From Good To Nice In Dashboard Design: Analysis, Decluttering And Knowledge Viz

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Even when it’s a blessing in disguise, discarding components of your work is not any enjoyable. Tossing out suboptimal components of our design generally is a daunting activity, particularly after you’ve invested hours of labor into it. However make no mistake, this can be a bias most designers are susceptible to. We are able to get too hooked up to issues we’ve created, regardless of them not offering any actual worth to our customers. Right here lies the distinction between okay and nice dashboard design. The previous is pretty straightforward to realize. The latter isn’t.

I’ve compiled a number of issues that I’ve discovered all through my profession with regard to dashboard design. On this article, we’ll discuss analysis, decluttering, and information visualization, in addition to how these items could make your dashboard design higher.


A dashboard is part of an utility that shows world details about the app’s utilization or every other exterior information. They arrive in several sorts, from comparatively simplistic one-layered dashboards like this one:

Whereas others are extra complicated and multilayered ones just like the one under:

The suggestions we’ll present on this article apply to a variety of dashboards, no matter their complexity.

Earlier than diving into our arguments, first, let’s type out what I imply by “mediocre” and “nice”. These phrases suggest a price system that isn’t precisely standard, so I owe you an evidence.

Mediocre vs Nice Dashboard Design

The distinction between “mediocre” and “nice”, I consider, lies within the course of. There’s additionally a continuum concerned between these two classes. Within the context of this text, the axes of this continuum are as follows:

Sourcing inspiration (copying),
Analysis (referred to within the subsequent part as “homework”),
Design Validation (substantiating design choices with information),
Knowledge Visualization,
Colour Palette.


Sourcing inspiration

Restricted and fragmented
Constant and purposeful

Design Validation
Restricted to inside stakeholders
Inclusive of each inside and end-users

Knowledge Visualization
Closely centered on aesthetics and tendencies
Knowledge viz options are in keeping with its objective; a superb steadiness between effectivity and complexity;

Colour palette
Arbitrary / trend-based
Utilizable of shade connotations, and alignment with model values

(All through this text, all references to mediocrity are based mostly on these distinctions)

Now that we’ve sorted out the definitions, let’s rapidly give an summary of my arguments. On this article, I recommend that, versus mediocre dashboards, nice ones require:

A wholesome dose of cluttering & decluttering,
A thought-through shade palette.

First, let’s break down analysis, or “homework” as I prefer to name it. How do you even do “homework” as a designer? Is it okay to repeat another person’s work so long as you don’t make it apparent? Or do you begin from scratch each time? — Let’s suppose this by way of.

Doing Your Personal Homework VS Copying Your Friends

Positive, there’s all the time the choice of copying and tweaking what your rivals already provide. Or, if there are not any shut equivalents, you’ll be able to simply “Frankenstein” the weather collectively from comparable dashboards. This certainly sounds simpler than “reinventing the wheel”. “Good artists copy, nice artists steal,” as Picasso’s quote goes — however, sadly, this method is prone to doom your design to mediocrity. Let me elaborate.

A fast disclaimer: if what you’re in search of is to study, then by all means copy nice designs and attempt to study from them. Nevertheless, if you happen to’re engaged on industrial / “actual” tasks, then copying alone doesn’t do.

To begin with, theoretically talking, you possibly can strike gold by copying nice dashboards. There’s a catch, nonetheless. What’s the chance that your supply of inspiration is well-researched, sensible, and most significantly relevant to your specific scenario? Are the dashboards you’ve discovered price stealing? Who is aware of. In the event you ask me, nonetheless, I wouldn’t wager on it. This ties in effectively with the concepts Austin Kleon outlined in his e book Steal like an artist.

Secondly, whenever you’re sourcing inspiration, all you see is the tip product: a colourful nice-looking dashboard. Hardly ever can you discover inspiration accompanied by a radical evaluation of the method, analysis, and decision-making concerned. This results in one thing akin to a cargo cult, i.e. replicating the patterns you see with out understanding why.

Lastly, one other unlucky facet impact of merely copying is that it’s not constant. You possibly can’t play the percentages and win each time. That’s to not say {that a} “correct” design course of is foolproof. I consider that following the ideas I define on this article will make your designs constantly higher, so you’ll be able to “strike gold” with a better diploma of reliability and replicability.

Merely put, following a correct course of and having a command of design ideas, versus mindlessly copying, offers you a greater likelihood of arising with usable designs with fewer iterations and useability testing classes.

