# Storytelling With Data Part I

"Stories have been used to dispossess and malign, but stories can also be used to empower and to humanize. Stories can break the dignity of a people, but stories can also repair that broken dignity."
— Chimamanda Ngozi Adichie, The Danger of a Single Story, TED Talk

There are many wonderful people out there creating content and enablement material (practical wisdom) about storytelling with data. Brent Dykes wrote an excellent book called, Effective Data Storytelling and Cole Nussbaumer Knaflic has published multiple books; Storytelling With Data and recently, Storytelling With You.

What I will say here in this article is this: 1) get and read those books and 2) start by telling your data story. What do you measure, monitor, and track? For me, I religiously track my spend on fuel in a smartphone app that tracks gas mileage. I can look at this app’s dashboard for my vehicle and tell you exactly (I have missed a few fill ups) how much I spent on fuel in the last 182,000 miles. I can tell you how much I have spent (approximately) on fuel in the last 10 years. This app tells me a lot and has many more capabilities to track maintenance like oil changes and tires. Why do I use it? I have been tracking different things since I figured out how to use spreadsheets…. It’s a thing I do! But… through that experience, I reckon (John Dutton voice) it is helpful to share your data story with other people. This will help us all practice and find common language.

Jordan Morrow writes in his book, Be Data Literate, about the lack of a common language with regard to data. He also talks about the four levels of analytics; descriptive, diagnostic, predictive, and prescriptive and the three Cs - which I’ll cover later in Part III. When we frame things using these four levels, we can identify our common language.

The gas mileage app is providing me with descriptive analytics about spend, fuel consumption, vehicle wear and tear, and maintenance. If the mile per gallon suddenly drops, we can ask why and look for an answer. Was it because of headwinds, towing, or because I was late and driving fast. (Of course I would never speed!)

Based on these insights, I can predict how much I will spend on fuel next month or next year.

As you read in the beginning of this writing, I attempted to capture your interest and attention with my data story. As you find new ways to share how you consume and generate data, you also begin developing new ways of hearing data stories. The US Census made a lot more sense to me when I learned more about how data is collected and used. This becomes incredibly important when it comes to demographics or social profiles. As these skills develop, one might see Facebook, TikTok, and other social media apps a little differently simply based on the fact that your data is being used for their financial gain. But I digress!

Stories are powerful as you read in this section’s opening quote. Chimamanda accurately points out that stories are so powerful that they can replace governments, marginalize groups or individuals, or create division where there might not be (or not as much).

With so many stories and attempts to capture your attention, we—as people—tend to become overwhelmed. There is a lot of noise, many signals, and sometimes too many options. How do we decide?

"A wealth of information creates a poverty of attention."
— Herbert A. Simon, Economist and Political Scientist

As individuals, we often make tough decisions based on our values and ethics. These core beliefs guide us and help us navigate difficult situations. Similarly, in business, we rely on frameworks, standards, protocols, and processes to guide our decision-making. We may measure our progress against established baselines to ensure that we are on track.

When it comes to discussing data and insights, it is important to provide context and background information to help listeners understand and calibrate their thinking. For example, if we are discussing cybersecurity capabilities, we might use the MITRE ATT&CK framework to describe our progress in preventing lateral movement. By providing a clear and concise description of the insights being discussed, and how they align with a well-known framework or baseline, we can enable others to make informed decisions.

In today's world, it is crucial that we learn to identify and call out misinformation. Misinformation and propaganda have always been present, but with the proliferation of digital media, it is more important than ever to be able to distinguish between reliable and unreliable sources. By establishing a common language and understanding, we can have more meaningful and effective communication and discussions.

"It is a capital mistake to theorize before one has data."
— Sherlock Holmes A Study in Scarlet, Arthur Conan Doyle

# Storytelling with Data: The Importance of Considering the User

The success of any data storytelling lies in its ability to engage and reach the emotion of the audience. It is crucial to consider who your audience is and tailor your presentation accordingly. While a technical audience with a high level of data literacy may be able to comprehend more complex language and visualizations, a non-technical audience may require simpler explanations, basic data visualizations, or a walk-through of what’s being presented. Using metaphors and analogies are very helpful tools when customizing your presentation or content.

It is also essential to consider their goals, interests, and motivations. What do they hope to learn from the data? How can the insights from the data be applied to their needs? By aligning your data storytelling with the audience's needs and interests, you can create a relevant and engaging story or presentation that effectively communicates the value of the data.

Finally, when considering the context of the data, user stories can also be used to identify key insights and actionable steps that can be taken based on those insights. This helps to make the data more valuable and applicable to your audience, and helps them understand the implications of the data.