Decision analysis for managers : a guide for making better personal and business decisions / / David Charlesworth.

• Superior document: Quantitative approaches to decision making collection,
• Author: Charlesworth, David.
• Year of Publication: 2013
• Edition: 1st ed.
• Language: English
• Series: 2013 digital library.; Quantitative approaches to decision making collection.
• Physical Description: 1 electronic text (x, 134 p.) :; digital file.
• Notes: Part of: 2013 digital library.

Everybody has to make decisions--they are unavoidable. Yet we receive little or no education or training on how to make decisions. Business decisions can be difficult: which people to hire, which product lines or facilities to expand and which to sell or shut down, which bid or proposal to accept, which process to implement, how much R&D to invest in, which environmental projects should receive the highest priority, and so on. Even if you make the correct decision, you still have to get buy-in and commitment from your team, other management, and key stakeholders to successfully implement the decision. Personal decisions can be even more difficult: which college to attend, who to date, who to marry, which automobile to buy, which house to buy, whether to change jobs or not, where to go on vacation, when and where to retire, how to handle and treat a serious illness or health problem, and so on. Decision analysis (DA) is a time-tested set of tools (mental frameworks) which will help you and the teams you work with clarify and reach alignment on goals and objectives and understand trade-offs in reaching those goals, develop and examine alternatives, systematically analyze the effects of risk and uncertainty, and maximize the chances of achieving your goals and objectives.

Table of Contents

Acknowledgments -- Preface -- What is decision analysis? And why should I care? -- How to start framing a DA problem: how can we work together? -- The objectives hierarchy: what do we want? -- Decisions and alternatives: what can we do? -- Influence diagrams: what do we know? -- Uncertainty assessment: the boundary between known and unknown -- Building a deterministic model: time to run the numbers -- Tornado diagrams: figuring out what is important -- Cumulative probability: looking at the range of outcomes -- Value of information: how much is it worth to know? -- Multiattribute decision analysis: there's more to life than money -- Other topics: more things to think about -- Notes -- References -- Index.