So how do you strike a steadiness between “copying” and “doing your individual homework”? Right here’s what I feel. On high of “stealing” (ahem.. in search of inspiration), additionally speak to your customers.

I 👏 can’t 👏 stress 👏 this 👏sufficient.

I wager we’re all (myself included) uninterested in listening to this mantra. “Speaking to customers” is like exercising or maintaining a healthy diet — everybody is aware of they need to do extra of it, however few truly do it.

“Individuals ignore design that ignores individuals”.

Frank Chimero

Is there a worse option to ignore customers than excluding them from the dialog altogether?

Alright, speaking to customers is vital. That a lot is evident. What isn’t self-explanatory although is how precisely this communication ought to happen — let’s go over a few actions to look at a few methods.

Person interviews:

Listed below are a number of questions price trying into when designing a dashboard.

What info do customers want probably the most?
What’s the objective of this dashboard?
What do customers seek the advice of this dashboard for?
How do they go about in search of this info at the moment?

On this piece, Stelian Suboti, a UI & UX designer with greater than 7 years of expertise, the creator claims that:

Really beneficial perception can come out of a brief consumer analysis section with simply 5 customers — and it’ll save an unlimited period of time down the road.

Doing analysis (consumer interviews on this case) is step one of the design pondering course of (empathy), in addition to the UX course of usually.


“Card sorting by its very nature, is a technique you’d use whenever you wish to uncover classes, teams, or interrelationships. Use this technique whenever you wish to understand how customers reply to visible cues and also you wish to seize the similarities and variations.”

Assume Design

As we’ve simply discovered, card sorting helps us perceive how customers group and categorize info. In sensible phrases, card sorting appears to be like one thing like this 👇

You usually wish to break up your dashboard into “atoms”, bits of data of the smallest dimension, in order that the individuals can set up the relationships amongst these components. That is how you possibly can construct the data hierarchy throughout the dashboard that’s in keeping with customers’ psychological fashions.

Usability Testing

Usability testing is arguably a very powerful and insightful analysis exercise you’ll be able to conduct with regard to dashboard design. Taking part in by ear and skipping this step altogether simply is perhaps the most important cardinal sin of UX design.

Right here’s what Nielsen Norman Group, the world’s main product design authority, has to say about usability testing:

“Even the most effective UX designers can’t design an ideal — and even ok — consumer expertise with out iterative design pushed by observations of actual customers and of their interactions with the design.”

In sensible phrases, you’d wish to conduct usability testing classes after card sorting and consumer interviews. The latter two actions blended with your individual assumptions ought to lead to early dashboard variations. These tough concepts will then must be examined and iterated on from sketches, and low-fi wireframes all the way in which to a high-fidelity prototype.

Now that we mentioned the analysis strategies, we are able to safely transfer on to my second argument, which is all about decluttering. How have you learnt in case your dashboard is cluttered? Does the “much less is extra” precept work each time? — These are the subjects we’re tackling subsequent.

To Declutter Or Not To Declutter

In a traditional sense, decluttering is almost synonymous with simplifying. Furthermore, the follow of “hold it easy silly” (KISS) has grow to be considerably of a design truism. The easier the higher, proper? I want it was that straightforward (no pun supposed).

A cluttered design, by definition, overwhelms its customers. That’s to not say that an app can’t have a studying curve. Adobe merchandise are in all probability a textbook definition of what “overwhelming a first-time consumer” means.

Let’s check out the next dashboard:

This is a wonderful instance of what is perhaps thought-about “cluttered”. A better take a look at the dashboard will let you know that it has to do with inventory (index) value motion, buying and selling quantity, financial occasions, and many others. In the event you suppose that this appears to be like intimidating — you’re proper. For a mean consumer, it in all probability is. I’d wager, although, that the individuals certified to make use of this sort of software program truly profit from this complexity — it permits them to work effectively. Obscuring a lot of the data offered on this dashboard will solely lead to pointless clicks and extreme friction.

Now let’s attempt to check out one thing seemingly decluttered and “clear”. By the way in which, this specific dashboard, designed by Bhojendra Rauniyar, received within the minimal dashboard problem by UpLabs. Congrats to Bhojendra!

Earlier than I begin critiquing the dashboard above, right here’s a disclaimer. To begin with, this can be a dribbble shot, so we are able to’t be sure whether or not it’s an remoted piece of design or part of a product. Secondly, I don’t have entry to the designer to ask for his rationale behind sure design choices. Thirdly, I have no idea whether or not this design has been examined and the total context of its utilization. As such, all I’ve left is to invest and assume. I hope, for instructional functions, that may do.

