Speaker 1: Welcome to the deep dive. We sip through the noise
Speaker 1: to find the signal, the key insights, and today you're
Speaker 1: right here with us as we dive into effective graphic
Speaker 1: design principles.
Speaker 2: That's right, we're drawing from Leroy Bessler's Visual Data Insights
Speaker 2: using SaaS ODS graphics.
Speaker 1: Now it is focused on SaaS software.
Speaker 2: But honestly, the core design ideas they apply pretty much everywhere, very.
Speaker 1: Universal stuff totally. So our mission today is to pull
Speaker 1: out those really practical, actionable tips. How can you make
Speaker 1: your visuals clear, more impactful.
Speaker 2: And Bestler kicks things off with well of the fundamentals.
Speaker 2: He boils it down to three key objectives for any
Speaker 2: visual Okay, what are they Providing precise numbers, showing what's
Speaker 2: actually important, and crucially making sure it's readable. Clarity.
Speaker 1: Right. The precise numbers part is interesting. It's like the
Speaker 1: visual gives the overview, but the data underneath. Yeah, that's
Speaker 1: the foundation exactly.
Speaker 2: And he brings in that great quote from Joseph Pulitzer.
Speaker 2: Oh yeah, be blief, clear, picturesque and accurate.
Speaker 1: That's fantastic advice and it connects directly to what you
Speaker 1: are listener are probably looking for getting the knowledge quickly,
Speaker 1: you know, without feeling overwhelmed.
Speaker 2: Absolutely brevity, which leads perfectly into the next big idea focus.
Speaker 2: Bestlaer shares this great piece of advice from his assistant,
Speaker 2: which wise, just put it on one page.
Speaker 1: Huh direct, very direct, Yeah.
Speaker 2: But powerful, right, limit the message, don't overload people.
Speaker 1: And he has that anecdote about Miller brewing the computer report.
Speaker 2: Oh yeah, the discapacity report. Apparently it was just pages
Speaker 2: and pages long, kind of useless until until he's upseted it.
Speaker 2: Focus just on the key yessage categories. Suddenly boom, the
Speaker 2: important stuff just jumped out.
Speaker 1: It's a perfect example, less clutter, more impact.
Speaker 2: But and this is important, Bestler stresses, you have to
Speaker 2: be transparent when you subset, meaning meaning you need to
Speaker 2: tell the viewer what's included, but also what's not included.
Speaker 2: Give them the context.
Speaker 1: Okay, so how do you do that?
Speaker 2: He suggests, using titles and subtitles clearly state you know,
Speaker 2: the toward number of categories versus how many you're showing,
Speaker 2: and give the grand total versus the subtotal for what's displayed,
Speaker 2: maybe even the percentage of the total.
Speaker 1: Ah. I see, So like top twenty cities make up
Speaker 1: seventy two percent of total sales. Something like that.
Speaker 2: Exactly like that. Yeah, it gives the viewer the full
Speaker 2: picture even while you're focusing their attention. No surprises, got it.
Speaker 1: It's about guiding, not hiding. Okay, so let's shift gears
Speaker 1: a bit. This other category. Bessler has a fun name
Speaker 1: for one approach.
Speaker 2: He does, the pac Man pie chart.
Speaker 1: Okay, explain the pac Man pie chart.
Speaker 2: Well, think about it. Sometimes you have a bunch of
Speaker 2: really small categories. If you group them into one tiny
Speaker 2: other slice, yeah, it visually emphasizes how insignificant they are
Speaker 2: compared to the main players. Like pac Man about to
Speaker 2: eat a tiny dot.
Speaker 1: Okay, I get the visual. So it downplays the small stuck.
Speaker 2: Right, But then the opposite can also be true. A
Speaker 2: large other slice can actually peak curiosity. Bessler uses an
Speaker 2: example from his local government property taxes. They showed the
Speaker 2: village's slices small, and a big chunk was just labeled other.
Speaker 1: Making people ask exactly, Okay.
Speaker 2: Where's the rest of my money going. Then it prompted
Speaker 2: questions about that big other chunk.
