#15 Communicating Data Insights to Non-Technical Stakeholders

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📊 Effective Communication of Data Insights

The ability to communicate data insights effectively is a crucial skill for data professionals. However, conveying complex data findings to non-technical stakeholders can be challenging.

The key is to present data in a clear, concise, and compelling manner that facilitates informed decision-making at all organizational levels. This guide explores techniques and best practices for achieving this, ensuring your data presentations are impactful and accessible.

Here are key techniques and best practices for achieving this:

🧑‍🤝‍🧑 Know Your Audience

Understanding your audience is the first step in effective communication. Tailor your message to meet their specific needs and preferences:

• Identify Stakeholders: Determine who will be using the data and what their background is. Knowing whether they are executives, managers, or frontline staff can help you tailor the depth and complexity of your presentation.

• Focus on Relevance: Highlight data that directly impacts their goals and responsibilities. For example, if presenting to marketing, focus on customer insights and campaign performance metrics.

🧩 Simplify Complex Data

Simplifying data does not mean dumbing it down; it means making it understandable:

• Avoid Jargon: Use plain language and avoid technical terms that might confuse your audience.

• Highlight Key Insights: Focus on the most critical data points and insights.

📊 Data Visualization

Visual aids can make data more digestible and engaging:

• Choose the Right Visualization: Select the appropriate chart or graph type (e.g., bar charts for comparisons, line charts for trends). Use pie charts for parts of a whole, scatter plots for correlations, and heat maps for performance intensity.

• Keep It Simple: Avoid clutter and keep visuals straightforward and to the point. Ensure your charts and graphs are easy to read and interpret at a glance.

📖 Storytelling with Data

Data storytelling is a powerful way to make data relatable:

• Craft a Narrative: Structure your presentation with a clear beginning (the problem), middle (the analysis), and end (the solution). Start with a hook to grab attention, then delve into the data, and finally, conclude with actionable insights.

• Use Storytelling Techniques: Engage your audience with relatable stories that illustrate your data points. Use real-world examples and analogies to make complex data more understandable.

🏫 Case Study: HBR

Here’s an example from Harvard Business Review’s data visuals section on how they present their images and statistics to the outside world. The visual comparison highlights the differences in the increase in business establishment entries from 2019 to 2022.

Key Elements of Effective Visualization:

1. Comparative Data Representation:

   • A grid of small multiples allows viewers to easily compare the growth trends across different countries.

2. Consistent Y-Axis:

   • Each chart uses the same y-axis scale, ensuring that the comparisons are visually accurate and not misleading. This consistency helps in understanding the relative magnitude of changes between countries.

3. Prominent Data Points and Trend Lines:

   • The percentage change is prominently displayed on each chart (e.g., 34% for the United States, 25% for Belgium). The green trend lines effectively show the upward or downward trajectory of business establishment entries.

HBR’s image exemplifies effective data visualization by combining clear and concise textual information with visually engaging and easy-to-interpret graphics.

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 📰 Data Tools, Articles and Resources 

1. Average Day In A Data Analyst’s Life

2. Building Dashboards That Tell Stories

3. What 10 Years at Uber, Meta and Startups Taught Me About Data Analytics

4. Awesome Strategies to Visualize Change with Time