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Prediction machines : the simple economics of artificial intelligence
The idea of artificial intelligence--job-killing robots, self-driving cars, and self-managing organizations--captures the imagination, evoking a combination of wonder and dread for those of us who will have to deal with the consequences. But what if it's not quite so complicated? The real job of artificial intelligence, argue these three eminent economists, is to lower the cost of prediction. And once you start talking about costs, you can use some well-established economics to cut through the hype. The constant challenge for all managers is to make decisions under uncertainty. And AI contributes by making knowing what's coming in the future cheaper and more certain. But decision making has another component: judgment, which is firmly in the realm of humans, not machines. Making prediction cheaper means that we can make more predictions more accurately and assess them with our better (human) judgment. Once managers can separate tasks into components of prediction and judgment, we can begin to understand how to optimize the interface between humans and machines. More than just an account of AI's powerful capabilities, Prediction Machines shows managers how they can most effectively leverage AI, disrupting business as usual only where required, and provides businesses with a toolkit to navigate the coming wave of challenges and opportunities.-- Provided by publisher
Book
Modeling, measuring and managing risk
This book is the first in the market to treat single- and multi-period risk measures (risk functionals) in a thorough, comprehensive manner. It combines the treatment of properties of the risk measures with the related aspects of decision making under risk.
eBook
Quantitative Risk Assessment
Quantitative risk assessments cannot eliminate risk, nor can they resolve trade-offs. They can, however, guide principled risk management and reduction - if the quality of assessment is high and decision makers understand how to use it. This book builds a unifying scientific framework for discussing and evaluating the quality of risk assessments and whether they are fit for purpose. Uncertainty is a central topic. In practice, uncertainties about inputs are rarely reflected in assessments, with the result that many safety measures are considered unjustified. Other topics include the meaning of a probability, the use of probability models, the use of Bayesian ideas and techniques, and the use of risk assessment in a practical decision-making context. Written for professionals, as well as graduate students and researchers, the book assumes basic probability, statistics and risk assessment methods. Examples make concepts concrete, and three extended case studies show the scientific framework in action.
eBook
Leaders and innovators : how data-driven organizations are winning with analytics
An integrated, strategic approach to higher-value analytics Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows how businesses leverage enterprise analytics to gain strategic insights for profitability and growth.
eBook
Visual Six Sigma : making data analysis lean
'Visual Six Sigma' provides the statistical techniques that help you get more information from your data. A unique emphasis on the visual allows you to take a more active role in data-driven decision making, so you can leverage your contextual knowledge to pose relevant questions and make more sound decisions. You'll learn dynamic visualization and exploratory data analysis techniques that help you identify occurrences and sources of variation, and the strategies and processes that make Six Sigma work for your organisation. This updated third edition includes new information on data quality, presentation, and analysis, with new, streamlined case studies featuring the latest functionalities in JMP 11 and JMP 11 Pro.
Book
Visual six sigma : making data analysis lean
Streamline data analysis with an intuitive, visual Six Sigma strategy
Visual Six Sigma provides the statistical techniques that help you get more information from your data. A unique emphasis on the visual allows you to take a more active role in data-driven decision making, so you can leverage your contextual knowledge to pose relevant questions and make more sound decisions. You'll learn dynamic visualization and exploratory data analysis techniques that help you identify occurrences and sources of variation, and the strategies and processes that make Six Sigma work for your organization.
The Six Sigma strategy helps you identify and remove causes of defects and errors in manufacturing and business processes; the more pragmatic Visual approach opens the strategy beyond the realms of statisticians to provide value to all business leaders amid the growing need for more accessible quality management tools.
* See where, why, and how your data varies
* Find clues to underlying behavior in your data
* Identify key models and drivers
* Build your own Six-Sigma experience
Whether your work involves a Six Sigma improvement project, a design project, a data-mining inquiry, or a scientific study, this practical breakthrough guide equips you with the skills and understanding to get more from your data. With intuitive, easy-to-use tools and clear explanations, Visual Six Sigma is a roadmap to putting this strategy to work for your company.
eBook
Big data, big innovation
A practical guide to leveraging your data to spur innovation and growth
Your business generates reams of data, but what do you do with it? Reporting is only the beginning. Your data holds the key to innovation and growth – you just need the proper analytics. In Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics, author Evan Stubbs explores the potential gold hiding in your un-mined data. As Chief Analytics Officer for SAS Australia/New Zealand, Stubbs brings an industry insider's perspective to guide you through pattern recognition, analysis, and implementation.
Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics details a groundbreaking approach to ensuring your company's upward trajectory. Use this guide to leverage your customer information, financial reports, performance metrics, and more to build a rock-solid foundation for future growth.
* Build an effective analytics team, and empower them with the right tools
* Learn how big data drives both evolutionary and revolutionary innovation, and who should be responsible
* Identify data collection and analysis opportunities and implement action plans
* Design the platform that suits your company's current and future needs
* Quantify performance with statistics, programming, and research for a more complete picture of operations
Effective management means combining data, people, and analytics to create a synergistic force for innovation and growth. If you want your company to move forward with confidence, Big Data, Big Innovation: Enabling Competitive Differentiation Through Business Analytics can show you how to use what you already have and acquire what you need to succeed.
eBook