Session 4 Decision Making.docx - w Session 4 Summary – Decision Making In this session we discussed three important questions How do people make

Session 4 Decision Making.docx - w Session 4 Summary –...

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w Session 4 Summary – Decision Making In this session, we discussed three important questions: How do people make decisions and why do we sometimes get derailed when we make decisions? What are some of the most important drivers of ineffective decision making that you may encounter in organizations? Finally, what can we do to improve our decision making? Decision making models: How are decisions made? We talked about the idea that our brain is trimmed to make decisions in the most efficient way since our resources, such as energy and time, are limited. Most of the time this works in our favour, but under certain circumstances this can lead to systematic decision-making biases. The Bounded Rationality Model of decision making recognizes that people have cognitive limitations, that information gathering is costly, and that we tend to be lazy when we make decisions. In other words, most people tend to make “good enough” decisions which can expose them to systematic errors. At the “input’ stage of the decision making process, people might suffer from incomplete information (like in our Carter Racing exercise), vague goals, or there might be environmental changes. This can make it challenging to effectively process information, preferences, and goals as they have to be constantly updated and questioned. At the “process” stage, people might suffer from cognitive and mental limitations, information overload (e.g., competing tasks), time pressure, and other distractors. These limitations can all influence people’s judgments, choices, and actions. Drivers of ineffective decision making We then talked about some of the fundamental forces that can cause people to make ineffective (and even sometimes dangerous!) decisions. At the individual level, we talked about the following biases: Selection bias: This bias happens when we conduct analyses on non-random data and fail to take into account flaws in the sample selection process. Think back to the temperature chart in Carter Racing or the way in which the Brits wanted to reinforce their planes. Changing the
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