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Author: Thomas C. Redman
Publisher: Harvard Business Press
ISBN: 1422163644
Category : Business & Economics
Languages : en
Pages : 257
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Book Description
Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
Author: Thomas C. Redman
Publisher: Harvard Business Press
ISBN: 1422163644
Category : Business & Economics
Languages : en
Pages : 257
Get Book
Book Description
Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.
Author: Marc Randolph
Publisher: Little, Brown
ISBN: 0316530212
Category : Business & Economics
Languages : en
Pages : 336
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Book Description
In the tradition of Phil Knight's Shoe Dog comes the incredible untold story of how Netflix went from concept to company-all revealed by co-founder and first CEO Marc Randolph. Once upon a time, brick-and-mortar video stores were king. Late fees were ubiquitous, video-streaming unheard was of, and widespread DVD adoption seemed about as imminent as flying cars. Indeed, these were the widely accepted laws of the land in 1997, when Marc Randolph had an idea. It was a simple thought—leveraging the internet to rent movies—and was just one of many more and far worse proposals, like personalized baseball bats and a shampoo delivery service, that Randolph would pitch to his business partner, Reed Hastings, on their commute to work each morning. But Hastings was intrigued, and the pair—with Hastings as the primary investor and Randolph as the CEO—founded a company. Now with over 150 million subscribers, Netflix's triumph feels inevitable, but the twenty first century's most disruptive start up began with few believers and calamity at every turn. From having to pitch his own mother on being an early investor, to the motel conference room that served as a first office, to server crashes on launch day, to the now-infamous meeting when Netflix brass pitched Blockbuster to acquire them, Marc Randolph's transformational journey exemplifies how anyone with grit, gut instincts, and determination can change the world—even with an idea that many think will never work. What emerges, though, isn't just the inside story of one of the world's most iconic companies. Full of counter-intuitive concepts and written in binge-worthy prose, it answers some of our most fundamental questions about taking that leap of faith in business or in life: How do you begin? How do you weather disappointment and failure? How do you deal with success? What even is success? From idea generation to team building to knowing when it's time to let go, That Will Never Work is not only the ultimate follow-your-dreams parable, but also one of the most dramatic and insightful entrepreneurial stories of our time.
Author: Chris J. Lloyd
Publisher: John Wiley & Sons
ISBN: 0470619600
Category : Business & Economics
Languages : en
Pages : 512
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Book Description
A hands-on guide to the use of quantitative methods and software for making successful business decisions The appropriate use of quantitative methods lies at the core of successful decisions made by managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, Data Driven Business Decisions introduces readers to the important role that data plays in understanding business outcomes, addressing four general areas that managers need to know about: data handling and Microsoft Excel®, uncertainty, the relationship between inputs and outputs, and complex decisions with trade-offs and uncertainty. Grounded in the author's own classroom approach to business statistics, the book reveals how to use data to understand the drivers of business outcomes, which in turn allows for data-driven business decisions. A basic, non-mathematical foundation in statistics is provided, outlining for readers the tools needed to link data with business decisions; account for uncertainty in the actions of others and in patterns revealed by data; handle data in Excel®; translate their analysis into simple business terms; and present results in simple tables and charts. The author discusses key data analytic frameworks, such as decision trees and multiple regression, and also explores additional topics, including: Use of the Excel® functions Solver and Goal Seek Partial correlation and auto-correlation Interactions and proportional variation in regression models Seasonal adjustment and what it reveals Basic portfolio theory as an introduction to correlations Chapters are introduced with case studies that integrate simple ideas into the larger business context, and are followed by further details, raw data, and motivating insights. Algebraic notation is used only when necessary, and throughout the book, the author utilizes real-world examples from diverse areas such as market surveys, finance, economics, and business ethics. Excel® add-ins StatproGo and TreePlan are showcased to demonstrate execution of the techniques, and a related website features extensive programming instructions as well as insights, data sets, and solutions to problems included in the material. Data Driven Business Decisions is an excellent book for MBA quantitative analysis courses or undergraduate general statistics courses. It also serves as a valuable reference for practicing MBAs and practitioners in the fields of statistics, business, and finance.
Author: Daniel J. Power
Publisher: Business Expert Press
ISBN: 1631576593
Category : Business & Economics
Languages : en
Pages : 106
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Book Description
Digital disruption is accelerating. Implementing a successful digital transformation strategy requires that senior managers make trade-off decisions to reinvent a business. Equally important all decision makers must learn to ask the right questions, use data and computer support in decision making, and increase their knowledge and skills. Creating a data-centric culture and rewarding data-based decision making leads to successful digital transformation. Join the digital journey. This book is targeted at managers, especially middle-level managers who are trying to come to grips with using data-based decision making in a transforming organization. The authors explore a number of broad questions including: How can managers become data-based decision makers? How can digital transformation become part of an organizational strategy? What new skills do managers need to implement digital transformation? How will we know an organization has been successfully transformed?
