How do you communicate and visualize your anomaly detection results to stakeholders and clients?

1 Understand your audience

Before you create any charts or reports, you need to understand who your audience is and what they care about. Are they technical experts, business managers, or end users? What are their goals, expectations, and pain points? How do they use or benefit from the data? How do they prefer to receive information? By answering these questions, you can tailor your message and format to suit their needs and interests.

2 Choose the right metrics and methods

Depending on your data and your objective, you may use different metrics and methods to measure and detect anomalies. For example, you may use standard deviation, z-score, moving average, interquartile range, or machine learning algorithms. You should explain why you chose a certain metric or method, how it works, and what assumptions or limitations it has. You should also provide some context and benchmarks to help your audience understand the scale and significance of the anomalies.

3 Visualize the anomalies clearly and intuitively

One of the most effective ways to communicate and visualize your anomaly detection results is to use graphs or charts that show the time series data and the anomalies. You can use different colors, shapes, or symbols to highlight the outliers and make them stand out from the normal data. You can also use annotations, labels, or captions to provide additional information or insights about the anomalies. You should choose a type of graph or chart that matches your data and your message, such as line charts, bar charts, scatter plots, or heat maps.

4 Explain the causes and implications of the anomalies

Besides showing the anomalies, you should also explain what caused them and what they mean for your stakeholders or clients. You should provide evidence or hypotheses to support your explanations, such as external factors, data quality issues, or changes in behavior or demand. You should also discuss the implications or recommendations based on your findings, such as potential risks, opportunities, or actions to take. You should use clear and concise language and avoid jargon or technical terms.

5 Solicit feedback and questions

Finally, you should solicit feedback and questions from your audience to ensure that they understand and appreciate your anomaly detection results. You should invite them to share their opinions, concerns, or suggestions, and address any doubts or objections they may have. You should also acknowledge any limitations or uncertainties in your analysis, and explain how you plan to improve or refine it in the future. By engaging your audience in a dialogue, you can build trust and rapport, and demonstrate your value and expertise.

6 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?