Applied Business Analytics

Integrating Business Process, Big Data, and Advanced Analytics
Author: Nathaniel Lin
Publisher: FT Press
ISBN: 0133481530
Category: Business & Economics
Page: 288
View: 6889

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Bridge the gap between analytics and execution, and actually translate analytics into better business decision-making! Now that you've collected data and crunched numbers, Applied Business Analytics reveals how to fully apply the information and knowledge you've gleaned from quants and tech teams. Nathaniel Lin explains why "analytics value chains" often break due to organizational and cultural issues, and offers "in the trenches" guidance for overcoming these obstacles. You'll discover why a special breed of "analytics deciders" is indispensable for any organization that seeks to compete on analytics… how to become one of those deciders… and how to identify, foster, support, empower, and reward others to join you. Lin draws on actual cases and examples from his own experience, augmenting them with hands-on examples and exercises to integrate analytics at all levels: from top-level business questions to low-level technical details. Along the way, you'll learn how to bring together analytics team members with widely diverse goals, knowledge, and backgrounds. Coverage includes: How analytical and conventional decision making differ — and the challenging implications How to determine who your analytics deciders are, and ought to be Proven best practices for actually applying analytics to decision-making How to optimize your use of analytics as an analyst, manager, executive, or C-level officer Applied Business Analytics will be invaluable to wide audiences of professionals, decision-makers, and consultants involved in analytics, including Chief Analytics Officers, Chief Data Officers, Chief Scientists, Chief Marketing Officers, Chief Risk Officers, Chief Strategy Officers, VPs of Analytics and/or Big Data, data scientists, business strategists, and line of business executives. It will also be exceptionally useful to students of analytics in any graduate, undergraduate, or certificate program, including candidates for INFORMS certification.

Computational Intelligence in Business Analytics

Concepts, Methods, and Tools for Big Data Applications
Author: Les Sztandera
Publisher: FT Press
ISBN: 0133552136
Category: Computers
Page: 128
View: 1026

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Use computational intelligence to drive more value from business analytics, overcome real-world uncertainties and complexities, and make better decisions. Drawing on his pioneering experience as an instructor and researcher, Dr. Les Sztandera thoroughly illuminates today's key computational intelligence tools, knowledge, and strategies for analysis, exploration, and knowledge generation. Sztandera demystifies artificial neural networks, genetic algorithms, and fuzzy systems, and guides you through using them to model, discover, and interpret new patterns that can't be found through statistical methods alone. Packed with relevant case studies and examples, this guide demonstrates: Customer segmentation for direct marketing Customer profiling for relationship management Efficient mailing campaigns Customer retention Identification of cross-selling opportunities Credit score analysis Detection of fraudulent behavior and transactions Hedge fund strategies, and more Szandera shows how computational intelligence can inform the design and integration of services, architecture, brand identity, and product portfolio across the entire enterprise. He also shows how to complement computational intelligence with visualization, explorative interfaces and advanced reporting, thereby empowering business users and enterprise stakeholders to take full advantage of it. For analytics professionals, managers, and students.

Real-world Data Mining

Applied Business Analytics and Decision Making
Author: Dursun Delen
Publisher: Pearson Education
ISBN: 0133551075
Category: Business & Economics
Page: 273
View: 4277

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Includes bibliographical references and index.

Modern Analytics Methodologies

Driving Business Value with Analytics
Author: Michele Chambers,Thomas W Dinsmore
Publisher: Pearson Education
ISBN: 0133498832
Category: Computers
Page: 272
View: 2414

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Create a complete roadmap for capitalizing on analytics to grow topline revenue and build shareholder value in your unique organization! Modern Analytics Methodologies goes far beyond the classic Analytics Maturity Model to help you overcome the gaps between your current analytics capabilities and where you need to go. Pioneering analytics experts Michele Chambers and Thomas Dinsmore help you implement analytics that supports your strategy, aligns with your culture, and serves your customers and stakeholders. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. Writing for both professionals and students, they show how to: Leverage the convergence of macro trends ranging from "flattening" and "green" to Big Data and machine learning Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies Modern Analytics Methodologies will be an indispensable resource for any executive or professional concerned with analytics, including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and line-of-business executives.

