This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject.

Utilize organizational data and analytics to make better decisions about managing the learning and development of your workforce.

A guide to the various models and methods to multicriteria decision-making in conditions of uncertainty presented in a systematic approach Multicriteria Decision-Making under Conditions of Uncertainty presents approaches that help to answer the fundamental questions at the center of all decision-making problems: "What to do?" and "How to do it?" The book explores methods of representing and handling diverse manifestations of the uncertainty factor and a multicriteria nature of problems that can arise in system design, planning, operation, and control. The authors—noted experts on the topic—and their book covers essential questions, including notions and fundamental concepts of fuzzy sets, models and methods of multiobjective as well as multiattribute decision-making, the classical approach to dealing with uncertainty of information and its generalization for analyzing multicriteria problems in condition of uncertainty, and more. This comprehensive book contains information on "harmonious solutions" in multiobjective problem-solving (analyzing < X, F> models), construction and analysis of < X, R> models, results aimed at generating robust solutions in analyzing multicriteria problems under uncertainty, and more. In addition, the book includes illustrative examples of various applications, including real-world case studies related to the authors’ various industrial projects. This important resource: Explains the design and processing aspect of fuzzy sets, including construction of membership functions, fuzzy numbers, fuzzy relations, aggregation operations, and fuzzy sets transformations Describes models of multiobjective decision-making (< X. M> models), their analysis on the basis of using the Bellman-Zadeh approach to decision-making in a fuzzy environment, and their diverse applications, including multicriteria allocation of resources Investigates models of multiattribute decision-making (< X, R> models) and their analysis on the basis of the construction and processing of fuzzy preference relations as well as demonstrating their applications to solve diverse classes of multiattribute problems Explores notions of payoff matrices and fuzzy-set-based generalization and modification of the classic approach to decision-making under conditions of uncertainty to generate robust solutions in analyzing multicriteria problems Written for students, researchers and practitioners in disciplines in which decision-making is of paramount relevance, Multicriteria Decision-Making under Conditions of Uncertainty presents a systematic and current approach that encompasses a range of models and methods as well as new applications.

As your business tries to make sense of today’s staggering amount of structured and unstructured data, traditional analytics will take you only so far. The key to success over the next few years will depend on augmented analytics, a method that embeds machine learning and natural language processing (NLP) in the process. This report explains how augmented analytics can help you uncover hidden insights, predict results, and even prescribe solutions. Author Alice LaPlante provides best practices for deploying augmented analytics, along with real-world case studies that show you how to take full advantage of this method. IT professionals, business managers, and CFOs will learn ways to democratize data use among business users and executives, using a self-service model. The future belongs to those who can get more from their data. This report shows you how. Get a primer on the key components and learn how they work together Delve into the benefits of—and roadblocks to—adopting augmented analytics Learn how companies use this method in marketing, sales, finance, and human resources Examine case studies of companies including Accenture and Riverbed

Make Better Decisions, Leverage New Opportunities, and Automate Decisioning at Scale Prescriptive analytics is more directly linked to successful decision-making than any other form of business analytics. It can help you systematically sort through your choices to optimize decisions, respond to new opportunities and risks with precision, and continually reflect new information into your decisioning process. In Prescriptive Analytics, analytics expert Dr. Dursun Delen illuminates the field’s state-of-the-art methods, offering holistic insight for both professionals and students. Delen’s end-to-end, all-inclusive approach covers optimization, simulation, multi-criteria decision-making methods, inference- and heuristic-based decisioning, and more. Balancing theory and practice, he presents intuitive conceptual illustrations, realistic example problems, and real-world case studies–all designed to deliver knowledge you can use. Discover where prescriptive analytics fits and how it improves decision-making Identify optimal solutions for achieving an objective within real-world constraints Analyze complex systems via Monte-Carlo, discrete, and continuous simulations Apply powerful multi-criteria decision-making and mature expert systems and case-based reasoning Preview emerging techniques based on deep learning and cognitive computing