Author: Kim Schildkamp
Publisher: Springer Science & Business Media
ISBN: 9400748159
Category : Education
Languages : en
Pages : 221
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Book Description
In a context where schools are held more and more accountable for the education they provide, data-based decision making has become increasingly important. This book brings together scholars from several countries to examine data-based decision making. Data-based decision making in this book refers to making decisions based on a broad range of evidence, such as scores on students’ assessments, classroom observations etc. This book supports policy-makers, people working with schools, researchers and school leaders and teachers in the use of data, by bringing together the current research conducted on data use across multiple countries into a single volume. Some of these studies are ‘best practice’ studies, where effective data use has led to improvements in student learning. Others provide insight into challenges in both policy and practice environments. Each of them draws on research and literature in the field.
Author: Chris O'Neal
Publisher: International Society for Technology in Education
ISBN: 1564844609
Category : Education
Languages : en
Pages : 149
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Book Description
This workbook will serve as your guide to incorporating the data-driven decision making process into your organization’s culture and behavior. O’Neal leads you through setting up teams; warehousing, accessing, and examining data; and finally reflecting on your process. Understand what’s happening in your school environment and how you can make better decisions that will keep you on a path to success.
Author: Nikki Blackmith
Publisher: CRC Press
ISBN: 1040017649
Category : Business & Economics
Languages : en
Pages : 328
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Book Description
Since the beginning of the 21st century, there has been an explosion in startup organizations. Together, these organizations have been valued at over $3 trillion. In 2019, alone, nearly $300 billion of venture capital was invested globally (Global Startup Ecosystem Report 2020). Simultaneously, an explosion in high volume and high velocity of big data is rapidly changing how organizations function. Gone are the days where organizations can make decisions solely on intuition, logic, or experience. Some have gone as far as to say that data is the most valuable currency and resource available to businesses, and startups are no exception. However, startups and small businesses do differ from their larger counterparts and corporations in three distinct ways: 1) they tend to have fewer resources, time, and specialized training to devote to data analytics; 2) they are part of a unique entrepreneurial ecosystem with unique needs; 3) scholarship and academic research on human capital data analytics in startups is lacking. Existing entrepreneurship research focuses almost exclusively on macro-level aspects. There has been little to no integration of micro- and meso-level research (i.e., individual and team sciences), which is unfortunate given how organizational scientists have significantly advanced human capital data analytics. Unlike other books focused on data analytics and decision for organizations, this proposed book is purposefully designed to be more specifically aimed at addressing the unique idiosyncrasies of the science, research, and practice of startups. Each chapter highlights a specific organizational domain and discuss how a novel data analytic technique can help enhance decision-making, provides a tutorial of said regarding the data analytic technique, and lists references and resources for the respective data analytic technique. The volume will be grounded in sound theory and practice of organizational psychology, entrepreneurship and management and is divided into two parts: assessing and evaluating human capital performance and the use of data analytics to manage human capital.
Author: Mark Jeffery
Publisher: John Wiley & Sons
ISBN: 0470504544
Category : Business & Economics
Languages : en
Pages : 325
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Book Description
NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATION How organizations can deliver significant performance gains through strategic investment in marketing In the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing. Explains how to use data-driven marketing to deliver return on marketing investment (ROMI) in any organization In-depth discussion of the fifteen key metrics every marketer should know Based on original research from America's leading marketing business school, complemented by experience teaching ROMI to executives at Microsoft, DuPont, Nisan, Philips, Sony and many other firms Uses data from a rigorous survey on strategic marketing performance management of 252 Fortune 1000 firms, capturing $53 billion of annual marketing spending In-depth examples of how to apply the principles in small and large organizations Free downloadable ROMI templates for all examples given in the book With every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time.
Author: Harvard Business Review
Publisher: Harvard Business Press
ISBN: 1633694291
Category : Business & Economics
Languages : en
Pages : 256
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Book Description
Don't let a fear of numbers hold you back. Today's business environment brings with it an onslaught of data. 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
Author: Amar Sahay
Publisher: Business Expert Press
ISBN: 1631573322
Category : Business & Economics
Languages : en
Pages : 242
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Book Description
Business Analytics: A Data-Driven Decision Making Approach for Business-Part I,/i> provides an overview of business analytics (BA), business intelligence (BI), and the role and importance of these in the modern business decision-making. The book discusses all these areas along with three main analytics categories: (1) descriptive, (2) predictive, and (3) prescriptive analytics with their tools and applications in business. This volume focuses on descriptive analytics that involves the use of descriptive and visual or graphical methods, numerical methods, as well as data analysis tools, big data applications, and the use of data dashboards to understand business performance. The highlights of this volume are: Business analytics at a glance; Business intelligence (BI), data analytics; Data, data types, descriptive analytics; Data visualization tools; Data visualization with big data; Descriptive analytics-numerical methods; Case analysis with computer applications.