Building a Digital Analytics Organization

Create Value by Integrating Analytical Processes, Technology, and People into Business Operations
Author: Judah Phillips
Publisher: FT Press
ISBN: 0133372812
Category: Computers
Page: 280
View: 5658

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Drive maximum business value from digital analytics, web analytics, site analytics, and business intelligence! In Building a Digital Analytics Organization, pioneering expert Judah Phillips thoroughly explains digital analytics to business practitioners, and presents best practices for using it to reduce costs and increase profitable revenue throughout the business. Phillips covers everything from making the business case through defining and executing strategy, and shows how to successfully integrate analytical processes, technology, and people in all aspects of operations. This unbiased and product-independent guide is replete with examples, many based on the author’s own extensive experience. Coverage includes: key concepts; focusing initiatives and strategy on business value, not technology; building an effective analytics organization; choosing the right tools (and understanding their limitations); creating processes and managing data; analyzing paid, owned, and earned digital media; performing competitive and qualitative analyses; optimizing and testing sites; implementing integrated multichannel digital analytics; targeting consumers; automating marketing processes; and preparing for the revolutionary “analytical economy.” For all business practitioners interested in analytics and business intelligence in all areas of the organization.

Enterprise Analytics

Optimize Performance, Process, and Decisions Through Big Data
Author: Thomas H. Davenport
Publisher: Pearson Education
ISBN: 0133039439
Category: Business & Economics
Page: 268
View: 7306

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"International Institute for Analytics"--Dust jacket.

Applying Advanced Analytics to HR Management Decisions

Methods for Selection, Developing Incentives, and Improving Collaboration
Author: James C. Sesil
Publisher: Pearson Education
ISBN: 0133064603
Category: Business & Economics
Page: 156
View: 1136

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Dramatically improve human capital management decisions by applying advanced analytics and "Big Data" technologies and processes! Pioneering HR technology expert James Sesil identifies widespread flaws in today's HR decision-making processes, and reveals how advanced analytics can help organizations make far more robust decisions about employee selection, performance management, strategy alignment, collaboration, and more. In this book he shows how to integrate Business Intelligence, ERP, Strategy Maps, Talent Management Suites, and advanced analytics -- and use them together to make far better decisions. You'll learn how to measure and improve the value of HCM decision-making in workforce/succession planning, talent acquisition, career development, corporate learning, and beyond. Sesil teaches key lessons from sources ranging from online dating services to Moneyball-style sports player selection processes. He shows how to systematically improve decision-making through more complete and sophisticated collaboration and new Collective Intelligence approaches. You'll learn how to use both internal and external data sources more effectively, and review a wide variety of advanced tools now available from vendors such as OrcaEyes, Vemo, Aruspex, Peoplefluent, Infor/Lawson, DecisionLens, Oracle, Ultimate, Cogniti, IBM, SAP, and Microsoft. Sesil concludes by demonstrating how to build "data driven" cultures and organizations that truly want to bring objectivity to decision-making, and will actually use these remarkable new tools. This book will be an invaluable resource for every HR executive, manager, analyst, and IT professional seeking new opportunities for competitive advantage through human capital and technological innovation.

Applied Insurance Analytics

A Framework for Driving More Value from Data Assets, Technologies, and Tools
Author: Patricia L Saporito
Publisher: FT Press
ISBN: 0133760731
Category: Computers
Page: 208
View: 5176

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Insurers: use analytics to drive far more value from your most important asset -- data! Today, many insurers radically underutilize their data, leaving them vulnerable to traditional and non-traditional competitors alike. Now, drawing on 25 years of industry experience, Patricia Saporito shows how to systematically leverage analytics to improve business performance and customer satisfaction throughout any insurance business. Applied Insurance Analytics demonstrates how to use analytics to systematically improve operations ranging from underwriting and risk management to claims. Even more important: it will help you drive more value everywhere by defining a focused enterprise-wide analytics strategy, and overcoming the challenges that stand in your way. Saporito helps you assess your current analytics maturity, choose the new applications that offer the most value, and master best practices from throughout the industry and beyond. Throughout, she helps you gain more value from data assets, technologies and tools you've already invested in. You'll find new case studies, practical tools, and easy templates for improving the "Analytics IQ" of your entire enterprise. For every insurance industry professional and manager concerned with analytics, including users, IT pros, sales/marketing specialists, and data scientists. This book will also be valuable to students in any MBA or other program focused on insurance or risk management, and to many students in IT or analytics-specific programs.

