Data-driven decision-making     
Effective communication of engineers to management is critical for data-driven decision-making. However it is a challenging task as they almost don't speak the same language:
  • engineers can be too tech-savvy and not have enough focus on the "so-what" of their analyses, missing the forest for the trees
  • management can oversee the subtleties of the analysis and press for cartoonish statements

Here are three strategies that can help you effectively communicate complex data insights to a non-technical audience:

Use simple language and make analogies

Use clear and concise language, avoid technical jargon or complex terminology that may be unfamiliar to your audience. Analogies and metaphors can be a powerful tool to explain the data in a relatable way. For example, if you're communicating insights about website traffic, you can use the analogy of a physical store. Unique IP's become new customers, page views are product views, a sales funnel can be customers moving from room-to-room. Einstein had a powerful quote related to this: "If you can't explain it to a six-year-old, you don't understand it yourself"

1 picture is worth 1000 words

Charts, graphs, and diagrams are the most powerful tool to help you to convey complex insights to non-technical stakeholders. They can illustrate trends, relationships or complex patterns in an instant, whereas a text description would long and laborious. It's important to choose formats that are easy to understand. Where possible stick to basic line or column graphs and avoid the more complex dual-axes plots or histograms. Keep your layouts clean and concise (and never forget the units!), use color coding or labels to help distinguish different data types. Also, keep in mind that different visual aids work better for different types of data insights. For example, a line chart may be suitable for displaying trends over time, while a scatter plot may be more appropriate for analyzing relationships between variables.

At Sense6 we use Grafana and Python Plots to present our data in an effective way, and so far, we can highly suggest these tools. We already have several blog posts about Grafana, you can check them out here and here as well as about data visualization use-cases that you can find here and here.

Focus your message to your audience

A byproduct of a good analysis is the breadth of insights that are available for discussion, which makes it easy to overwhelm your stakeholders. Therefore it is especially important to understand your audience and what they want to get out of the analysis. Focus your message and graphs relentlessly, and resist the urge to show all the details. Different stakeholders have different priorities, concerns, and levels of technical expertise, and therefore will require different types of information. Your communication of the analysis must change depending on who you present to.

A crucial part of Sense6 (and any data-analytics company) is not only to generate strong analyses, but also to deliver impactful high-quality presentations to enable our customers to move forward. We hope the above points serve you well. If you are interested in what else we do, or if you have any suggestions, feel free to reach out.
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