You may have heard the Native American proverb about stories. "Tell me a fact and I'll learn. Tell me a truth and I'll believe. But tell me a story and it will live in my heart forever." Storytelling is a huge part of the human experience. But there are often multiple stories hidden within one data set. It’s important to remember that data is less often about telling a specific story and more like starting a guided conversation and letting the user find the story that fits their need. Think dialogue instead of monologue!
When communicating with data, your product should pose a problem and deliver insight to lead the audience to take action. Do you remember the Choose Your Own Adventure Series? These children’s books were very popular in the 80’s and 90’s, allowing the reader to become part of the story. They are a great example of how to turn a linear story or monologue into flexible dialogue or a guided conversation. As the main character, you were able to take in the information provided and take action by deciding what to do from two or three options. Each of which led to more options, and then to one of many endings.
Now, that you’re geared up to put those critical thinking skills to use, let’s make sure you have the principles to help you design for guiding the conversation.
1. Find the purpose and message of your data products and know your audience. Know what information is most critical for your audience's decision-making, and what questions they need answered to be more successful. Ask:
What outcome are you looking for?
What do you hope to change in your organization by creating this report, dashboard or analysis tool?
As you design the data product, understanding the audiences can help you craft a product that fits their needs and is something they love to use.
2. Be discriminating with what data you present. The most common mistake in data products is the inability to make decisions on what information is most important. This lack of focus often results in a directionless and sprawling document -- drowning your audience in data. Remember, you know the data and you know your audience. Distinguish between what is simply interesting and what is really relevant.
3. Define metrics that are meaningful and can lead to action. Metrics are the values that you use to judge performance. They are the numerical reflection of the real-world behavior that your organization wants to improve, avoid, or shape. Metrics create focus and alignment in an organization by providing clarity on what improvement looks like. Metrics can also create behaviors that are counter-intuitive or contrary to organizational goals. Only the right metrics and most actionable data should be featured in a data product to make the most of your audience's attention.
4. Create a logical structure and narrative flow for your data product.
How you choose to lay out the information shapes how your audience understands the big picture and how the smaller pieces fit together. Ask:
What is the general structure of the content you want to communicate?
How does the content connect?
How does one data or visualization element flow into the next?
Whether it is a dashboard or a data-rich presentation, the structure of your data product is an opportunity to define the logical way to look at a problem or the business.
5. Master basic design skills for making your data presentation attractive and easy to understand, including choosing the right form and language to present the data. Your next challenge is to consider how the data looks, in what form it is delivered, and how words are best incorporated to facilitate understanding. You can start this process by considering factors that will influence the format in which you present the data:
Timeliness - How frequently is that data updated?
Aesthetic value - How important is if that the data presentation looks attractive, or can it be purely utilitarian?
Mobility - Does the audience need to access the information through mobile devices?
Connectivity - Does the dashboard need to connect to live data sources or can it be updated on a less frequent basis?
Data detail - Will the data product offer a capability to drill down to see more context?
Data density - How information-rich will views of the data be?
Interactivity - Will the user benefit from interacting with the data?
Collaboration - Is it important that your audience can easily share and collaborate with others about the data?
6. Create data products that serve a broader audience and start a dialogue.
These products do not simply facilitate the flow of information between people. They also add tremendous value to the data they are communicating by analyzing, summarizing, structuring, storytelling, visualizing, and contextualizing. It takes many diverse skills to be good at designing data products.
Begin with these principles and start a dialogue around your data in a logical and structured way! Find out more on guiding the conversation around your data from our book, Data Fluency.
Excerpted with permission from the publisher, Wiley, from Data Fluency: Empowering Your Organization with Effective Data Communication by Zach Gemignani, Chris Gemignani, Richard Galentino, Patrick Schuermann. Copyright © 2014.