The Analytics Process

Strategic and Tactical Steps
Author: Eduardo Rodriguez
Publisher: CRC Press
ISBN: 1351975633
Category: Computers
Page: 256
View: 8139

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This book is about the process of using analytics and the capabilities of analytics in today’s organizations. Cutting through the buzz surrounding the term analytics and the overloaded expectations about using analytics, the book demystifies analytics with an in-depth examination of concepts grounded in operations research and management science. Analytics as a set of tools and processes is only as effective as: The data with which it is working The human judgment applying the processes and understanding the output of these processes. For this reason, the book focuses on the analytics process. What is intrinsic to analytics’ real organizational impact are the careful application of tools and the thoughtful application of their outcomes. This work emphasizes analytics as part of a process that supports decision-making within organizations. It wants to debunk overblown expectations that somehow analytics outputs or analytics as applied to other concepts, such as Big Data, are the be-all and end-all of the analytics process. They are, instead, only a step within a holistic and critical approach to management thinking that can create real value for an organization. To develop this holistic approach, the book is divided into two sections that examine concepts and applications. The first section makes the case for executive management taking a holistic approach to analytics. It draws on rich research in operations and management science that form the context in which analytics tools are to be applied. There is a strong emphasis on knowledge management concepts and techniques, as well as risk management concepts and techniques. The second section focuses on both the use of the analytics process and organizational issues that are required to make the analytics process relevant and impactful.

Big Data Driven Supply Chain Management

A Framework for Implementing Analytics and Turning Information Into Intelligence
Author: Nada R. Sanders
Publisher: Pearson Education
ISBN: 0133762823
Category: Business & Economics
Page: 272
View: 554

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Master a complete, five-step roadmap for leveraging Big Data and analytics to gain unprecedented competitive advantage from your supply chain. Using Big Data, pioneers such as Amazon, UPS, and Wal-Mart are gaining unprecedented mastery over their supply chains. They are achieving greater visibility into inventory levels, order fulfillment rates, material and product delivery… using predictive data analytics to match supply with demand; leveraging new planning strengths to optimize their sales channel strategies; optimizing supply chain strategy and competitive priorities; even launching powerful new ventures. Despite these opportunities, many supply chain operations are gaining limited or no value from Big Data. In Big Data Driven Supply Chain Management, Nada Sanders presents a systematic five-step framework for using Big Data in supply chains. You'll learn best practices for segmenting and analyzing customers, defining competitive priorities for each segment, aligning functions behind strategy, dissolving organizational boundaries to sense demand and make better decisions, and choose the right metrics to support all of this. Using these techniques, you can overcome the widespread obstacles to making the most of Big Data in your supply chain — and earn big profits from the data you're already generating. For all executives, managers, and analysts interested in using Big Data technologies to improve supply chain performance.

Marketing Data Science

Modeling Techniques in Predictive Analytics with R and Python
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133887340
Category: Business & Economics
Page: 225
View: 9037

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Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analytics. Writing for both managers and students, Thomas W. Miller explains essential concepts, principles, and theory in the context of real-world applications. Building on Miller's pioneering program, Marketing Data Science thoroughly addresses segmentation, target marketing, brand and product positioning, new product development, choice modeling, recommender systems, pricing research, retail site selection, demand estimation, sales forecasting, customer retention, and lifetime value analysis. Starting where Miller's widely-praised Modeling Techniques in Predictive Analytics left off, he integrates crucial information and insights that were previously segregated in texts on web analytics, network science, information technology, and programming. Coverage includes: The role of analytics in delivering effective messages on the web Understanding the web by understanding its hidden structures Being recognized on the web – and watching your own competitors Visualizing networks and understanding communities within them Measuring sentiment and making recommendations Leveraging key data science methods: databases/data preparation, classical/Bayesian statistics, regression/classification, machine learning, and text analytics Six complete case studies address exceptionally relevant issues such as: separating legitimate email from spam; identifying legally-relevant information for lawsuit discovery; gleaning insights from anonymous web surfing data, and more. This text's extensive set of web and network problems draw on rich public-domain data sources; many are accompanied by solutions in Python and/or R. Marketing Data Science will be an invaluable resource for all students, faculty, and professional marketers who want to use business analytics to improve marketing performance.

