytics Teams\u003c\/i\u003e, AI and analytics strategy expert Jeremy Adamson delivers an accessible and insightful roadmap to structuring and leading a successful analytics team. The book explores the tasks, strategies, methods, and frameworks necessary for an organization beginning their first foray into the analytics space or one that is rebooting its team for the umpteenth time in search of success.\u003c\/p\u003e \u003cp\u003eIn this book, you’ll discover:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eA focus on the three pillars of strategy, process, and people and their role in the iterative and ongoing effort of building an analytics team\u003c\/li\u003e \u003cli\u003eRepeated emphasis on three guiding principles followed by successful analytics teams: start early, go slow, and fully commit\u003c\/li\u003e \u003cli\u003eThe importance of creating clear goals and objectives when creating a new analytics unit in an organization\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for executives, managers, team leads, and other business leaders tasked with structuring and leading a successful analytics team, \u003ci\u003eMinding the Machines\u003c\/i\u003e is also an indispensable resource for data scientists and analysts who seek to better understand how their individual efforts fit into their team’s overall results.\u003c\/p\u003e \u003cp\u003eForeword xiii\u003c\/p\u003e \u003cp\u003eIntroduction xvi\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Prologue 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eFor the Leader from the Business 5\u003c\/p\u003e \u003cp\u003eFor the Career Transitioner 6\u003c\/p\u003e \u003cp\u003eFor the Motivated Practitioner 6\u003c\/p\u003e \u003cp\u003eFor the Student 7\u003c\/p\u003e \u003cp\u003eFor the Analytics Leader 8\u003c\/p\u003e \u003cp\u003eStructure of This Book 8\u003c\/p\u003e \u003cp\u003eWhy is This Book Needed? 9\u003c\/p\u003e \u003cp\u003eCommunication Gap 9\u003c\/p\u003e \u003cp\u003eTroubles with Taylorism 10\u003c\/p\u003e \u003cp\u003eRinse, Report, Repeat 12\u003c\/p\u003e \u003cp\u003eToo Fast, Too Slow 13\u003c\/p\u003e \u003cp\u003eMore Data, More Problems 14\u003c\/p\u003e \u003cp\u003eSummary 15\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Strategy 17\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Role of Analytics in the Organization 20\u003c\/p\u003e \u003cp\u003eThe Analytics Playbook 20\u003c\/p\u003e \u003cp\u003eData and Analytics as a Culture Change 24\u003c\/p\u003e \u003cp\u003eCurrent State Assessment 26\u003c\/p\u003e \u003cp\u003eReadiness Assessment 26\u003c\/p\u003e \u003cp\u003eCapability Modeling and Mapping 28\u003c\/p\u003e \u003cp\u003eTechnology Stack Review 32\u003c\/p\u003e \u003cp\u003eData Quality and Governance 34\u003c\/p\u003e \u003cp\u003eStakeholder Engagement 35\u003c\/p\u003e \u003cp\u003eDefining the Future State 37\u003c\/p\u003e \u003cp\u003eDefining the Mandate 39\u003c\/p\u003e \u003cp\u003eAnalytics Governance Model 40\u003c\/p\u003e \u003cp\u003eTarget Operating Model 42\u003c\/p\u003e \u003cp\u003eDefine Your Principles 43\u003c\/p\u003e \u003cp\u003eFunctions, Services, and Capabilities 43\u003c\/p\u003e \u003cp\u003eInteraction Models 44\u003c\/p\u003e \u003cp\u003eOrganizational Design 48\u003c\/p\u003e \u003cp\u003eCommunity of Practice 52\u003c\/p\u003e \u003cp\u003eProject Delivery Model 55\u003c\/p\u003e \u003cp\u003eClosing the Gap 57\u003c\/p\u003e \u003cp\u003eSetting the Horizon 58\u003c\/p\u003e \u003cp\u003eEstablishing a Talent Roadmap 59\u003c\/p\u003e \u003cp\u003eConsultants and Contractors 60\u003c\/p\u003e \u003cp\u003eChange Management 62\u003c\/p\u003e \u003cp\u003eImplementing Governance Models 64\u003c\/p\u003e \u003cp\u003eSummary 65\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Process 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eProject Planning 73\u003c\/p\u003e \u003cp\u003eIntake and Prioritization 73\u003c\/p\u003e \u003cp\u003eProject Pipelines 77\u003c\/p\u003e \u003cp\u003ePortfolio Project Management 80\u003c\/p\u003e \u003cp\u003eProject Scoping and Planning 83\u003c\/p\u003e \u003cp\u003eScoping and Requirements Definition 86\u003c\/p\u003e \u003cp\u003ePlanning 92\u003c\/p\u003e \u003cp\u003eProject Execution 96\u003c\/p\u003e \u003cp\u003eGovernance Structure and Communication Plan 99\u003c\/p\u003e \u003cp\u003eProject Kickoff 102\u003c\/p\u003e \u003cp\u003eAgile Analytics 103\u003c\/p\u003e \u003cp\u003eChange and Stakeholder Management 106\u003c\/p\u003e \u003cp\u003eSkeuomorphs 106\u003c\/p\u003e \u003cp\u003eAI 101 and Project Brainstorming 107\u003c\/p\u003e \u003cp\u003eIterative Insights 110\u003c\/p\u003e \u003cp\u003eCloseout and Delivery 111\u003c\/p\u003e \u003cp\u003eAutomation 112\u003c\/p\u003e \u003cp\u003eProject Debrief 114\u003c\/p\u003e \u003cp\u003eSummary 118\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 People 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBuilding the Team 122\u003c\/p\u003e \u003cp\u003eSuccess Factors 123\u003c\/p\u003e \u003cp\u003eTeam Composition 128\u003c\/p\u003e \u003cp\u003eHiring and Onboarding 129\u003c\/p\u003e \u003cp\u003eTalent Development 131\u003c\/p\u003e \u003cp\u003eRetention 136\u003c\/p\u003e \u003cp\u003eDepartures 137\u003c\/p\u003e \u003cp\u003eThe Data Scientist Hierarchy of Needs 139\u003c\/p\u003e \u003cp\u003eCulture 140\u003c\/p\u003e \u003cp\u003eInnovation 145\u003c\/p\u003e \u003cp\u003eCommunication 147\u003c\/p\u003e \u003cp\u003eSuccession Planning 149\u003c\/p\u003e \u003cp\u003ePotential Pitfalls 151\u003c\/p\u003e \u003cp\u003eDunning-Kruger Effect 152\u003c\/p\u003e \u003cp\u003eDiderot Effect 153\u003c\/p\u003e \u003cp\u003eLeading the Team 154\u003c\/p\u003e \u003cp\u003eData Scientists as Craftspeople 157\u003c\/p\u003e \u003cp\u003eTeam Conventions 160\u003c\/p\u003e \u003cp\u003eFormal Meetings 162\u003c\/p\u003e \u003cp\u003eCoffee Chats 164\u003c\/p\u003e \u003cp\u003eManaging Conflict 167\u003c\/p\u003e \u003cp\u003eRelationship Management 169\u003c\/p\u003e \u003cp\u003eOwning the Narrative 175\u003c\/p\u003e \u003cp\u003ePerformance Metrics 177\u003c\/p\u003e \u003cp\u003eSummary 181\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Future of Business Analytics 187\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAutoML and the No‐Code Movement 189\u003c\/p\u003e \u003cp\u003eData Science is Dead 192\u003c\/p\u003e \u003cp\u003eThe Data Warehouse 195\u003c\/p\u003e \u003cp\u003eTrue Operationalization 196\u003c\/p\u003e \u003cp\u003eExogenous Data 198\u003c\/p\u003e \u003cp\u003eEdge AI 199\u003c\/p\u003e \u003cp\u003eAnalytics for Good 200\u003c\/p\u003e \u003cp\u003eAnalytics for Evil 201\u003c\/p\u003e \u003cp\u003eEthics and Bias 203\u003c\/p\u003e \u003cp\u003eAnalytics Talent Shortages 204\u003c\/p\u003e \u003cp\u003eDeath of the Career Transitioner 206\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Summary 211\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Coda 213\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIndex 215\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eJeremy Adamson\u003c\/b\u003e is a leader in AI and analytics strategy across industries. Jeremy has worked with major organizations to establish leadership positions in data science and to unlock real business value using advanced analytics. He holds an MBA from the University of Calgary and is a professional engineer in the province of Alberta.   \u003c\/p\u003e\u003cp\u003eMake data science part of the lifeblood of your business, and avoid costly missteps \u003c\/p\u003e\u003cp\u003eBy now, almost every organization has stepped into the world of big data analytics—and some of us have already tried again and again to get it right. We know that data science has the potential to unlock tremendous value, so why is it so hard to get it right? In \u003ci\u003eMinding the Machines\u003c\/i\u003e, analytics strategy expert Jeremy Adamson explains that the problem is often one of too many cooks in the kitchen, and too few recipes for success. This book shows you how to blend data science with business acumen.  \u003c\/p\u003e\u003cp\u003eInside, you’ll find a roadmap for internalizing the three pillars of analytics: strategy, process, and people. Create an analytics operation that can truly transform outcomes.  \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eInstall the right leaders and position your analytics unit within your organization\u003c\/li\u003e \u003cli\u003eIntegrate analytics insights into the business in a constructive and meaningful way\u003c\/li\u003e \u003cli\u003eIdentify and fully commit to projects that will add value over the long term\u003c\/li\u003e \u003cli\u003eHire the right people and get them working for the organization as a whole\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003eAnyone who aspires to be part of a world-class analytics team will benefit from the tasks, methods, and frameworks clearly presented in this valuable book.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003e“For leaders craving a playbook that puts together all the key elements required for building a high performing Advanced Analytics \u0026amp; AI function in a comprehensive but down to earth manner, this book is most definitely a must read.”\u003c\/b\u003e\u003c\/i\u003e\u003cbr\u003e \u003cb\u003e— Celia Wanderley,\u003c\/b\u003e Chief Customer Officer and Head of Services at AltaML \u003c\/p\u003e\u003cp\u003e\u003cb\u003e“…\u003ci\u003e with detailed explanations and checklists throughout, anyone looking to grow an analytics and data science organization can find support within the book.”\u003c\/i\u003e\u003c\/b\u003e\u003cbr\u003e \u003cb\u003e— Bill Franks,\u003c\/b\u003e author of \u003ci\u003eThe Analytics Revolution\u003c\/i\u003e, and Director, Center for Statistics and Analytical Research, Kennesaw State University \u003c\/p\u003e\u003cp\u003e\u003ci\u003e\u003cb\u003e“ … a valuable resource for all parties as they advance the role of analytics, and being digital, in their organization… ”\u003c\/b\u003e\u003c\/i\u003e\u003cbr\u003e \u003cb\u003e— Lee Ackerman,\u003c\/b\u003e Director of Digital Strategy, SAIT’s School for Advanced Digital Technology\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989629747429,"sku":"NP9781119785323","price":40.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119785323.jpg?v=1761784877","url":"https:\/\/k12savings.com\/products\/minding-the-machines-isbn-9781119785323","provider":"K12savings","version":"1.0","type":"link"}