No longer. A new generation of tools and massive amounts of available data make it easy for anyone to create visualizations that communicate ideas far more effectively than generic spreadsheet charts ever could.What’s more, building good charts is quickly becoming a need-to-have skill for managers. If you’re not doing it, other managers are, and they’re getting noticed for it and getting credit for contributing to your company’s success.In Good Charts, dataviz maven Scott Berinato provides an essential guide to how visualization works and how to use this new language to impress and persuade. Dataviz today is where spreadsheets and word processors were in the early 1980s—on the cusp of changing how we work. Berinato lays out a system for thinking visually and building better charts through a process of talking, sketching, and prototyping.This book is much more than a set of static rules for making visualizations. It taps into both well-established and cutting-edge research in visual perception and neuroscience, as well as the emerging field of visualization science, to explore why good charts (and bad ones) create “feelings behind our eyes.” Along the way, Berinato also includes many engaging vignettes of dataviz pros, illustrating the ideas in practice.Good Charts will help you turn plain, uninspiring charts that merely present information into smart, effective visualizations that powerfully convey ideas.

    Strategic, applied, and performance-oriented. While most textbooks in this area stress concepts and theory, Market-Based Management, 4e, incorporates a more strategic and applied approach. External performance metrics of a business are emphasized and actual measurement tools are provided. Its streamlined organization makes it ideal for courses in which outside cases and readings will be assigned.

    As author Jeffrey Needham points out in this eye-opening book, big data can provide unprecedented insight into user habits, giving enterprises a huge market advantage. It will also inspire organizations to change the way they function."Disruptive Possibilities: How Big Data Changes Everything" takes you on a journey of discovery into the emerging world of big data, from its relatively simple technology to the ways it differs from cloud computing. But the big story of big data is the disruption of enterprise status quo, especially vendor-driven technology silos and budget-driven departmental silos. In the highly collaborative environment needed to make big data work, silos simply don't fit.Internet-scale computing offers incredible opportunity and a tremendous challenge--and it will soon become standard operating procedure in the enterprise. This book shows you what to expect.

    When inexperienced entrepreneurs ask my advice about their idea for a tech startup, they often worry "What if Google decides to compete with us? They will crush us!" I respond that far more startups die of suicide than homicide. If you can avoid hurting yourself, then you are already better off than most of your competitors. Startups are a chance to build something entirely original with brilliant and ambitious people. But startups are also dangerous. Limited money means there is little room for mistakes. One bad decision can mean bankruptcy. The potential payoff attracts capital, which in turn attracts scam artists. The unscrupulous often lack the skills needed to succeed, but sometimes they are smart enough to trick investors. Even entrepreneurs who start with a strong moral compass can find that the threat of failure unmoors their ethics from their ambition. Emotions matter. We might hope that those in leadership positions possess strength and resilience, but vanity and fragile egos have sabotaged many of the businesses that I’ve worked with. Defeat is always a possibility, and not everyone finds healthy ways to deal with the stress. In this book I offer both advice and also warnings. I've seen certain self-destructive patterns play out again and again, so I wanted to document one of the most extreme cases that I've witnessed. In 2015 I worked for a startup that began with an ingenious idea: to use the software techniques known as Natural Language Processing to allow people to interact with databases by writing ordinary English sentences. This was a multi-billion dollar idea that could have transformed the way people gathered and used information. However, the venture had inexperienced leadership. They burned through their $1.3 million seed money. As their resources dwindled, their confidence transformed into doubt, which was aggravated by edicts from the Board Of Directors ordering sudden changes that effectively threw away weeks' worth of work. Every startup forces its participants into extreme positions, often regarding budget and deadlines. Often these situations are absurd to the point of parody. Therefore, there is considerable humor in this story. The collision of inexperience and desperation gives rise to moments that are simply silly. I tell this story in a day-to-day format, both to capture the early optimism, and then the later sense of panic. Here then, is a cautionary tale, a warning about tendencies that everyone joining a startup should be on guard against."

