How to Win the PowerPoint Party with Dang Good Data

We’ve all been there: stuck staring at screens with mountains of data to parse through and make into an easily digestible presentation for people who will likely on give it five seconds of thought before making a decision or moving on to the next problem. You could have faced this at school, work, or a very intense PowerPoint Party: you can’t escape the data. The Science Track hosted panelists Dane Ault, Jamie Bernstein, and Dr. Theda Daniels Race at 10AM Friday in Hilton 209–211 as they discussed “Making Data Look Dang Good”—how to take information and make it into something, well, dang good (because winning the PowerPoint Party is #goals).

The boiler plate of the panel is: make a story out of the data. That’s all it really comes down to – how can you show your info in a way that a person who has never researched anything to do with your topic can follow your line of thought? Show how you got from A to B (and C, D, E to K if needed) with all relevant citations and you’ve got an ace of a presentation.

Ault says that distilling facts into images is a lot like logo design. You have to take visual clichés and the facts and marry them into something recognizable for someone who hasn’t done the research that you have. He’ll take a simple image that’s relevant to the data story and work the info into that. Since he doesn’t have a science background, his process involves a lot of reading and working those hours of reading down into something that a person off the street could find helpful but a high-level scientist wouldn’t.

Keep in mind that sometimes you have no power over how your presentation is interpreted. You can do everything you can to keep your story straight but once data is discussed while you’re not in the room there’s nothing left for you to do. Bernstein spoke of the numerous times when she had to keep speaking up about how her research needed to be interpreted and still those who used her research only took what information they wanted but not the conclusion she reported.

Of course, even in 2023, biases are made for irrelevant reasons that some use to discount the work of researchers. Dr. Race said she had a Black female colleague who only takes her meetings camera off to present her information to prevent those biases from occurring. In the past, Bernstein has asked a male colleague to repeat everything she says because she knew she’d go unacknowledged in male dominated rooms if she spoke her ideas herself – and she was right; her ideas went unheard until her colleague repeated them (while crediting her) and suddenly those unheard ideas were so smart. All three panelists have seen biases towards colleagues in their industries based off race, gender, sexuality, accents, and even because of wardrobe.  Be wary of prejudices when presenting; you may end up having to do what you have to do to make sure your voice is heard like the panelists but don’t let someone else’s ignorance stop you from trying to share your knowledge and expertise.

When a member of the audience asked how to make choices in how to present information (i.e. giving a percent number as 75% or 3/4), Dr. Race provided the sage advice of ensure you maintain integrity. You know what story needs to be told by your presentation – don’t twist the data to fit your narrative. Be true to what you know and seek to spread that truth.

Sometimes you’ll get a broad ask for a report with no further details as to what’s expected. Bernstein recommends framing those asks as a partnership – you’re both working to get the data they need to move forward. Ask questions like, “what are you trying to do with this?” and “What question are you trying to answer?” If what they’re asking for won’t answer the question they have then ask them if instead of [the broad topic they came to you with], what if you provide them with this? You may have to break it to them that what they need is a bigger project or a larger scope but a partnership should help narrow down what the scope should actually be.

When attending presentations for your own edification, it’s important to take the info presented with a grain of salt. Question everything. The panelists offered these tips when asked about ways the trust of an audience could be abused by bad actors only looking to disseminate information in exactly the way they need:

  • Check citations. Some bad actors of the research community will ask each other to cite them in new research (relevant or not) just to build up numbers and lend credibility to their name.
  • Check sources. Look into who’s writing the article and what they’re reviewing. Their biggest source could very well be themselves or something they have monetary gain in. Alternatively check how their sources got the information they used; check sample size, demographics, and how data was collected.
  • Look for ways companies and presenters could use to get around citing their sources and data:
    • “Give us the *** and we’ll give you some ** that definitely means something.”
    • “The info is proprietary.”
    • “It’s math so trust it.”
    • “It’s AI, if something is AI it’s true –it’s smarter than you.”
    • “If the computer says it’s correct then it is. Just trust it.”

If all of the above is above board, interpret the information in a way that makes the most sense to you. Bernstein said that most of the time people who do the presentations aren’t trying to lie, it’s just the way the information is interpreted. Would that information actually mean anything to you if you placed yourself in the large sample size where the results only slightly improved what you were looking to solve?

The panel gave a wealth of information but if you aim to tell a story, keep it understandable for the average person, maintain integrity, and question everything then you’ll have made your data look dang good.

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