Imagine the following situation: you’ve spent days and days performing complex data analysis. When it’s time to deliver and present the results to your team and leaders, you can’t get the message across clearly and they leave the meeting without really understanding how your research can help the company.
No professional who works with data would want to go through that, right?
Besides being an uncomfortable situation, episodes like this can hinder your professional growth. After all, it’s time to expose the results of your analysis that you can prove the value of your analytical effort and reinforce your contributions to the company.
The point is that knowing data analysis methodologies, knowing how to deal with them, and finding insights from them is not enough for you to be able to stand out in your profession.
Just as important as analyzing the information is knowing how to make a memorable data presentation that gets straight to the point and makes it clear that you made a difference with your analysis.
In this article, you can check out 6 foolproof tips for delivering a data presentation that impresses and conveys credibility. Check out.
1) Script your presentation and follow it to the letter
A powerful data presentation starts behind the scenes. The first step before entering the scene is to make a complete script of your presentation, with details about the procedures you went through and the most relevant content.
Study and reread this script a few times and try to find points for improvement in the way you present the results of your analysis.
And an important point: follow your script. During presentations, it is very common that, due to nervousness, lack of practice, or simply carelessness, you divert your attention from what needs to be said.
Of course, it may be that someone asks a question in the course of your exhibition and you need to deviate briefly from the pre-set route. But if you’ve studied the content of your presentation and are clear about what needs to be shown, you’ll have no difficulty picking up where you left off.
2) Explain your methodology and justify
With the script ready and revised, it’s time to think about the most important elements of your presentation. At this stage, give special attention to the methods and techniques you used in your data analysis.
Justify your choices during the analysis, explain why you used a particular database, and make it clear that these decisions were the most effective in finding points for improvement and solving problems in the company.
For example, if you chose to perform predictive analytics, explain how the procedures it predicts can help you find consistent and promising results.
3) Highlight what’s really important
Data presentation needs to be concise and to the point. In practice, the professional who stands out is precisely the one who manages to extract, from a large amount of data, what really matters and makes a difference in the performance of the team and the company’s business.
Therefore, highlight only what is essential about the nature of the data, the analysis process, and its contributions.
Some tips are valid in this process of filtering what is relevant. You can take out slides that don’t contribute and prove the conclusion your analysis has reached. Plus, you can review the graphics over and over again to make sure they’re getting the right, assertive message across.
Of course, there is no ready-made recipe for this step, after all, everything will depend on the content of your analysis, your results, and your audience. What you should avoid at all times is to pollute your presentation with unnecessary content, something we will also comment on in the next topic.
4) Choose the ideal graphic elements
No mixing up disjointed colors and inserting graphics that don’t talk to each other in your slides. When presenting data, remember that less is more.
The first step is to take care not to leave your presentation polluted. Visual elements need to be aligned with the relevance of the content, organized in a hierarchy that makes sense and supports the message you want to get across.
For example, if you intend to show a percentage evolution in the level of sales in a given period, choose an arrow facing up with the value of this increase on the side, and not a graph that can pollute your presentation or take your audience’s unnecessary time for a relatively simple message.
5) Make it easy to understand with examples
A data presentation, of course, carries a high level of complexity. The message most faithful to your analysis will not always be easily understood by the audience you are speaking to.
In these situations, a tip is to make the data easier to understand through examples. You can cite a story from a book, everyday events, or make comparisons with elements familiar to most people.
That way, you’ll be able to hold people’s attention even if the content is complex, allowing them to see the results and applicability of your analysis more directly.
6) Present your conclusions with conviction (but not just that)
Are you sure that the trajectory traveled during your analysis generated consistent and promising conclusions for the company? So it’s time to defend them with conviction.
As a general rule, the objective of market-oriented research is to identify gaps and areas for improvement. Therefore, when presenting the conclusions of your data analysis, highlight the benefits that these findings can bring to the company.
If necessary, project the possible numerical results that this conclusion can generate for the business. That way, everyone will be able to understand, in fact, the relevance of your work.
But don’t stop at this step. Here’s a bonus tip: provide insights for new research and raise new questions from the results you’ve found.
No research, by itself, exhausts the possibilities on a subject, theme, or problem to be solved. Most of the time, the conclusions of an analysis generate a series of possibilities for further investigations.
So, at the end of your presentation, come up with new hypotheses and show other opportunities for analysis. We do not doubt that, with this simple action, you will be seen as a professional who always goes above and beyond and performs above average.
Want to get even deeper into the data analysis? Discover Conquer’s Data Analysis specialization.
With professors who are a reference in the market and a methodology focused on practical application in the content, you will understand even more your company’s data flow and become capable of making increasingly agile, reliable, and assertive decisions.