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I spent a lot of time in my last role building presentations and executive summaries for leadership. Way more than I would have liked 😀.
Here is everything I learned about doing it well.
The short version: less is more, and the story matters more than the data.
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Not every insight belongs on a main slide
When you finish an analysis you usually have ten interesting findings. Maybe more. The instinct is to show all of them.
Resist that instinct.
Pick the two or three findings that actually drive a decision.
Everything else goes into an appendix (the last slide of your presentation is usually ‘Thank you’ slide. After that you can add as many additional slides as you want) or gets mentioned verbally if someone asks. Nobody remembers slide seven of fourteen. They remember the one clear thing you told them.
I actually like to have several insights written in my notebook, that I use only when present it to the audience. It is like some secret information you can find out only if you are present at the meeting. It can be related to a different analysis that was sent via email, or some public information from the news relevant to the topic, or something about the competitors.
Build the story first, then the slides
Before you open PowerPoint, answer one question: what do you want your audience to do after this presentation?
Approve a budget? Change a process? Stop a campaign? Whatever it is, that is your storyline. Every slide should build towards that single action. If a finding does not support the storyline, it does not belong in the main deck — even if it is interesting.
This is the difference between a presentation and a data dump.
One finding per slide, 1-2 sentences maximum
Each slide should make one point. Write it as a short, declarative sentence as the slide title — not "Q3 Regional Performance" but "West grew 18% in Q3, driven by the new loyalty programme."
The chart and supporting numbers do the rest of the explaining. You do not need three paragraphs of text on a slide. If you find yourself writing a wall of text, that is a sign the slide is trying to make too many points at once.
Don't write what's obvious from the chart
If your chart clearly shows West outperforming every other region, you do not need a bullet point that says "West outperformed every other region." That is what the chart is for.
Use your words to add what the chart cannot show — context, cause, or what to do about it. The chart shows what happened. Your text explains why it matters.
Reference your numbers to make the point stronger
"Revenue grew" is weak. "Revenue grew 18%, the strongest quarter in two years" reads stronger.
Specific numbers make a finding feel credible and give your audience something concrete to remember and repeat to their own stakeholders. Vague language gets forgotten. Numbers stick.
Footers and references matter more than people think
Every slide should have a small footer noting the data source and date range. It looks more professional, and more importantly, it means someone can ask "where did this come from" and you have an immediate answer instead of scrambling.
For example, your bar chart shows %, then in the footer you can indicate data source, date range, and what is the total number. So people can calculate what 35% actually mean if they want to.
Also if you are using external data (like numbers from the media or news) it is very important to reference it in the footers.
This is a small habit that signals rigour.
Write the executive summary last — but it goes first
This trips people up. The executive summary is the first thing your audience sees, but it should be the last thing you write.
You cannot summarise an analysis you have not finished. Build out your findings first, decide on your storyline, then come back and write one tight paragraph: the key finding, why it matters, what you recommend. That becomes slide one.
I was also taught to add a little magnifying glass icon with a link to a different slides next to each finding. This way when you are presenting the executive summary and someone asks ‘can you show me the details’, you click on it and go straight to the relevant slide.
Some people read only the executive summary and skim the rest. It needs to stand completely on its own.
When you present to C-suite (CCO, CFO, CEO) - you literally have 3-5 min to the whole presentation, as the whole meeting has an agenda. You only have time for an executive summary and answering questions if any arises.
Do not repeat what is already in the slides
If you are presenting live, do not read your slides out loud word for word. Your audience can read. Use your speaking time to add context, answer the "why," and connect findings to the bigger picture. The slide is the headline. You are the article.
A real example
Imagine you are presenting Q3 retail performance to leadership.
The cluttered version tries to cover regional breakdowns, every data cleaning step you did, methodology notes, and six bullet points per slide. By the third slide, your audience has stopped reading.
The clean version says one thing: West grew 18% in Q3, driven by the new loyalty programme. One supporting chart. One recommendation — expand the programme to the South region next. A footer noting the data source. That is it. That is the whole slide.
One of those gets remembered in the meeting. The other gets skimmed and forgotten by the time everyone leaves the room.
The one-page checklist
Save this for your next presentation.
Define the action you want your audience to take before building anything
Pick 2-3 findings that support that action — everything else goes to appendix
One finding per slide, stated as a sentence, not a topic
1-2 sentences of text maximum per slide — let the chart do the rest
Don't restate what the chart already shows
Use specific numbers, not vague language
Add a footer with data source and date range on every slide
Write the executive summary last, place it first
Don't read your slides aloud — add context instead
Less is more. If in doubt, cut it
Keep pushing 💪,
Karina
I just published a YouTube video on how I use Claude for data analysis — exploratory analysis, debugging SQL, turning findings into stakeholder-ready outputs.
I also cover the privacy setting most people have never checked and because of that our data is used to train the models. → link
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