Modeling Techniques in Predictive Analytics

Business Problems and Solutions with R
Author: Thomas W. Miller
Publisher: FT Press
ISBN: 0133412954
Category: Computers
Page: 348
View: 750

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Today, successful firms compete and win based on analytics. Modeling Techniques in Predictive Analytics brings together all the concepts, techniques, and R code you need to excel in any role involving analytics. Thomas W. Miller’s unique balanced approach combines business context and quantitative tools, appealing to managers, analysts, programmers, and students alike. Miller addresses multiple business challenges and business cases, including segmentation, brand positioning, product choice modeling, pricing research, finance, sports, text analytics, sentiment analysis, and social network analysis. He illuminates the use of cross-sectional data, time series, spatial, and even spatio-temporal data. For each problem, Miller explains why the problem matters, what data is relevant, how to explore your data once you’ve identified it, and then how to successfully model that data. You’ll learn how to model data conceptually, with words and figures; and then how to model it with realistic R programs that deliver actionable insights and knowledge. Miller walks you through model construction, explanatory variable subset selection, and validation, demonstrating best practices for improving out-of-sample predictive performance. He employs data visualization and statistical graphics in exploring data, presenting models, and evaluating performance. All example code is presented in R, today’s #1 system for applied statistics, statistical research, and predictive modeling; code is set apart from other text so it’s easy to find for those who want it (and easy to skip for those who don’t).

Business Analytics Principles, Concepts, and Applications

What, Why, and How
Author: Marc J. Schniederjans,Dara G. Schniederjans,Christopher M. Starkey
Publisher: Pearson Education
ISBN: 0133552187
Category: Business & Economics
Page: 350
View: 7970

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Learn everything you need to know to start using business analytics and integrating it throughout your organization. Business Analytics Principles, Concepts, and Applications brings together a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. They offer a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making. Using step-by-step examples, the authors identify common challenges that can be addressed by business analytics, illustrate each type of analytics (descriptive, prescriptive, and predictive), and guide users in undertaking their own projects. Illustrating the real-world use of statistical, information systems, and management science methodologies, these examples help readers successfully apply the methods they are learning. Unlike most competitive guides, this text demonstrates the use of IBM's menu-based SPSS software, permitting instructors to spend less time teaching software and more time focusing on business analytics itself. A valuable resource for all beginning-to-intermediate-level business analysts and business analytics managers; for MBA/Masters' degree students in the field; and for advanced undergraduates majoring in statistics, applied mathematics, or engineering/operations research.

Business Analytics Principles, Concepts, and Applications with SAS

What, Why, and How
Author: Marc J. Schniederjans,Dara G. Schniederjans,Christopher M. Starkey
Publisher: Pearson Education
ISBN: 0133989402
Category: Business & Economics
Page: 334
View: 5106

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Responding to a shortage of effective content for teaching business analytics, this text offers a complete, integrated package of knowledge for newcomers to the subject. The authors present an up-to-date view of what business analytics is, why it is so valuable, and most importantly, how it is used. They combine essential conceptual content with clear explanations of the tools, techniques, and methodologies actually used to implement modern business analytics initiatives. This book offers a proven step-wise approach to designing an analytics program, and successfully integrating it into your organization, so it effectively provides intelligence for competitive advantage in decision making.

Advanced Analytics Methodologies

Driving Business Value with Analytics
Author: Michele Chambers,Thomas W. Dinsmore
Publisher: Pearson Education
ISBN: 0133498603
Category: Business & Economics
Page: 324
View: 1685

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Advanced Analytics Methodologies is today's definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its expanded, cutting-edge coverage helps readers systematically "jump the gap" between their organization's current analytical capabilities and where they need to be. Step by step, Michele Chambers and Thomas Dinsmore help readers customize a complete roadmap for implementing analytics that supports unique corporate strategies, aligns with specific corporate cultures, and serves unique customer and stakeholder communities. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore provide advanced applications and examples not available elsewhere, describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. They show how to: Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and many line-of-business executives.

