Set the scene

1. Set the scene

Analyzing your data and setting the scene with a good exposition is the second practical step in forming a data story.

2. Operational insights vs. strategic insights

Data analysis first requires getting good data and then subsequently processing this data to get needed insights. The first question about your insights will be whether they are operational or strategic. Operational insights deal with day to day operations while strategic insights typically relate to longer term objectives. Knowing which type of insight you are working with can help immensely when you are setting the scene for your data story. Operational insights often require you to demonstrate more technical knowledge of business processes and strategic insights typically rely more on non-technical knowledge and operational understandings. However these are only general guidelines, look around your organization and understand how insights are shared to best set the scene.

3. The exposition or challenge

The exposition starts a story. It includes the primary characters' names, setting, mood, and time. Setting the scene means explaining what is going on around you. Your exposition can be dramatic or low-key, depending on the situation. You often want to start fairly strong with stark, direct language because you need to justify the meeting or read the final report. It would help if you exposed challenging factors and circumstances that imply a need to act and place them out front. Otherwise, you fail to address the unspoken question, "why are we here?" The data should support your story and be relevant to the operational or strategic insights.

4. Start to pull your audience in

Your goal is to engage your readers or listeners by evoking emotions and a deep understanding that a problem exists. To do this, you will need to convince them that you have thoroughly researched all angles of the challenge and that you have developed a compelling solution well supported with data insights.

5. A problem statement

Be sure to construct your problem statement in a way that is recognizable to critical thinkers. Problem statements often have three elements: First, the problem itself is stated clearly and with enough contextual detail to establish why it is important; Second, an implied problem-solving method is often stated as a claim or a working thesis. It has such phrases as "we noticed" or "we thought this may be due to". This is foreshadowing the future parts of your data story. Third, the scope of the problem will set the bounds for your proposed solutions.

6. One problem at a time

Finally, be careful to focus on one problem. Defining it specifically enough that you can summarize it in one or two sentences. Avoid trying to investigate or write about multiple, broad, or overly ambitious problems for one data story. Vague problem definition leads to unsuccessful proposals and vague, unmanageable documents. Simply naming the topic is not the same as defining a problem.

7. Let's practice!

Can you set the scene by writing a good exposition? Let's exercise your new knowledge and see.

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