This book outlines the benefits and limitations of simulation, what is involved in setting up a simulation capability in an organization, the steps involved in developing a simulation model and how to ensure that model results are implemented. In addition, detailed example applications are provided to show where the tool is useful and what it can offer the decision maker. In Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics, Andrew Greasley provides an in-depth discussion of Business process simulation and how it can enable business analytics How business process simulation can provide speed, cost, dependability, quality, and flexibility metrics Industrial case studies including improving service delivery while ensuring an efficient use of staff in public sector organizations such as the police service, testing the capacity of planned production facilities in manufacturing, and ensuring on-time delivery in logistics systems State-of-the-art developments in business process simulation regarding the generation of simulation analytics using process mining and modeling people’s behavior Managers and decision makers will learn how simulation provides a faster, cheaper and less risky way of observing the future performance of a real-world system. The book will also benefit personnel already involved in simulation development by providing a business perspective on managing the process of simulation, ensuring simulation results are implemented, and that performance is improved.

This is a practical, user-friendly guide to the identification and assessment of indoor air contaminants that contribute to buildingrelated illness in commercial buildings, institutions, and residences. The third edition covers basic concepts and details various approaches and up-to-date analytical methods.

Learn how to apply HR analytics to solve real workplace challenges and drive better business decisions.

Dive into the world of predictive analytics with 'Practical Predictive Analytics.' This comprehensive guide walks you through analyzing current and historical data to predict future outcomes. Using tools like R and Spark, you will master practical skills, solve real-world challenges, and apply predictive analytics across domains like marketing, healthcare, and retail. What this Book will help me do Learn the six steps for successfully implementing predictive analytics projects. Acquire practical skills in data cleaning, input, and model deployment using tools like R and Spark. Understand core predictive analytics algorithms and their applications in various industries. Apply data analytics techniques to solve problems in fields such as healthcare and marketing. Master methods for handling big data analytics using Databricks and Spark for effective prediction. Author(s) The author, None Winters, is an experienced data scientist and technical educator. With extensive background in predictive analytics, Winters specializes in applying statistical methods and techniques to real-world consultation scenarios. Winters brings a practical and accessible approach to this text, ensuring that learners can follow along and apply their newfound expertise effectively. Who is it for? This book is ideal for statisticians and analysts with some programming background in languages like R, who want to master predictive analytics skills. It caters to intermediate learners who aim to enhance their ability to solve complex analytical problems. Whether you're looking to advance your career or improve your proficiency in data science, this book will serve as a valuable resource for learning and growth.

Resolve data-heavy retail marketing questions through key analytic steps, with expert guidance in a direct and conceptual style.

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

Key Business Analytics will help managers apply tools to turn data into insights that help them better understand their customers, optimise their internal processes and identify cost savings and growth opportunities.

More than ever, data drives decisions in organizations—and we have more data, and more ways to analyze it, than ever. Yet strategic initiatives continue to fail as often as they did when computers ran on punch cards. Economist and research scientist Alec Levenson says we need a new approach. The problem, Levenson says, is that the business people who devise the strategies and the human resources people who get employees to implement them use completely different analytics. Business analytics can determine if operational priorities aren't being achieved but can't explain why. HR analytics reveal potentially helpful policy and process improvements but can't identify which would have the greatest strategic impact. This book shows how to use an integrated approach to bring these two pieces together. Levenson presents a thorough and realistic treatment of the reasons for and challenges of taking an integrated approach. He provides details on the different parts of both enterprise and human capital analytics that have to be conducted for integration to be successful and includes specific questions to ask, along with examples of applying integrated analytics to address particular organizational challenges. Effective analytics is a team sport. Levenson's approach allows you to get the deepest insights by bringing people together from both the business and HR perspectives to assess what's going on and determine the right solution.

Apply the tools and techniques of text analytics with ease and add value to your company by understanding its key approaches and the business reality behind them.

Here's the net takeaway: Businesses want insights from data they can translate into meaningful actions and real results. Software vendors are beginning to deliver a new generation of advanced analytics packages that address business issues directly. In this O'Reilly report, Mike Barlow reveals how this new user-friendly software is helping businesses go beyond data analysis and straight to decision-making—without requiring data science expertise or truckloads of cash. How has advanced analytics progressed from lab project to commercial product so quickly? Through interviews with data analysts, you'll understand the role that machine learning plays in specialized analytics packages, and how this software alone can make decisions based on what's likely to happen next. When you have these capabilities, you’ve reached "the last mile of analytics."

