Data to action, a three-act story
By: Ryan Andrews
Tags: Product Design, Data Storytelling, Data Stories, Data Visualization, Product Management

Data is everywhere. Actionable data is not. That’s a bit harder to find. While our data heavy world loves beautiful visualizations, we often find ourselves staring blankly into a vast sky of sparkling bars and pies, wondering which of these glimmers is our North Star. Which of these shapes or red numbers should we even care about? What action should we take? Without action, these celestial visualizations are worthless. Data stays where it is, floating in a vacuum, not bringing meaningful change to our course.

But what makes data actionable? Is it more data? More filters? More graphs? Less of everything?

In narrative fiction, characters need to change. Events and circumstances happen that cause friction, drama, joy, hate, love, and change. There comes a point where action has to be taken in order to meet a resolution, and usually it comes down to making the right decisions. This narrative normally fits into what is called the three-act structure.

Data can be looked at in the same framework. Dashboards should tell us a story. Some dashboards make it a hard story to read, others give us the clearest report we’ve ever seen. Let’s explore the three-act structure, and how it speaks to reaching our true data goal: action.

the three-act narrative structure

Act 1: Setup

Typically, the first act is all about exposition. In fiction, this is where we learn about the characters and the setting. We find out who we are dealing with, what their lives are like, and what elements of this world are in play. A one-word summary of this is context.

Data Context

Data context is everything that helps us take action on the information we are being presented. A number by itself only inspires the few who already have the context in their minds. Without context, we’re left with questions such as:

Is this data good or bad?

How current is this data?

What timeframe does this data represent?

How does it compare to the past?

Where does it rank in comparison to others?

Data context frames metrics, revealing the story that is to be told. It tells us what we are looking at, where it’s from, and how current it is. It helps us understand where a number is in relation to where it should be, where others are, and where it has been. With data context, we know what we are dealing with and have the setup to our data story.

Inciting Incident

Also known as the catalyst, this is the first turning point in the story. Something dramatic happens that ensures action must be taken, life will never be the same, or an important question must be addressed.

With data, this is our first discovery. It may be a metric recommended by a data science engine, or a clear red indicator in an otherwise sea of green. Given our established context, we move forward with our discovery into the second act.

Act 2: Rising Action

The second act is where our hero tries to resolve the inciting incident from the first act. This usually leads to further conflict, deeper issues, or unexpected realizations about themselves.

In our data story, this is where the context starts to lead to conclusions. With the culmination of time context, geographic context, comparisons, and data science driven insights, the story rises and we uncover more about our first discovery in act one. Along the way, we are sure to uncover more inciting facts, further progressing our story and forming our complete narrative.

Dramatic Question

At some point in the progression of the story, a question usually arises. It’s what the audience wants to know, the reason they stick with the narrative. This question will be answered in the third act in order to provide a satisfying conclusion to the audience. (We’ll skip over cliffhangers for now.) With data, there is one question that matters, one question that needs to be answered by any visualization, dashboard, or report.

We have all of this data and information, that’s not a question. We are trying to determine where we should focus our time and effort. Or put another way, what action should we take?

This is the dramatic question in data storytelling: What action should we take?

In the second act, we are working to answer this question. With a more fully informed story in hand, we move to the third act.

Act 3: Resolution

This is where some sort of resolution is reached. In a final narrative, the story and its subplots are tied together and presented to the audience in a satisfying way — the climax.

In our data story, this is the communication or strategy we decide to implement. We’re answering the dramatic question, we’re deciding what action we should take. Oftentimes, we make these decisions with others. We use the data context and discoveries to share a story and agree on conclusions. Our conclusions dictate actions such as changes in strategy, focus adjustments, tactical adjustments, or behavioural modifications.

It is key for the third act to include trackable changes. Our goal is real action, not just conversation. We must have action plans to carry out, targets to work towards, and tools to carry objectives forward.

Epilogue

Oh yes, there’s more.

We can’t just take action and never follow up on it. Decisions we make and tactics we implement need to be reviewed and renewed. This is the follow up on our data story. Our data will constantly evolve. Given the action we take, we expect noticeable changes.

This is where the tools that empower us are crucial. Data has to be part of our documented workflow, and the actions we take from that data has to be tightly linked. Without these tools, without these workflows, our decision will vanish into that vast vacuum and will be unable to reach a satisfying conclusion.

It’s an ongoing effort. We must continue to use data to take action and follow up on that action with more data. Our data story is cyclical, the three acts constant. The data points we see move and the changes in KPIs that come from our action will tell a whole new data story. Time for a sequel.