From Numbers to Narrative | Sweet Slides 101 | Presentation Skills Webinar | SlideRabbit

Our Sweet Slides 101 webinar series focuses on crucial presentation and visual communication skills. This time we offered a data visualization webinar, From Numbers to Narrative.

Check out the highlights below and consider attending our next session, Captivate & Engage:
https://us06web.zoom.us/webinar/regis...

Data-savvy professionals enjoy more success

In our data-driven world, decision-making processes hinge upon the insights gleaned from data analysis. From optimizing operations to driving strategic initiatives, data underpins nearly every aspect of business today.

It’s not enough to simply possess data – it’s how we interpret and communicate that data that has a profound effect on how we perform in our professional lives.

In fact, 85% of those who consider themselves data literate report performing “very well” at work. Only 54% of non-data literate professionals would say the same.

By honing data skills, from analyzation through communication, professionals can strengthen their careers and expand their opportunities.

How do you make a story out of data?

When faced with a set of data, the challenge is to understand that data and be able to communicate important insights with context so that the recipients of the information take appropriate action.

To get from raw data to a true story, there are four major steps:

1. Review data for understanding

The first step to telling a data story is to take the time to really understand your data. What elements do you have to work with? Is there a time component? Are you working with absolute numbers or percentages? Given all of the data that you have, what are all the questions that you could answer?

In our example, we identified many answerable questions from a fairly simple set of data about calls into a call center.
Data Table example for data visualization webinar

But we can’t tell ALL of these stories – it’s simply too much for an audience to process. So how do we decide what we need to share?

2. Identify simple insights

Data doesn’t happen in a vacuum – once you are familiar with the data, widen your lens and consider context. Instead of focusing on all of the data you have access to, change your focus to only what your audience needs or wants to know.

What is the business question at hand? Might the data support a decision regarding budget allotment? Or marketing strategy?

In our example, the title told us that we are hunting for areas for improvement. Where we are fielding the most calls, we might have some opportunities for changes that will reduce call volume. Once we know what we’re trying to answer, we can review the data from that lens, searching for things that might provide insights.

3. Choose the right graph

Different graph types are best for different usages. Some graphs, like line graphs, are best for evaluating trends over time. Bar graphs, on the other hand, make comparing data easy. Pie graphs, of course, are best at showing a snapshot of composition.

We explored several graph types, but ultimately landed on this clustered bar graph, split by category. This graph allows us to see the general composition of the call categories, with the largest volumes listed at the top. We can also easily assess the year over year change in each category.

4. Provide context and action items

While the above is a good data expression, it is still not a story. Remember, data doesn’t happen in a vacuum, so consider what context might be necessary for the audience to arrive at the correct conclusion. Be selective! If we share too much detail, we might muddy up our main takeaway.

But beyond context, for this data to really become a story, we need to supply the “so what?” It’s not a story without an ending, so include the recommendations and action items – what should we DO about the data?

In our example, we added crucial context to explain outliers, used color to draw the eye to important data and strengthened our title in include our conclusion so that the data wasn’t just a statement, but a story.

When it comes to data, think about creating TRACTion

To make sure that your data visualization is working hard, check to see if have included the following:

Titles that provide guidance on what the data is telling us

Recommendations on what changes or decisions should be made according to the data

Annotations that draw attention to the right things, or explain outliers

Conclusions drawn from your evaluation of the data

Takeaways about next steps and action items


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