Doing data science is difficult. Projects are typically very dynamic with requirements that change as data understanding grows. The data itself arrives piecemeal, is added to, replaced, contains undiscovered flaws and comes from a variety of sources. Teams also have mixed skill sets and tooling is often limited. Despite these disruptions, a data science team must get off the ground fast and begin demonstrating value with traceable, tested work products. This is when you need Guerrilla Analytics. In this book, you will learn about: The Guerrilla Analytics Principles: simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting. Reproducible, traceable analytics: how to design and implement work products that are reproducible, testable and stand up to external scrutiny. Practice tips and war stories: 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and research. Preparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventions. Data gymnastics: over a dozen analytics patterns that your team will encounter again and again in projects The Guerrilla Analytics Principles: simple rules of thumb for maintaining data provenance across the entire analytics life cycle from data extraction, through analysis to reporting Reproducible, traceable analytics: how to design and implement work products that are reproducible, testable and stand up to external scrutiny Practice tips and war stories: 90 practice tips and 16 war stories based on real-world project challenges encountered in consulting, pre-sales and research Preparing for battle: how to set up your team's analytics environment in terms of tooling, skill sets, workflows and conventions Data gymnastics: over a dozen analytics patterns that your team will encounter again and again in projects

Implementing Analytics demystifies the concept, technology and application of analytics and breaks its implementation down to repeatable and manageable steps, making it possible for widespread adoption across all functions of an organization. Implementing Analytics simplifies and helps democratize a very specialized discipline to foster business efficiency and innovation without investing in multi-million dollar technology and manpower. A technology agnostic methodology that breaks down complex tasks like model design and tuning and emphasizes business decisions rather than the technology behind analytics. Simplifies the understanding of analytics from a technical and functional perspective and shows a wide array of problems that can be tackled using existing technology Provides a detailed step by step approach to identify opportunities, extract requirements, design variables and build and test models. It further explains the business decision strategies to use analytics models and provides an overview for governance and tuning Helps formalize analytics projects from staffing, technology and implementation perspectives Emphasizes machine learning and data mining over statistics and shows how the role of a Data Scientist can be broken down and still deliver the value by building a robust development process

The world of learning and performance has changed significantly since the first edition of First Things Fast was published more than a decade ago. This thoroughly revised and updated second edition of the best-selling classic recognizes a world chock-full of technology, economic strains, and opportunities. How do learning and performance professionals plan in this shifting context? How do they take advantage of new human and Internet-based resources? How do they bring their recommendations forward and add more value, no matter where they work? These questions are addressed throughout this new edition. This important resource is a practical guide that is filled with job aids, design templates, and examples offering step-by-step guidance to the basics of performance analysis. This new edition includes: New questions and templates that reflect the shift of learning and support from the classroom to the workplace, and the blends that provide learning and support in both environments Fresh approaches for using wikis, blogs, and online surveys to gather information Innovative ideas for tapping into the power of social networking and the possibilities presented for analysts Information on the critical link between analysis and evaluation and new guidelines for both activities A wealth of new illustrative case examples Insightful commentaries from successful leaders in the field who explain how they use analysis to advance individual and organizational strategy "Allison Rossett combines thought leadership for the profession with practical guidance. This book, the second edition of a classic in the field, is filled with proven practices and ready-to-use tools making this a resource you'll use frequently." -Dana Gaines Robinson, Coauthor, Performance Consulting ANDSTRATEGIC BUSINESS PARTNER "What I appreciate about this book is that it is a straightforward, practical guide to planning, and it embraces new technology and the convergence of learning and work." -Nancy J. Lewis, Vice President and Chief Learning Officer, ITT Corporation

