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"Strategy, risk management and project management are often considered separately by those applying their principles--but at their most effective, all are dependent upon each other for success. Enlightened Planning teaches this holistic perspective and demonstrates how a synthesis of these approaches yields far greater opportunities. A strategic, calculated risk, for example, can be less inherently risky than chronic risk-aversion over time. Here, a respected specialist and teacher demonstrates how to become an "enlightened planner"; one that is aware of project, strategy and risk concerns, and their potential interplay. Following the core principle of Keep It Simple Systematically, he shows how organised, systematic thought processes can demystify the complexities of decision-making when considering a huge variety of concerns at once. Supported throughout with real-life cases from the author's considerable experiences with commercial organisations, it is also supported by a website containing even more cases, learning and teaching materials. This book is essential reading for any practitioner specialising in risk management, project management or strategy; as well as those teachers or participants in executive programmes"--

Project management. --- Risk management. --- Decision making.

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Business policy --- Project management --- Risk management --- 65.012.4 --- Insurance --- Management --- Industrial project management --- 65.012.4 Management. Directorate. Technique and methods of management --- Management. Directorate. Technique and methods of management --- Project management. --- Risk management. --- Social Sciences and Humanities. Management studies, Business Administration, Organizational Science --- Management studies, Business Administration, Organizational Science (General).

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This book is your definitive guide to the rapidly growing role of Quantitative User Experience (Quant UX) Research in product development. The book provides an overview of the skills you need on the job, presents hands-on projects with reusable code, and shares advice on starting and developing a career. The book goes beyond basic skills to focus on what is unique to Quant UX. The authors are two of the most widely recognized practitioners in Quant UX research, and this book shares insights from their combined decades of experience. Organizations today have more data about user needs and behaviors than ever before. With this large-scale data, Quant UX researchers work to understand usage patterns, measure the impact of design changes, and inform strategic decisions. In the Quant UX role, interdisciplinary researchers apply analytical skills to uncover user needs, inform engineering and design, answer strategic business questions, and optimize software and hardware products for human interaction. This book provides guidance around customer satisfaction surveys, understanding user behavior from log analysis, and the statistical methods that are commonly used to assess user outcomes. What You Will Learn Discover the role of Quantitative User Experience (Quant UX) research Understand how Quant UX research differs from other disciplines such as data science Plan common research projects and know how to achieve success Position Quant UX activities in product development, engineering, and UX organizations Apply the HEART framework to measure user experience outcomes Evaluate your skills and potential to be hired as a Quant UX researcher Know what to expect during job interviews Find examples of common Quant UX projects with shared R code and data sets.

Artificial intelligence --- Quantitative research. --- Data Science. --- Data Analysis and Big Data. --- Data processing. --- Artificial Intelligence --- Information Theory --- Computers

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Banks and banking --- Data processing

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This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

Statistics. --- Statistics for Business/Economics/Mathematical Finance/Insurance. --- Statistics and Computing/Statistics Programs. --- Marketing. --- Mathematical statistics. --- Economics --- Statistique --- Statistique mathématique --- Marketing --- Mathematics --- Physical Sciences & Mathematics --- Mathematical Statistics --- R (Computer program language) --- Marketing research --- Statistical methods. --- GNU-S (Computer program language) --- Domain-specific programming languages --- Statistics for Business, Management, Economics, Finance, Insurance. --- Consumer goods --- Domestic marketing --- Retail marketing --- Retail trade --- Industrial management --- Aftermarkets --- Selling --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Econometrics --- Statistics . --- R (Computer program language).