Speaker 1: Huh. So the other slice isn't just a dumping grounds.
Speaker 1: It can be a communication tool.
Speaker 2: Itself precisely depends on what you want to achieve. Minimize
Speaker 2: something or maybe highlight a collective you want people to
Speaker 2: think about.
Speaker 1: Interesting. Okay, moving on sparse graphs. This sounds like it
Speaker 1: connects to the keep it simple idea.
Speaker 2: It absolutely does. Simple graphs are just easier and faster
Speaker 2: to grasp. Less cognitive load for the viewer makes sense.
Speaker 1: Any specific examples.
Speaker 2: He mentions his sparse line annotation for trend data, basically
Speaker 2: stripping away anything that isn't essential to seeing the trend itself.
Speaker 1: So minimal gridlines, maybe fewer labels if the trend is obvious,
Speaker 1: something like that.
Speaker 2: And he points out that those pac Man pies we
Speaker 2: just talked about they also count as sparse because they're
Speaker 2: so focused and simple.
Speaker 1: God keep it clean. Now, something really fundamental. Bar charts,
Speaker 1: specifically the axis.
Speaker 2: Ah, yes, the starting point. Bethler is very very clear
Speaker 2: on this, and the rule is for bar charts without
Speaker 2: negative values, the value axis must start at zero. Period.
Speaker 1: Why is that so critical?
Speaker 2: Because if you start at higher, say just to zoom
Speaker 2: in on the tops of the bars, Yeah, you completely
Speaker 2: distort the visual comparison. A bar that's twice as tall
Speaker 2: should represent twice the value starting above zero rates that
Speaker 2: fundamental relationship. It's misleading even if you don't mean it.
Speaker 1: To be right. It exaggerates the differences visually, like that
Speaker 1: five foot tall growth chart idea.
Speaker 2: Exactly zero baseline unless you're dealing with negatives. It's about
Speaker 2: visual accuracy.
Speaker 1: Okay, And this ties into another principle he calls maximally
Speaker 1: simple design.
Speaker 2: Yep. Again, it's about removing clutter. But here the distinction
Speaker 2: is important. It's not about limiting the information, but.
Speaker 1: About limiting the unnecessary graphic.
Speaker 2: You got it, extra borders, weird background patterns, three D effects,
Speaker 2: anything that doesn't actually add information or clarify the data.
Speaker 1: Get rid of it, Marie Condo for charts you said earlier.
Speaker 2: Kind of does it spark understanding? If not, maybe it
Speaker 2: doesn't belong.
Speaker 1: Okay. Now let's talk footnotes. Often tiny text at the
Speaker 1: bottom right, Usually yes.
Speaker 2: But Bessler argues that if the footnote contains really crucial information,
Speaker 2: like a major caveat or definition.
Speaker 1: Which wouldn't be tiny, right, he actually.
Speaker 2: Suggests making it the same size as the title text,
Speaker 2: maybe even bold.
Speaker 1: It wow, really that prominent?
Speaker 2: If it's critical context? Yes, it signals. Hey, pay attention
Speaker 2: to this. It fundamentally affects how you read this chart.
Speaker 2: Boilerplate stuff, fine print, sure, keep it small, but important.
Speaker 2: Context needs visibility.
Speaker 1: That makes a lot of sense. Okay, what about the
Speaker 1: text within the shart itself? Access labels? Values?
Speaker 2: Big point here? Use horizontal text whenever humanly possible.
Speaker 1: Because it's just easier to read, way easier.
Speaker 2: Our eyes scan horizontally naturally vertical text, tilted text, it
Speaker 2: forces you to crane your neck, slows you down.
Speaker 1: So what about, say, long labels on a vertical axis.
Speaker 2: He suggests trying to integrate that information elsewhere. Put in
Speaker 2: the subtitle, maybe the main title if.
Speaker 1: It fits naturally, or sometimes you don't even need the
Speaker 1: label exactly.
