What are some ways to identify and analyze insurtech data using critical thinking?

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Insurtech data is a valuable asset for insurance professionals who want to improve their products, services, and customer experience. However, data alone is not enough to generate insights and solutions. You also need to apply critical thinking skills to identify, analyze, and evaluate the data and its implications. In this article, you will learn some ways to use critical thinking to enhance your insurtech data analysis.

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Jacy Johnson

BI Workhorse

1 Define the problem

The first step in critical thinking is to define the problem you want to solve or the question you want to answer with the data. This will help you narrow down your focus, set your objectives, and identify your assumptions and criteria. For example, if you want to improve customer retention, you need to define what retention means, how you measure it, and what factors influence it.

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Jacy Johnson

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The generation of a hypothesis begins with induction, which depends on active awareness in observation. Induction further demands our thoroughgoing analysis of how the mechanics of the hypothesis might manifest in reality. We cannot assume that the mechanism we suppose or the model we provisionally create is itself the reality.

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2 Gather relevant data

The next step is to gather the data that is relevant to your problem or question. This may involve collecting data from various sources, such as internal databases, external platforms, surveys, interviews, or social media. You need to ensure that the data is reliable, valid, and up-to-date. You also need to check for any gaps, biases, or errors in the data that may affect your analysis.

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Jacy Johnson

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Never mistake the data model for the data set. The points on the graph are the data; the lines connecting them, the tick marks, the averages, the smoothing we apply all confuses the model for the data. Our worst errors take place at the data conversion step, because we mistake our mental aids for the data.

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3 Analyze the data

Once you have the data, you need to analyze it to find patterns, trends, correlations, or outliers that may provide insights or answers. You can use different methods and tools to analyze the data, such as descriptive statistics, inferential statistics, visualization, or machine learning. You need to apply logic, reasoning, and evidence to support your analysis and avoid fallacies or cognitive biases.

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Jacy Johnson

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No single method, tool, system or approach can meet every data challenge. We must therefore remain thoroughly skeptical of what we bring to the data. We often too quickly apply our "fixes" to the data to make it conform to our expectations: outliers are ignored, correlations are deemed impotent, moving averages are applied and damage is done to the data until we have made a textbook distribution that bears no resemblance to our underlying data set.

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4 Evaluate the results

The final step is to evaluate the results of your analysis and see how they relate to your problem or question. You need to assess the strengths and weaknesses of your results, the limitations and implications of your data, and the assumptions and criteria you used. You also need to compare your results with other sources, perspectives, or alternatives and see if they are consistent or contradictory.

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Jacy Johnson

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Hypothesis testing requires us to be willing to actually modify that hypothesis, and to not depend on our childhood comforts like p-values to do all the thinking on our behalf.

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5 Communicate the findings

After you evaluate the results, you need to communicate your findings to your stakeholders, such as customers, colleagues, managers, or partners. You need to tailor your communication to your audience, purpose, and context. You need to use clear, concise, and accurate language and visuals to convey your message and recommendations. You also need to acknowledge any uncertainties or risks and invite feedback or questions.

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Jacy Johnson

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If you actually understand what you measured, you should have no issue communicating that to other teams. If you struggle to reword a metric or segment into an understandable alias for your customers, you likely have measured the wrong thing.

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6 Reflect and improve

The last step in critical thinking is to reflect on your process and outcome and see how you can improve them. You need to review your data analysis and identify what worked well and what did not. You need to learn from your mistakes and successes and apply them to your future projects. You also need to update your data and analysis as new information or changes occur.

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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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What are some ways to identify and analyze insurtech data using critical thinking?

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1 Define the problem

2 Gather relevant data

3 Analyze the data

4 Evaluate the results

5 Communicate the findings

6 Reflect and improve

7 Here’s what else to consider

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