A Reflection on Part One - Telling Stories With Data

Photo by Pixabay from Pexels

In reading through the introduction of ‘Telling Stories With Data’ by Rohan Alexander (2021) a few notions came to mind that I thought pertinent to share. Data contain a story. The numbers are not just purely objective measures of reality. They are a reflection of the way in which we understand and interact with the world. It is important to understand when communicating using data that we are presenting the story within that data. Or, at least a story. There are important things then to consider when telling a story of data to ensure that an accurate story is being told. Not just the story we wish to be told. Moreover, we need to recognize that in being told what data mean we are in turn being told a story.

It is crucial to understand that with data we must tell the story the data is telling, not the story we wish to tell. Do not fit the evidence to your narrative, let the evidence guide the narrative. The legendary baseball player Henry “Hammerin’ Hank” Aaron passed away this January 22nd. In many memorial messages towards Mr. Aaron he was remembered for his grace in the face of racism through his chasing and surpassing Babe Ruth’s home run record. That he ignored the racism levelled against him with stoic dignity. However, in his autobiography, Mr. Aaron writes of how the experience in surpassing Ruth left a foul taste in his mouth and tarnished baseball for him (William Davis, 2021). While what is presented is the mythologized image of a Black man confronting racism with stoicism and grace, what in actuality is happening is the erasure of the experiences of a Black man for the purposes of narrative. The data are being used to tell a story, while the story of the data is not being told.

In reflecting on ‘Telling Stories With Data’ (Alexander, 2021), I would like to add to the apt comparison of writing quantitative analysis to writing fiction (2021). That to study your favourite creative pieces and not only consider the analogous fiction elements of character, plot, setting, theme, and style when writing quantitative analysis. Study your favourite books, films, artwork, and designs and critically examine how they communicate meaning through story. And, how convincing they are of the points attempting to be made. Critically examine why you were drawn into some creative productions over others. What kept you from being immersed in the story? Was it the lack of developed characters (in the case of data, who generated it and how)? Was it a the lack of a coherent plot (what is the data trying to say and how can we let it say this)? Was it an unrealistic or underdeveloped setting (what is the broader context of the data, and where and when was it generated)? Was it poorly realized and unclear themes (what is the context of the data)? Or, was it a lack of coherent or convincing story (what models best tell the story of the data)?

Critically study logos and children’s media. These are exemplars of communicating complex ideas in a simple and direct manner. Look at Pixar productions or the film ‘The Song of the Sea’ for excellent examples in doing this. Critically study graphic novels and comics. Look at Gary Larson’s ‘The Farside’ for communicating a story in a simple, one-panel comic. Look at Jeff Lemire’s ‘Essex County’ for meaningful stories told through uncluttered illustration. And look at ‘The Arrival’ by Shaun Tan for an example of communicating without words. This type of media is valuable in understanding communicating with info visualization and how images can heighten the message of your written word.

In writing quantitative analysis, you may not be writing a fictional story. At least I hope not. But, that does not mean we cannot learn from the practice of writing fiction. Look to see how best you can tell the story of the data and not the story you want it to tell. Poor fictional stories fall victim to this same issue of a forced story being less fulfilling than one that develops coherently and naturally. In writing quantitative analysis, you are not the main character. You are the mouthpiece of the data and you are accountable for telling its story. Tell its story accurately and in a compelling manner.


Alexander, R. (2021, January 21). Telling Stories With Data.

William Davis, B. (2021, January 22). Henry ‘Hank’ Aaron is dead, but his life’s story is already at risk. New York Daily News.