The Best Thinking in Business Analytics from the Decision Sciences Institute


Author: Decision Sciences Institute,Merrill Warkentin
Publisher: FT Press
ISBN: 0134073053
Category: Computers
Page: 288
View: 2879

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Today, business success depends on making great decisions – and making them fast. Leading organizations apply sophisticated business analytics tools and technologies to evaluate vast amounts of data, glean new insights, and increase both the speed and quality of decision making. In The Best Thinking and Practices in Business Analytics from the Decision Sciences Institute , DSI has compiled award-winning and award-nominated contributions from its most recent conferences: papers that illuminate exceptionally high-value applications and research on analytics for decision-making. These papers have appeared in no other DSI collection. Explore them here, and you’ll discover powerful new opportunities for competitive advantage through analytics. For all business, academic, and organizational professionals concerned with the science of more effective decision-making; and for undergraduate students, graduate students, and certification candidates in all related fields.

Analytics for Insurance

The Real Business of Big Data
Author: Tony Boobier
Publisher: John Wiley & Sons
ISBN: 1119141087
Category: Business & Economics
Page: 296
View: 6867

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The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential – yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business – but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data – but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets.

Global Business Analytics Models

Concepts and Applications in Predictive, Healthcare, Supply Chain, and Finance Analytics
Author: Hokey Min
Publisher: FT Press
ISBN: 0134057619
Category: Computers
Page: 243
View: 2334

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THE COMPLETE GUIDE TO USING ANALYTICS TO MANAGE RISK AND UNCERTAINTY IN COMPLEX GLOBAL BUSINESS ENVIRONMENTS Practical techniques for developing reliable, actionable intelligence–and using it to craft strategy Analytical opportunities to solve key managerial problems in global enterprises Written for working managers: packed with realistic, useful examples This guide helps global managers use modern analytics to gain reliable, actionable, and timely business intelligence–and use it to manage risk, build winning strategies, and solve urgent problems. Dr. Hokey Min offers a practical, easy-to-understand overview of business analytics in a global context, focusing especially on managerial and strategic implications. After demystifying today’s core quantitative tools, he demonstrates them at work in a wide spectrum of global applications. You’ll build models to help segment global markets, forecast demand, assess risk, plan financing, optimize supply chains, and more. Along the way, you’ll find practical guidance for developing analytic thinking, operationalizing Big Data in global environments, and preparing for future analytical innovations. Whether you’re a global executive, strategist, analyst, marketer, supply chain professional, student or researcher, this book will help you drive real value from analytics–in smarter decisions, improved strategy, and better management. In today’s global business environments characterized by growing complexity, volatility, and uncertainty, business analytics has become an indispensable tool for managing these challenges. Specifically, global managers need analytics expertise to solve problems, identify opportunities, shape strategy, mitigate risk, and improve their day-to-day operational efficiency. Now, for the first time, there’s an analytics guide designed specifically for decision-makers in global organizations. Leveraging his experience teaching a number of students and training hundreds of managers and executives, Dr. Hokey Min demystifies the principles and tools of modern business analytics, and demonstrates their real-world use in global business. First, Dr. Min identifies key success factors and mindsets, helping you establish the preconditions for effective analysis. Next, he walks you through the practicalities of collecting, organizing, and analyzing Big Data, and developing models to transform them into actionable insight. Building on these foundations, he illustrates core analytical applications in finance, healthcare, and global supply chains. He concludes by previewing emerging trends in analytics, including the newest tools for automated decision-making. Compare today’s key quantitative tools Stats, data mining, OR, and simulation: how they work, when to use them Get the right data… …and get the data right Predict the future… …and sense its arrival sooner than others can Implement high-value analytics applications… …in finance, supply chains, healthcare, and beyond