“I believe that this book will fill a great need for both full-time competitive intelligence practitioners, and those looking to add analytical skills to their managerial tool kit.” --Bill Fiora, Partner and Founder, Outward Insights “All practicing managers and business decision makers should be grateful to Fleisher and Bensoussan for showing them how their analysis work can become more rigorous and their approach less casual. Accept no imitations. This is the genuine article.” --Sheila Wright, Director of the Competitive Intelligence-Marketing Interface Teaching and Research Initiative (CIMITRI) at Leicester Business School, De Montfort University The Definitive How-To Guide for Business and Competitive Analysis Transform raw data into compelling, actionable business recommendations Answer the questions executives ask–“What?” “So What?” and “Now What?” Today’s 24 most valuable techniques: how to choose them, how to use them For everyone who performs analysis: managers, consultants, functional specialists, and strategists A completely new book by the authors of the popular Strategic and Competitive Analysis Business success begins with deep clarity about your competition and your business environment. But, even as data gathering has improved dramatically, few business professionals know the state-of-the-art techniques for analyzing their data. Now there’s a comprehensive, immensely practical guide to today’s best tools and techniques for answering tough questions and making actionable recommendations. begins with end-to-end guidance on the analysis process, including defining problems, avoiding analytical pitfalls, choosing tools, and communicating results. Next, the authors offer detailed guides on 24 of today’s most valuable analysis models: techniques that have never been brought together in one book before.They offer in-depth, step-by-step guidance for using every technique–along with realistic assessments of strengths, weaknesses, feasibility, and business value. Business and Competitive Analysis You are flooded with data. This book will help you transform that data into actionable insights and recommendations that enterprise decision makers cannot and will not ignore. Craig S. Fleisher and Babette E. Bensoussan begin with a practical primer on the process and context of business and competitive analysis: how it works, how to avoid pitfalls, and how to communicate results. Next, they introduce their unique FAROUT method for choosing the right tools for each assignment. The authors then present 24 of today’s most valuable analysis methods.They cover “classic” techniques, such as McKinsey 7S and industry analysis, as well as emerging techniques from multiple disciplines:economics,corporate finance, sociology, anthropology, and the intelligence and futurist communities. For each, they present clear descriptions, background context, strategic rationales, strengths, weaknesses, step-by-step instructions, and references. The result is a book you can rely on to meet any analysis challenge, no matter how complex or novel. The fundamentals of business and competitive analysis Goals, processes, pitfalls, deliverables, and benefits Competitive analysis techniques Nine Forces, Competitive Positioning, Business Model, SERVO, and Supply Chain Analyses Enterprise analysis techniques Benchmarking, McKinsey 7S, Shadowing, Product Line, and Win/Loss Analyses Environmental analysis techniques Strategic Relationships, Corporate Reputation, Critical Success Factors, Driving Forces, and Country Risk Analyses Evolutionary analysis techniques Technology Forecasting,War Gaming, Event/Timeline, Indications and Warning Analyses, and more Financial, probabilistic, and statistical techniques Basic Statistics, Competitor Cash Flow, Analysis of Competing Hypothesis (ACH), and Linchpin Analyses Table of Contents: Preface 1. Business and Competitive Analysis: Definition, Context, and Benefits 2. Performing the Analysis Process 3. Avoiding Analysis Pitfalls 4. Communicating Analysis Results 5. Applying the FAROUT method 6. Industry Analysis (The Nine Forces) 7. Competitive Positioning Analysis 8. Business Model Analysis 9. SERVO Analysis 10. Supply Chain Management (SCM) Analysis 11. Benchmarking Analysis 12. McKinsey 7S Analysis 13. Shadowing 14. Product Line Analysis 15. Win/Loss Analysis 16. Strategic Relationship Analysis 17. Corporate Reputation Analysis 18. Critical Success Factors Analysis 19. Country Risk Analysis 20. Driving Forces Analysis 21. Event and Timeline Analysis 22. Technology Forecasting 23. War Gaming 24. Indications and Warning Analysis 25. Historiographical Analysis 26. Interpretation of Statistical Analysis 27. Competitor Cash Flow Analysis 28. Analysis of Competing Hypothesis 29. Linchpin Analysis Index

This issue discusses the six steps involved in defining a client's training needs in relation to the organization's overall business goals. Offers techniques to use at each point in the analysis process plus sample questions used for collecting data.