Speaker 2: If the horizontal axis is clearly showing dates, do you
Speaker 2: really need to label it date? Probably not, The context
Speaker 2: makes it obvious.
Speaker 1: Good point. And what if you have lots of tick
Speaker 1: marks on the horizontal access and the labels start overlapping
Speaker 1: or turning vertical?
Speaker 2: Yeah, that's a common problem. He suggests a few things.
Speaker 2: Can the viewer reasonably infer the missing values? Maybe you
Speaker 2: only label every second or third tick.
Speaker 1: Mark, or strength the font shrink, the.
Speaker 2: Font carefully, or some software has a stagger option putting
Speaker 2: labels on two levels. Anything is better than unreadable vertical text.
Speaker 1: Okay, good practical tips there. Now, thinking about graphs online
Speaker 1: on the web, any specific advice definitely?
Speaker 2: First, mouseover data tips are pretty much.
Speaker 1: Essential, so when you hover the mouse, you.
Speaker 2: See the exact value for that point or bar. It
Speaker 2: adds that layer of precision without cluttering the main visual.
Speaker 1: Nice. What else for webgraphs?
Speaker 2: For really dense data thinks scatter plots with tons of
Speaker 2: points or complex trend lines, consider linking to the underlying data,
Speaker 2: maybe an Excel file.
Speaker 1: So people can dig deeper if they want to.
Speaker 2: Exactly gives them the option for detailed inspection without overwhelming
Speaker 2: the initial graphic. You can link it right from the
Speaker 2: graph page.
Speaker 1: Smart and sizing, oh yeah.
Speaker 2: Size the image appropriately for the screen. Show them the
Speaker 2: entire picture, as Bessler puts it, avoid forcing people to
Speaker 2: scroll around just to see the whole.
Speaker 1: Charge right, basic usability. Okay, let's tackle the infamous pie
Speaker 1: chart people love them or hate them? Bestler's take.
Speaker 2: He gives best practices. Key thing include the slice description,
Speaker 2: the actual value and the percentage for each slice.
Speaker 1: Where do those go on the slice in a legend.
Speaker 2: Either way, but make sure it's clear. He mentions using
Speaker 2: call out lines if needed to avoid labels overlapping, especially
Speaker 2: on smaller.
Speaker 1: Slices, and the order of slices.
Speaker 2: Definitely order them largest slice to smallest slice, usually starting
Speaker 2: at the twelve o'clock position and going clockwise. It guides
Speaker 2: the eye to what's most important.
Speaker 1: Makes sense. What about that other slice and pies?
Speaker 2: Generally, he advises against using another slice in a standard
Speaker 2: pie chart unless you're specifically doing that pac Man thing
Speaker 2: we talked about earlier for a very deliberate communication purpose.
Speaker 2: Otherwise it can obscure too much.
Speaker 1: Okay, got it. Color obviously huge in visuals. What are
Speaker 1: the key color considerations?
Speaker 2: Contrast is king, especially label text against its background slice
Speaker 2: or bar color. Dark backgrounds need light text, Light backgrounds
Speaker 2: need dark text, simple but critical.
Speaker 1: Any tricks to make that easier?
Speaker 2: He suggests choosing palettes that are either all generally light
Speaker 2: fills or all generally dark fills. That way, you can
Speaker 2: usually stick to one label color, either black or white
Speaker 2: for everything. Simplifies things.
Speaker 1: Interesting idea. What about the use of color itself, when
Speaker 1: to use it when not?
Speaker 2: He has this great line. Uncolor might be the right color.
Speaker 1: I mean black and white basically, Yeah.
Speaker 2: Black and white if you have very few categories. Maybe
Speaker 2: shades of gray if you have a handful, reserve vibrant
Speaker 2: color for when you really need it to differentiate many
Speaker 2: distinct categories. Don't use color just for decoration.
Speaker 1: So purpose driven color exactly.
Speaker 2: He also mentions using transparency, which can be handy for
Speaker 2: overlapping elements like in scatterplots.
Speaker 1: Good tip. Any warnings about color.