    Now more than ever, managers must know how to tease insight from data--to understand where the numbers come from, make sense of them, and use them to inform tough decisions. How do you get started?Whether you're working with data experts or running your own tests, you'll find answers in the HBR Guide to Data Analytics Basics for Managers. This book describes three key steps in the data analysis process, so you can get the information you need, study the data, and communicate your findings to others.You'll learn how to: Identify the metrics you need to measure Run experiments and A/B tests Ask the right questions of your data experts Understand statistical terms and concepts Create effective charts and visualizations Avoid common mistakes

    A brand must be elastic enough to allow for reasonable category and product-line extensions, flexible enough to change with dynamic market conditions, consistent enough so that consumers who travel physically or virtually won’t be confused, and focused enough to provide clear differentiation from the competition. Strong brands are more than globally recognizable; they are critical assets that can make a significant contribution to your company’s bottom line.In Global Brand Power, Kahn brings brand management into the 21st century, addressing how branding contributes to the purchase process and how to position a strong global brand, from identifying the appropriate competitive set, offering a sustainable differential advantage, and targeting the right strategic segment. This essential guide also covers how customer ownership of your brand affects marketing strategy, methods for assessing brand value, how to manage a brand for long-term profitability, effective brand communications and repositioning strategies, and how to manage a brand in a world of total transparency—where one slip-up can go around the world via social media instantaneously.Filled with stories about how Coca-Cola, The Estée Lauder Companies Inc., Marriott, Apple, Starbucks, Campbell Soup Company, Southwest Airlines, and celebrities like Lady Gaga are leveraging their brands, Global Brand Power is the only book you will need to implement an effective brand strategy for your firm.

    Along the way we’ll learn how selection bias can explain why your boss doesn’t know he sucks (even when everyone else does); how to use Bayes’ Theorem to decide if your partner is cheating on you; and why Mark Zuckerberg should never be used as an example for anything. See the world in a whole new light, and make better decisions and judgements without ever going near a t-test. Think. Think Statistically.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    Includes generic job models for entrepreneurs, technical professionals, salespeople, service workers and corporate managers. Defines JCA and describes in detail how to conduct JCA studies. Suggests future directions and uses for competency research.

    These days, linger over a Web page selling lamps, and they will turn up at the advertising margins as you move around the Internet, reminding you, tempting you to make that purchase. Search engines such as Google can now look deep into the data on the Web to pull out instances of the words you are looking for. And there are pages that collect and assess information to give you a snapshot of changing political opinion. These are just basic examples of the growth of Web intelligence, as increasingly sophisticated algorithms operate on the vast and growing amount of data on the Web, sifting, selecting, comparing, aggregating, correcting; following simple but powerful rules to decide what matters. While original optimism for Artificial Intelligence declined, this new kind of machine intelligence is emerging as the Web grows ever larger and more interconnected.Gautam Shroff takes us on a journey through the computer science of search, natural language, text mining, machine learning, swarm computing, and semantic reasoning, from Watson to self-driving cars. This machine intelligence may even mimic at a basic level what happens in the brain.

    Yet nothing could be further from the truth. In fact, often the more elaborately crafted a business plan, the more likely the venture is to flop.Why? Most plans waste too much ink on numbers and devote too little to information that really matters to investors. The result? Investors discount them.In How to Write a Great Business Plan, William A. Sahlman shows how to avoid this all-too-common mistake by ensuring that your plan assesses the factors critical to every new venture:· The people—the individuals launching and leading the venture and outside parties providing key services or important resources· The opportunity—what the business will sell and to whom, and whether the venture can grow and how fast· The context—the regulatory environment, interest rates, demographic trends, and other forces shaping the venture's fate· Risk and reward—what can go wrong and right, and how the entrepreneurial team will respondTimely in this age of innovation, How to Write a Great Business Plan helps you give your new venture the best possible chances for success.

    Information is provided on the fundamental concepts of table and graph design, the numbers and knowledge most suitable for display in a graphic form, the best tabular means to communicate certain ideas, and the component-level aspects of design. Analysts, technicians, and managers will appreciate the solid theory behind this outline for ensuring that tables and graphs present quantitative business information in a truthful, attractive format that facilitates better decision making.

    Mullen, Jr. reveals how to become a top-producing financial advisor using the method he has taught at Merrill Lynch and is famous for in the industry. This comprehensive book combines marketing, prospecting, sales, and time management techniques into a system that will help readers build a successful and lucrative practice. Mullen gives financial advisors all the tools and guidance they need to:- get the appointment - build relationships - convert prospects to client - retain clients - use niche marketing successfully - balance current clients and prospects - increase the products and services each client uses - attract millionaire clientsContaining templates, scripts, letters, and 15 tried-and-true Market Action Plans, this indispensable guide shows readers how to take their financial services practice to the million-dollar level and beyond.

    

    In it readers will discover how to avoid typical mistakes, especially those pertaining to conflict among different divisions.