{"product_id":"monetizing-your-data-isbn-9781119356240","title":"Monetizing Your Data","description":"\u003cb\u003eTransforming data into revenue generating strategies and actions\u003c\/b\u003e \u003cp\u003eOrganizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more\u003ci\u003e,\u003c\/i\u003e but what to do with it? \u003ci\u003eMonetizing your Data\u003c\/i\u003e provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way.\u003c\/p\u003e \u003cp\u003eThis book shows you how to use your data to:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eMonetize your data to drive revenue and cut costs\u003c\/li\u003e \u003cli\u003eConnect your data to decisions that drive action and deliver value\u003c\/li\u003e \u003cli\u003eDevelop analytic tools to guide managers up and down the ladder to better decisions\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eTurning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; \u003ci\u003eMonetizing your Data\u003c\/i\u003e walks you through the translation and transformation to help you leverage your data into value creating strategies.\u003c\/p\u003e \u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgments xvii\u003c\/p\u003e \u003cp\u003eAbout the Authors xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection I Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Introduction 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecisions 4\u003c\/p\u003e \u003cp\u003eAnalytical Journey 7\u003c\/p\u003e \u003cp\u003eSolving the Problem 8\u003c\/p\u003e \u003cp\u003eThe Survey Says… 9\u003c\/p\u003e \u003cp\u003eHow to Use This Book 12\u003c\/p\u003e \u003cp\u003eLet’s Start 15\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Analytical Cycle: Driving Quality Decisions 16\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAnalytical Cycle Overview 17\u003c\/p\u003e \u003cp\u003eHierarchy of Information User 28\u003c\/p\u003e \u003cp\u003eNext Steps 30\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Decision Architecture Methodology: Closing the Gap 31\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMethodology Overview 32\u003c\/p\u003e \u003cp\u003eDiscovery 36\u003c\/p\u003e \u003cp\u003eDecision Analysis 38\u003c\/p\u003e \u003cp\u003eMonetization Strategy 40\u003c\/p\u003e \u003cp\u003eAgile Analytics 41\u003c\/p\u003e \u003cp\u003eEnablement 46\u003c\/p\u003e \u003cp\u003eSummary 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection II Decision Analysis 51\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Decision Analysis: Architecting Decisions 53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCategory Tree 54\u003c\/p\u003e \u003cp\u003eQuestion Analysis 57\u003c\/p\u003e \u003cp\u003eKey Decisions 61\u003c\/p\u003e \u003cp\u003eData Needs 64\u003c\/p\u003e \u003cp\u003eAction Levers 67\u003c\/p\u003e \u003cp\u003eSuccess Metrics 68\u003c\/p\u003e \u003cp\u003eCategory Tree Revisited 71\u003c\/p\u003e \u003cp\u003eSummary 74\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection III Monetization Strategy 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Monetization Strategy: Making Data Pay 79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBusiness Levers 81\u003c\/p\u003e \u003cp\u003eMonetization Strategy Framework 84\u003c\/p\u003e \u003cp\u003eDecision Analysis and Agile Analytics 85\u003c\/p\u003e \u003cp\u003eCompetitive and Market Information 95\u003c\/p\u003e \u003cp\u003eSummary 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 Monetization Guiding Principles: Making It Solid 98\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eQuality Data 99\u003c\/p\u003e \u003cp\u003eBe Specific 102\u003c\/p\u003e \u003cp\u003eBe Holistic 103\u003c\/p\u003e \u003cp\u003eActionable 104\u003c\/p\u003e \u003cp\u003eDecision Matrix 106\u003c\/p\u003e \u003cp\u003eGrounded in Data Science 107\u003c\/p\u003e \u003cp\u003eMonetary Value 108\u003c\/p\u003e \u003cp\u003eConfidence Factor 109\u003c\/p\u003e \u003cp\u003eMeasurable 111\u003c\/p\u003e \u003cp\u003eMotivation 112\u003c\/p\u003e \u003cp\u003eOrganizational Culture 113\u003c\/p\u003e \u003cp\u003eDrives Innovation 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Product Profitability Monetization Strategy: A Case Study 115\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBackground 115\u003c\/p\u003e \u003cp\u003eBusiness Levers 117\u003c\/p\u003e \u003cp\u003eDiscovery 117\u003c\/p\u003e \u003cp\u003eDecide 118\u003c\/p\u003e \u003cp\u003eData Science 125\u003c\/p\u003e \u003cp\u003eMonetization Framework Requirements 125\u003c\/p\u003e \u003cp\u003eDecision Matrix 128\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection IV Agile Analytics 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Decision Theory: Making It Rational 133\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDecision Matrix 134\u003c\/p\u003e \u003cp\u003eProbability 136\u003c\/p\u003e \u003cp\u003eProspect Theory 139\u003c\/p\u003e \u003cp\u003eChoice Architecture 140\u003c\/p\u003e \u003cp\u003eCognitive Bias 141\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Data Science: Making It Smart 145\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMetrics 146\u003c\/p\u003e \u003cp\u003eThresholds 149\u003c\/p\u003e \u003cp\u003eTrends and Forecasting 150\u003c\/p\u003e \u003cp\u003eCorrelation Analysis 151\u003c\/p\u003e \u003cp\u003eSegmentation 154\u003c\/p\u003e \u003cp\u003eCluster Analysis 156\u003c\/p\u003e \u003cp\u003eVelocity 160\u003c\/p\u003e \u003cp\u003ePredictive and Explanatory Models 161\u003c\/p\u003e \u003cp\u003eMachine Learning 162\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Data Development: Making It Organized 164\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eData Quality 164\u003c\/p\u003e \u003cp\u003eDirty Data, Now What? 169\u003c\/p\u003e \u003cp\u003eData Types 170\u003c\/p\u003e \u003cp\u003eData Organization 172\u003c\/p\u003e \u003cp\u003eData Transformation 176\u003c\/p\u003e \u003cp\u003eSummary 180\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Guided Analytics: Making It Relevant 181\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSo, What? 181\u003c\/p\u003e \u003cp\u003eGuided Analytics 184\u003c\/p\u003e \u003cp\u003eSummary 196\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 User Interface (UI): Making It Clear 197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction to UI 197\u003c\/p\u003e \u003cp\u003eThe Visual Palette 198\u003c\/p\u003e \u003cp\u003eLess Is More 199\u003c\/p\u003e \u003cp\u003eWith Just One Look 206\u003c\/p\u003e \u003cp\u003eGestalt Principles of Pattern Perception 209\u003c\/p\u003e \u003cp\u003ePutting It All Together 212\u003c\/p\u003e \u003cp\u003eSummary 220\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 User Experience (UX): Making It Work 221\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003ePerformance Load 221\u003c\/p\u003e \u003cp\u003eGo with the Flow 225\u003c\/p\u003e \u003cp\u003eModularity 228\u003c\/p\u003e \u003cp\u003ePropositional Density 229\u003c\/p\u003e \u003cp\u003eSimplicity on the Other Side of Complexity 231\u003c\/p\u003e \u003cp\u003eSummary 232\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection V Enablement 233\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Agile Approach: Getting Agile 235\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAgile Development 235\u003c\/p\u003e \u003cp\u003eRiding the Wave 236\u003c\/p\u003e \u003cp\u003eAgile Analytics 237\u003c\/p\u003e \u003cp\u003eSummary 241\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 Enablement: Gaining Adoption 242\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTesting 242\u003c\/p\u003e \u003cp\u003eAdoption 245\u003c\/p\u003e \u003cp\u003eSummary 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 Analytical Organization: Getting Organized\u003c\/b\u003e 251\u003c\/p\u003e \u003cp\u003eDecision Architecture Team 251\u003c\/p\u003e \u003cp\u003eDecision Architecture Roles 259\u003c\/p\u003e \u003cp\u003eSubject Matter Experts 261\u003c\/p\u003e \u003cp\u003eAnalytical Organization Mindset 262\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection VI Case Study 265\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCase Study Michael Andrews Bespoke 267\u003c\/p\u003e \u003cp\u003eDiscovery 267\u003c\/p\u003e \u003cp\u003eDecision Analysis Phase 278\u003c\/p\u003e \u003cp\u003eMonetization Strategy, Part I 286\u003c\/p\u003e \u003cp\u003eAgile Analytics 287\u003c\/p\u003e \u003cp\u003eMonetization Strategy, Part II 303\u003c\/p\u003e \u003cp\u003eGuided Analytics 313\u003c\/p\u003e \u003cp\u003eClosing 324\u003c\/p\u003e \u003cp\u003eBibliography 327\u003c\/p\u003e \u003cp\u003eIndex 331\u003c\/p\u003e \u003cp\u003e\u003cb\u003eANDREW ROMAN WELLS\u003c\/b\u003e is the CEO of Aspirent, a management consulting firm focused on analytics. He has extensive experience building analytical solutions for a wide range of companies, from Fortune 500s to small non-profits. Mr. Wells focuses on helping organizations utilize their data to make impactful decisions that drive revenue through monetization strategies. He has been building analytical solutions for over 25 years and is excited to share these practical methods, tools, and techniques with a wider audience. Mr. Wells earned a Bachelor’s degree in Business Administration with a focus on Finance and Management Information Systems from the University of Georgia.