How do you manage information overload and cognitive biases in analytics?

Information overload and cognitive biases are two common challenges that can affect your analytical skills and decision making. Information overload occurs when you have too much data or information to process, while cognitive biases are mental shortcuts or errors that distort your perception or interpretation of reality. In this article, you will learn some practical tips on how to manage these challenges and improve your analytical skills.

1 Define your problem and goal

The first step to manage information overload and cognitive biases is to clearly define your problem and goal. What are you trying to achieve or solve with your analysis? What are the key questions or hypotheses that you need to test or answer? By defining your problem and goal, you can narrow down your scope and focus on the relevant information and criteria that matter for your analysis.

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Sacha Cornuault

Research Consultant, NeuroLeadership Institute | Neuroscience and strategy for business growth.
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By setting clear boundaries, your mind can sift through vast datasets, identifying only pertinent chunks. This precision not only streamlines your analytical approach but also minimizes distractions. One method I often utilise is “The 5-Whys Technique.” It helps peel back layers of a problem, making the core objective unmistakably evident.

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2 Evaluate your sources and data

The next step is to evaluate your sources and data for their quality, reliability, and validity. Where did you get your data or information from? How accurate, complete, and current is it? How does it relate to your problem and goal? How can you verify or cross-check it? By evaluating your sources and data, you can avoid using unreliable or irrelevant information that can lead to false or misleading conclusions.

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Jeremy Levin

I help - I train - I analyse - I nerd ... a lot. I like to verb when I can. It's better than nouning.
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CSU Chico's "CRAAP" model (Currency, Relevance, Authority, Accuracy, Purpose) is great for this. It also has the added benefit of being able to ask "how CRAAPy are my sources," which always gets a giggle ... but also makes it memorable. And, if it's memorable, it's more likely to be considered and used.

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3 Apply critical thinking and logic

The third step is to apply critical thinking and logic to your analysis. Critical thinking is the ability to analyze, evaluate, and synthesize information objectively and rationally. Logic is the system of rules and principles that guide your reasoning and arguments. By applying critical thinking and logic, you can avoid fallacies, assumptions, and biases that can impair your judgment and reasoning.

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Sacha Cornuault

Research Consultant, NeuroLeadership Institute | Neuroscience and strategy for business growth.
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Every piece of data can be seen as a neural signal; it’s your job to decode its importance. Infuse your analysis with a robust blend of critical thinking and logic. This enables to differentiate between noise and genuine insights, ensuring that decisions are made on a foundation of rationality rather than emotion.

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4 Recognize and mitigate your biases

The fourth step is to recognize and mitigate your biases. Biases are the tendencies or preferences that influence your perception or interpretation of reality. They can be conscious or unconscious, and they can affect your analysis in various ways. For example, confirmation bias is the tendency to seek or interpret information that confirms your existing beliefs or expectations, while anchoring bias is the tendency to rely too much on the first piece of information that you encounter. By recognizing and mitigating your biases, you can reduce their impact on your analysis and decision making.

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Sacha Cornuault

Research Consultant, NeuroLeadership Institute | Neuroscience and strategy for business growth.
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Remember, if you have a brain, you have biases. Familiarise yourself with common biases and make a concerted effort to counteract them. Periodically question: “Am I seeing what I want to see, or what’s actually there?” A valuable technique I’ve adopted is peers reviewing each other’s work, to identify potential blind spots.

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5 Seek feedback and diverse perspectives

The fifth step is to seek feedback and diverse perspectives on your analysis. Feedback is the information or opinions that you receive from others about your analysis. Diverse perspectives are the different viewpoints or approaches that others have on your problem or goal. By seeking feedback and diverse perspectives, you can improve your analysis by learning from others' experiences, insights, and criticisms.

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6 Review and refine your analysis

The final step is to review and refine your analysis. Reviewing your analysis means checking it for errors, gaps, or inconsistencies. Refining your analysis means improving it by adding, removing, or modifying information or criteria. By reviewing and refining your analysis, you can ensure that it is clear, coherent, and comprehensive.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Jeremy Levin

I help - I train - I analyse - I nerd ... a lot. I like to verb when I can. It's better than nouning.
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Information overload often leads to bias: when facing too much data, we gravitate toward data that supports our preconceptions. Instead, answer questions - one valuable, overarching question providing the analytic theme, broken down into sub-questions, i.e. "what do I need to know to be able to answer this?" Use these sub-questions to narrow the scope of your research and focus on answering smaller questions to make the data bulk more manageable.

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Sacha Cornuault

Research Consultant, NeuroLeadership Institute | Neuroscience and strategy for business growth.
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Analytics isn’t solely about crunching numbers. It involves empathy, intuition, and an understanding that behind every data point lies a human story. Embrace tools that helps in decluttering data, but also remember the human element in every analysis. It is important to take breaks during data deep-dives to engage in a completely unrelated activity. This provides a neural reset, often leading to clearer, more innovative insights upon return.

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How do you manage information overload and cognitive biases in analytics?

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3

4

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1 Define your problem and goal

2 Evaluate your sources and data

3 Apply critical thinking and logic

4 Recognize and mitigate your biases

5 Seek feedback and diverse perspectives

6 Review and refine your analysis

7 Here’s what else to consider

Analytical Skills

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How do you manage information overload and cognitive biases in analytics?

1

2

3

4

5

6

7

1 Define your problem and goal

2 Evaluate your sources and data

3 Apply critical thinking and logic

4 Recognize and mitigate your biases

5 Seek feedback and diverse perspectives

6 Review and refine your analysis

7 Here’s what else to consider

Analytical Skills

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