"Just the understanding and insights you will pick up about how people encounter and cope with combinations of technical, social, political, and economic opportunities and challenges make the book a joy to read and worth much more than the price of it alone." --Barry Boehm, from the Foreword This practical handbook shows you how to build an effective business case when you need to justify--and persuade management to accept--software change or improvement. Based on real-world scenarios, the book covers the most common situations in which business case analyses are required and explains specific techniques that have proved successful in practice. Drawing on years of experience in winning the "battle of the budget," the author shows you how to use commonly accepted engineering economic arguments to make your numbers "sing" to management. The book provides examples of successful business cases; along the way, tables, tools, facts, figures, and metrics guide you through the entire analytic process. Writing in a concise and witty style, the author makes this valuable guidance accessible to every software engineer, manager, and IT professional. Highlights include: How and where business case analyses fit into the software and IT life cycle process Explanations of the most common tools for business case analysis, such as present-value, return-on-investment, break-even, and cost/benefit calculation Tying the business process to the software development life cycle Packaging the business case for management consumption Frameworks and guidelines for justifying IT productivity, quality, and delivery cycle improvement strategies Case studies for applying appropriate decision situations to software process improvement Strategic guidelines for various business case analyses With this book in hand, you will find the facts, examples, hard data, and case studies needed for preparing your own winning business cases in today's complex software environment.

Residents in Boston, Massachusetts are automatically reporting potholes and road hazards via their smartphones. Progressive Insurance tracks real-time customer driving patterns and uses that information to offer rates truly commensurate with individual safety. Google accurately predicts local flu outbreaks based upon thousands of user search queries. Amazon provides remarkably insightful, relevant, and timely product recommendations to its hundreds of millions of customers. Quantcast lets companies target precise audiences and key demographics throughout the Web. NASA runs contests via gamification site TopCoder, awarding prizes to those with the most innovative and cost-effective solutions to its problems. Explorys offers penetrating and previously unknown insights into healthcare behavior. How do these organizations and municipalities do it? Technology is certainly a big part, but in each case the answer lies deeper than that. Individuals at these organizations have realized that they don't have to be Nate Silver to reap massive benefits from today's new and emerging types of data. And each of these organizations has embraced Big Data, allowing them to make astute and otherwise impossible observations, actions, and predictions. It's time to start thinking big. In Too Big to Ignore, recognized technology expert and award-winning author Phil Simon explores an unassailably important trend: Big Data, the massive amounts, new types, and multifaceted sources of information streaming at us faster than ever. Never before have we seen data with the volume, velocity, and variety of today. Big Data is no temporary blip of fad. In fact, it is only going to intensify in the coming years, and its ramifications for the future of business are impossible to overstate. Too Big to Ignore explains why Big Data is a big deal. Simon provides commonsense, jargon-free advice for people and organizations looking to understand and leverage Big Data. Rife with case studies, examples, analysis, and quotes from real-world Big Data practitioners, the book is required reading for chief executives, company owners, industry leaders, and business professionals.

This book contains the extended and revised versions of selected papers from the Third International Symposium on Business Modeling and Software Design (BMSD 2013), held in Noordwijkerhout, The Netherlands, during July 8-10, 2013. The symposium was organized and sponsored by the Interdisciplinary Institute for Collaboration and Research on Enterprise Systems and Technology (IICREST), in cooperation with the Dutch Research School for Information and Knowledge Systems (SIKS), the Center for Telematics and Information Technology (CTIT), Aristotle University of Thessaloniki (AUTH), and AMAKOTA Ltd. The theme of BMSD 2013 was "Enterprise Engineering and Software Generation." The 13 full and 20 short papers presented at BMSD 2013 were selected from 56 submissions. The eight papers published in this book were carefully reviewed and selected from the 13 full papers. The selection includes papers touching upon a large number of research topics, ranging from more conceptual ones, such as modeling landscapes, process modeling, declarative business rules, and normalized systems to more practical ones, such as business-case development and performance indicators, and from more business-related topics, such as value modeling and service systems, to topics related to information architectures.

This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment. R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis. The main tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate. The supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway. What You’ll Learn Set up a business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholders Model the inherent uncertainties in the problem with Monte Carlo simulation using the R language Communicate the results graphically Draw appropriate insights from the results Develop creative decision strategies for thorough opportunity cost analysis Calculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysis Construct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available Who This Book Is For Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students

A good business case is so much more than simply the means to justify a decision. A well-written and well-researched business case will secure funding; make sure any project stays on the right side of regulation; mobilize support for the cause; provide the platform for managing the project and the benchmark against which to measure progress. Ian Gambles' Making the Business Case shows you how to make sense of the task at hand, develop a strategy, articulate your options, define the benefits, establish the costs, identify the risks and make a compelling case. Just as with the best business cases, the text is concise, jargon-free and easy to read; illustrated throughout with practical examples drawn from real cases and including reflective exercises at the end of each chapter to help you consolidate what you have learned. At only 198 pages long, this is a jewel of a book; essential reading for the manager tasked with making the business case, the senior manager who needs to understand and test it, and the project manager who is responsible for delivering whatever is agreed on.