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eKATHY WILLIAMS CHIANG\u003c\/b\u003e is an established business analytics practitioner with expertise in guided analytics, analytic data mart development, and business planning. Prior to her current position as vice president of business insights at Wunderman Data Management, Ms. Chiang consulted with Aspirent on numerous analytic projects for several multinational clients including IHG and Coca Cola, among others. She has also worked for multinational corporations including Telecommunications Systems of Trinidad and Tobago, Acuity Brands Lighting, BellSouth International, and Portman Overseas. Ms. Chiang is experienced in designing and developing analytic tools and management dashboards that inform, matter, and drive action. She is highly skilled in data exploration, analysis, visualization, and presentation, and has developed solutions in the telecom, hospitality, and consumer products industries covering customer experience, marketing campaigns, revenue management, and web analytics. Ms. Chiang, a native of New Orleans, holds a Bachelor of Science degree in Chemistry, summa cum laude with University honors (4.0), from Louisiana State University, as well as an MBA from Tulane University. She is a member of Phi Beta Kappa and Mensa.  \u003c\/p\u003e\u003cp\u003eIf your organization is like most, it’s sitting atop a mountain of data—data collected from web traffic, point of sale systems, enterprise resource planning systems, social data, and other sources. But what good is it all? Short answer: There are diamonds and gold for those who know how to unearth them. \u003c\/p\u003e \u003cp\u003eData assets in most organizations are an under-utilized gold mine of information, just begging to be transformed into actionable revenue-generating strategies—which, in today’s hyper-competitive, global marketplace, not only can give you a significant competitive edge, but also become a non-stop source of profit. And as experts Andrew Wells and Kathy Chiang demonstrate in this hands-on guide, digging it out is easier than you may think.  \u003c\/p\u003e\u003cp\u003e\u003ci\u003eMonetizing Your Data\u003c\/i\u003e provides a framework and a proven formula for converting your company’s ever-growing mountain of data into revenue-generating actions using three disciplines: decision architecture, data science, and guided analytics.  \u003c\/p\u003e\u003cp\u003eThere are big gaps between recognizing a business problem and knowing which data can be useful in solving it or how to leverage it to drive financial performance. Drawing on their extensive experience delivering solutions to companies around the world, Andrew and Kathy arm you with a complete system and powerful analytical tools for transforming data you already have into insights that drive winning strategies.  \u003c\/p\u003e\u003cp\u003eFollowing a brief explanation of the analytical cycle, they cut to the chase with clear, step-by-step guidance on how to develop value-generating ideas that translate into big returns. With the help of real-world examples, templates, checklists, and a companion website, they show you how to put their system to work in your organization, right away.  \u003c\/p\u003e\u003cp\u003eYour data can be a priceless resource, but only if you know how to unearth the nuggets of actionable intelligence buried within it. Whether you work in a large multinational or a small, single-owner shop, your enterprise can garner substantial rewards by using the methods, tools, and techniques you’ll discover in \u003ci\u003eMonetizing Your Data.\u003c\/i\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989651112165,"sku":"NP9781119356240","price":49.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119356240.jpg?v=1761784962","url":"https:\/\/k12savings.com\/products\/monetizing-your-data-isbn-9781119356240","provider":"K12savings","version":"1.0","type":"link"}