Biases in Decision Making
Chapter 1: Introduction to Data-Driven Decision Making
Data-driven decision making can revolutionize an organization, as demonstrated by the story of the Oakland A's baseball team in the early 2000s. The team's new general manager, Billy, introduced data-driven decision-making which resulted in the team breaking the world record of 20 consecutive wins in the Baseball League. This was achieved despite a significantly lower budget compared to other teams.
Chapter 2: Identifying Biases in Decision Making
Biases can significantly impact decision making. In Moneyball there is a scene, where seasoned experts rely on patterns they have learned over the years to make decisions, similar to how an AI works. It is important to question if decisions are based on enough supporting data and to identify any decisions in your company that you are taking lacking sufficient underlying data support.
Chapter 3: Dealing with Ambiguity and Uncertainty in Decision Making
The Elsberg Paradox is a game that challenges your intuition and logic on how you deal with ambiguity and uncertainty in decision making. The game reveals that most people have an aversion to uncertainty, leading them to make irrational decisions.
Chapter 4: Recognizing Common Biases
Several biases can be found in decision-making, especially among managers. These include:
- Similarly Assumptions: Viewing new situations as overly similar to those encountered before.
- Overconfidence Bias: Belief that one's views on the situation are accurate.
- Discounting Alternative Views: Belief that others’ views are less valid than one's own.
- The "fundamental attribution error": Automatic causal reasoning in which others’ shortcomings have internal causes while one’s own failures have external causes.
These biases should not always be avoided as they can be useful tools to simplify complex situations. However, it's important to be aware of them and reflect on their impact.
Chapter 5: Using Biases to Shape Decision-Making Culture
Amazon is a company that uses biases to influence the culture of decision making within their leadership. These biases are encoded in their leadership principles and are used to shape the culture of the company, pushing an innovation culture within a large corporation. Some of these principles even seemingly contradict each other, challenging leaders to reflect.
Chapter 6: Defining a Unifying KPI
Finding a unifying KPI to guide the decision making within a team or company provides clarity in guidance. In the case of the Oakland A's, the unifying KPI was "how often does the player get to base per dollar spend". This KPI guided the team's strategy in buying players, focusing on finding under-valued players that provide the best value for money.
Chapter 7: Implementing Data-Driven Decision Making
Implementing data-driven decision making involves hiring data scientists to crunch data and make informed decisions. However, this transformation is not easy and can create opposition as it threatens the way things are done.
Key Learnings:
- Be aware of your biases – conscious and unconscious. Reflect on their impact on decision-making.
- Not all biases are bad. They can effectively guide your team’s decision-making culture.
- Be clear about the problem and the question to ask.
- Find your guiding metrics – they can serve as a North Star.
- Implementing data-driven decision making can create opposition, but it's a necessary step for transformation.
Further discussions on topics such as a data-driven decision-making process, noise, correlation vs causation are needed to fully understand and implement data-driven transformation in a company.