Speaker 2: Oh yeah, the big one is how colors look different
Speaker 2: on screens versus projectors. Big difference.
Speaker 1: Sometimes I've seen that happen washes everything out totally.
Speaker 2: So test on the actual projector if you can. Even
Speaker 2: different computer monitors can show colors surprisingly differently.
Speaker 1: So what's the safest bet.
Speaker 2: Black and white is universally safe. Shades of gray are
Speaker 2: usually fine too, as long as they're distinct enough. Color
Speaker 2: always carries that extra risk of looking wrong on different devices.
Speaker 1: He mentions SaaS HLS colors briefly.
Speaker 2: Yeah, just noting that if you use shades of the
Speaker 2: same hue, make sure the lightness and saturation vary enough
Speaker 2: to be distinguishable.
Speaker 1: Okay, And bringing it back to basics. Again, just making
Speaker 1: sure people can read the text.
Speaker 2: Absolutely fundamental, sufficient font size, high contrast, plain background. Maybe
Speaker 2: use bold strategically for emphasis readability. Trump's almost everything.
Speaker 1: Else makes sense if they can't read it, what's the point?
Speaker 2: Precisely?
Speaker 1: Okay, couple of specific chart types to finish on three
Speaker 1: D pie.
Speaker 2: Charts just no, He's very blunt. They are always misleading
Speaker 2: because the perspective disorts the slice proportions ods graphics actually
Speaker 2: prevents you from making them directly.
Speaker 1: Good riddance maybe probably, yeah.
Speaker 2: Though older sends tools good, but yeah, avoid three D pies.
Speaker 1: What about donut charts?
Speaker 2: A donut chart is basically just a pie chart with
Speaker 2: a whole It uses the same logic, same options.
Speaker 1: Then you put text in the hole.
Speaker 2: You can. There are options like whole label and whole value,
Speaker 2: but he warns they have limitations. You don't have much
Speaker 2: control over the font size, and software might cut off
Speaker 2: the text or abbreviate it unexpectedly, so not.
Speaker 1: Super reliable for critical info.
Speaker 2: Probably not. He suggests using subtitles, footnotes, or maybe an
Speaker 2: inset statement if you want more control over text that
Speaker 2: appears in that central area, rather than relying solely on
Speaker 2: the whole labels.
Speaker 1: Okay, and don't it charts still need ordered slices and
Speaker 1: clear label Oh.
Speaker 2: Yeah, all the same best practices as pie charts apply.
Speaker 2: Order the slices, include category names, values, percentages, keep it clear.
Speaker 1: Got it? So, wrapping this all up, lots of practical
Speaker 1: advice here.
Speaker 2: Definitely. It boes down to clarity, focus, accuracy, and readability.
Speaker 1: Prioritize the data, guide the viewer's eye, keep it clean,
Speaker 1: make sure everything's legible.
Speaker 2: Use elements like subsetting or even that other category thoughtfully.
Speaker 2: It's all about creating those aha moments for your audience,
Speaker 2: not overwhelming.
Speaker 1: Them right, helping you, the listener, get those insights across effectively.
Speaker 2: Which leads us to a final thought for you to
Speaker 2: chew on.
Speaker 1: Okay, let's hear it.
Speaker 2: Think about a visual you're working on right now, or
Speaker 2: maybe one you made recently. Pick just one principle we've
Speaker 2: talked about today, maybe starting bars at zero or improving
Speaker 2: text contrast or simplifying the design. How could you apply
Speaker 2: that one principle immediately? And what difference realistically do you
Speaker 2: think you would make to how well someone understands the
Speaker 2: information you're trying to share.
Speaker 1: That's a great takeaway action. Just one change can make
Speaker 1: a big difference. And of course, if you want to
Speaker 1: dive even deeper, Leroy Besler's book Visual Data Insights using
Speaker 1: SaaS ODS Graphics is the place to go.
Speaker 2: Absolutely a really solid resource.
Speaker 1: Well thanks for joining us for this deep dive. Hopefully
Speaker 1: you've got some new tools for your visual communication toolkit.