People Analytics in the Era of Big Data

Changing the Way You Attract, Acquire, Develop, and Retain Talent
Author: Jean Paul Isson,Jesse S. Harriott
Publisher: John Wiley & Sons
ISBN: 111923316X
Category: Business & Economics
Page: 416
View: 522

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Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics. Written by the Global Vice President of Business Intelligence and Predictive Analytics at Monster Worldwide, this book is packed full of actionable insights to help you source, recruit, acquire, engage, retain, promote, and manage the exceptional talent your organization needs. With a unique approach that applies analytics to every stage of the hiring process and the entire workforce planning and management cycle, this informative guide provides the key perspective that brings analytics into HR in a truly useful way. You're already inundated with disparate employee data, so why not mine that data for insights that add value to your organization and strengthen your workforce? This book presents a practical framework for real-world talent analytics, backed by groundbreaking examples of workforce analytics in action across the U.S., Canada, Europe, Asia, and Australia. Leverage predictive analytics throughout the hiring process Utilize analytics techniques for more effective workforce management Learn how people analytics benefits organizations of all sizes in various industries Integrate analytics into HR practices seamlessly and thoroughly Corporate executives need fact-based insights into what will happen with their talent. Who should you hire? Who should you promote? Who are the top or bottom performers, and why? Who is at risk to quit, and why? Analytics can provide these answers, and give you insights based on quantifiable data instead of gut feeling and subjective assessment. People Analytics in the Era of Big Data is the essential guide to optimizing your workforce with the tools already at your disposal.

Marketing and Sales Analytics

Proven Techniques and Powerful Applications from Industry Leaders
Author: Cesar A. Brea
Publisher: Pearson Education
ISBN: 0133592928
Category: Business & Economics
Page: 235
View: 4807

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PROFITING FROM MARKETING ANALYTICS: YOUR COMPLETE EXECUTIVE ROADMAP “Solid ideas and experiences, well-told, for executives who need higher returns from their analytic investments. Captures many best practices that are consistent with our own experiences at Bain & Company, helping clients develop actionable strategies that deliver sustainable results.” –Bob Bechek, Worldwide Managing Director, Bain & Company “Cesar has explored a complex subject in a clear and useful way as senior marketers look to more effectively leverage the power of data and analytics.” –Bill Brand, Chief Marketing and Business Development Officer, HSN, Inc. “Loaded with meaty lessons from seasoned practitioners, this book defines the guideposts of the Marketing Analytics Age and what it will take for marketing leaders to be successful in it. Cesar Brea has provided a practical playbook for marketers who are ready to make this transition.” –Meredith Callanan, Vice President, Corporate Marketing and Communications, T. Rowe Price “While the field has a lot of books on the statistics of marketing analytics, we also need insights on the organization issues and culture needed to implement successfully. Cesar Brea's Marketing and Sales Analytics has addressed this gap in an interesting and helpful way.” –Scott A. Neslin, Albert Wesley Frey Professor of Marketing, Tuck School of Business, Dartmouth College To successfully apply marketing analytics, executives must orchestrate elements that transcend multiple perspectives and organizational silos. In Marketing and Sales Analytics, leading analytics consultant Cesar Brea shows you exactly how to do this. Brea examines the experiences of 15 leaders who've built high-value analytics capabilities in multiple industries. Then, building on what they've learned, he presents a complete blueprint for implementing and profiting from marketing analytics. You'll learn how to evaluate “ecosystemic” conditions for success, reconcile diverse perspectives to frame the right questions, and organize your people, data, and operating infrastructure to answer them and maximize business results. Brea helps you overcome key challenges ranging from balancing analytic techniques to governance, hidden biases to culture change. He also offers specific guidance on crucial decisions such as “buy vs. build?”, “centralize or decentralize?”, and “hire generalists or specialists?” Whether you lead, practice, or rely on marketing analytics, this guide will help you gain more value–with less frustration. Go beyond “My algorithm can beat up your algorithm” It's not about formulas, it's about cultivating conditions for success Plan backwards, starting from desired business results Focus on value, not allure, hype, or sexiness Orchestrate resources to ask better questions, answer them, and act Tackle any analytically intensive initiative– and get the results you're accountable for Make the most of new “native” digital channels… ... and the rapid digitization of legacy channels, too