Learn how to solve problems and achieve goals with data and communicate your results and recommendations clearly and persuasively.

The most persuasive & memorable way to communicate findings is storytelling. Data storytelling is a way to present data and insights using narratives. A compelling story can help in -actionability of ideas -audience engagement -disbelievers persuasion -stakeholders memorability -simplification of complex ideas In general it's proven that humanising data through stories makes them more relatable, while interactive data storytelling allows the audience to explore data, leading to deeper understanding.

To greatly help with decision making using data, you need to (1) visualise them but also (2) avoid common biases when interpreting them Visuals help since: -our brain can process them x60.000 faster than text -visuals can become +43% more persuasive when used in presentations -increases audiences willingness to read by +80% but also be careful since some common data fallacies are: -Correlation implies causation -Availability heuristic -Sample size fallacy -Confirmation bias -Model overfitting -Survivorship bias -Anchoring bias etc All these biases can negatively impact decisions even with perfect data

How do you support decisions with data and communicate effectively?

Making decisions based on data is a valuable skill in any field, but how do you ensure that your data is reliable, relevant, and understandable? And how do you communicate your findings and recommendations to others in a clear and persuasive way? In this article, you will learn some practical tips and tools to support your decisions with data and communicate effectively.

1 Define your problem and goal

Before you dive into data collection and analysis, you need to have a clear idea of what problem you are trying to solve and what goal you are trying to achieve. This will help you focus your data search and avoid getting overwhelmed or distracted by irrelevant information. You can use a simple framework like SMART (Specific, Measurable, Achievable, Relevant, Time-bound) to define your problem and goal and make sure they are realistic and actionable.

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2 Choose your data sources and methods

Depending on your problem and goal, you will need to select the appropriate data sources and methods to gather and analyze the data. You may use primary data (collected by yourself or your team) or secondary data (collected by others) or a combination of both. You may use quantitative data (numbers and statistics) or qualitative data (words and stories) or a mix of both. You may use descriptive, inferential, or predictive analytics to summarize, compare, or forecast the data. You should consider the validity, reliability, and bias of your data sources and methods and how they affect your results.

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3 Visualize and interpret your data

Once you have collected and analyzed your data, you need to present it in a way that is easy to understand and communicate. You can use various tools and techniques to visualize your data, such as charts, graphs, tables, maps, dashboards, or infographics. You should choose the best type of visualization for your data and audience and follow some best practices, such as using appropriate colors, labels, scales, and legends. You should also interpret your data and draw meaningful insights and conclusions from it. You should avoid jumping to hasty or biased assumptions and check for errors or outliers in your data.

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Michalis (Mike) Konstantoulakis

Director of BI & Insights @efood || "that greek guy talking about Data & stuff.." || Mentor
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To greatly help with decision making using data, you need to (1) visualise them but also (2) avoid common biases when interpreting them Visuals help since: -our brain can process them x60.000 faster than text -visuals can become +43% more persuasive when used in presentations -increases audiences willingness to read by +80% but also be careful since some common data fallacies are: -Correlation implies causation -Availability heuristic -Sample size fallacy -Confirmation bias -Model overfitting -Survivorship bias -Anchoring bias etc All these biases can negatively impact decisions even with perfect data

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4 Communicate your findings and recommendations

The final step is to communicate your findings and recommendations to your stakeholders, such as your boss, colleagues, clients, or customers. You should tailor your message and format to your audience and purpose and use clear and concise language and visuals. You should also tell a compelling story with your data and explain how it relates to your problem and goal and what actions or decisions you suggest. You should anticipate and address any questions or objections that your audience may have and provide evidence and logic to support your claims.

Add your perspective

Michalis (Mike) Konstantoulakis

Director of BI & Insights @efood || "that greek guy talking about Data & stuff.." || Mentor
Report contribution
The most persuasive & memorable way to communicate findings is storytelling. Data storytelling is a way to present data and insights using narratives. A compelling story can help in -actionability of ideas -audience engagement -disbelievers persuasion -stakeholders memorability -simplification of complex ideas In general it's proven that humanising data through stories makes them more relatable, while interactive data storytelling allows the audience to explore data, leading to deeper understanding.

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5 Seek feedback and improve

Data-driven decision making is not a one-time process, but a continuous cycle of learning and improvement. You should seek feedback from your audience and evaluate the impact and effectiveness of your decisions and actions. You should also monitor and update your data and methods as the situation changes and new information becomes available. You should always look for ways to improve your data quality, analysis, and communication skills and learn from your successes and failures.

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6 Use online tools and resources

There are many online tools and resources that can help you support your decisions with data and communicate effectively. For instance, Google Data Studio is a free tool that enables you to create and share interactive dashboards and reports with data from multiple sources. Tableau is a powerful tool for exploring, visualizing, and analyzing data, as well as creating attractive charts and graphs. Canva is an easy-to-use tool that assists in designing professional-looking infographics and presentations. DataCamp is an online platform that provides courses and projects on data science and analytics skills and tools. Coursera is another online platform that offers courses and certificates on various topics, including data-driven decision making and communication.

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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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How do you support decisions with data and communicate effectively?

1

2

3

4

5

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1 Define your problem and goal

2 Choose your data sources and methods

3 Visualize and interpret your data

4 Communicate your findings and recommendations

5 Seek feedback and improve

6 Use online tools and resources

7 Here’s what else to consider

Decision-Making

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How do you support decisions with data and communicate effectively?

1

2

3

4

5

6

7

1 Define your problem and goal

2 Choose your data sources and methods

3 Visualize and interpret your data

4 Communicate your findings and recommendations

5 Seek feedback and improve

6 Use online tools and resources

7 Here’s what else to consider

Decision-Making

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