Let’s begin with the chart. It compares consumer scores with earnings. I’m left to marvel although what values outline these two classes? The values should be the identical since each curves are on the identical graph. So will we measure earnings in common ranking or ranking in {dollars}? Moreover, there are not any labels for the dimensions, so I can’t even be certain of the models of measurement. What would in all probability be extra helpful is having separate graphs for key metrics with clear labels, i.e. to introduce “further complexity”.

Moreover, the stats alone are usually not very beneficial. Is incomes “5k” in “1.8k” hours a superb outcome? How does that examine to my friends? What are my dynamics?

That’s to not say that the dashboard I discussed first is ideal and the second is unhealthy. You possibly can argue that each of those require additional work. My level is that decluttering for the sake of decluttering is a poor design maxim.

Cluttered apps are unnecessarily overwhelming and arduous to navigate. How have you learnt if an app is all the above? Presto! That’s proper, you speak to the customers and have usability testing classes with them. Apart from usability testings, there are a number of different practices that may assist be sure that your interface isn’t cluttered:

Clear info hierarchy;
Using modals or panels;
On-hover interactions;
Two to 3 colours;
White house, loads of it.

Now that we went by way of analysis and cluttering, we are able to transfer on to information visualization. Knowledge visualization is irreplaceable for a lot of causes. It permits you to:

See patterns,
Evaluate information,
Articulate the data visually,
Observe information dynamics.

Does this ring a bell? Precisely — that is just about the whole lot {that a} dashboard ought to do. It’s no coincidence that the majority dashboards function graphs and charts. Subsequently, being competent at information visualization immediately interprets into being a reliable dashboard designer. Let’s zoom in on that.

Step Up Your Knowledge Visualization Recreation

There are a number of varieties of charts obtainable, thus we have to select correctly. The sunburst chart does look superior, however is it as clear and clear because the pie chart? Maybe. That actually does rely in your customers. Kinds of charts apart, there are additionally colours, their semantics and so many different issues that add to the complexity of knowledge visualization in dashboard design.

On this part, I’ll do my greatest to stipulate a few of the information visualization greatest practices and their utility in dashboard design. Let’s begin with colours.

This part is basically based mostly on the analysis of Claus O. Wilke, Professor in Molecular Evolution at The College of Texas at Austin, and the creator of Fundamentals of Knowledge Visualization.

Colour In Dashboard Design

Let’s tackle the difficulty with numbers first. What number of colours must you use in UI design and dashboard design particularly? — Frankly, there’s no magic variety of colours that works it doesn’t matter what. Nevertheless, if I had been to advocate you a quantity, it could be 5. That doesn’t embody shades if the depth of the colour represents a price or semantic colours if you happen to want them (e.g. pink for error messages or inexperienced for achievement messages).

Why 5? Nicely, there’s a 6:3:1 “golden” rule of visible design. These numbers symbolize the proportion amongst three model colours: predominant, secondary, and accent. Nevertheless, it is best to do not forget that on high of those three colours, you’re seemingly going to wish some variation of white and black for textual content and its background.

One other factor to make use of colours for is to tell apart amongst totally different entities. Listed below are a number of frequent shade palettes.

Use monochromatic shade palettes if exhibiting info inside a single class. That method you’ll be able to introduce one other dimension to your chart that’s straightforward to learn. For instance, the extra intense the colours, the upper the worth and vice versa.

Right here’s an instance:

What you can too do is choose two colours to symbolize the other ends of a spectrum. That method you’ll be able to simply inform aside values that belong to totally different extremes. Right here’s an instance:

Listed below are a number of shade palettes for this method you’ll be able to select:

Beware Of Colours Semantics

Now that we went by way of the approaches you’ll be able to take with utilizing colours, it also needs to be famous that colours elicit unconscious reactions. These reactions are sometimes called “shade semantics”.

When evaluating 2 teams, utilizing colours like pink and inexperienced (due to the semantics related to these colours) may result in misrepresentation. Purple, as an illustration, is commonly related to hazard, failure, and poor efficiency.

Check out the graphs under, which illustrate the mathematics efficiency of two lessons. We would robotically assume that college students on the graph on the left in Class A are performing poorly, because of the truth that the values are represented with pink. Purple, particularly together with inexperienced, typically elicits such an interpretation.

Nevertheless, there are circumstances the place this semantic distinction can be utilized to our benefit like within the instance under, i.e. utilizing pink to show efficiency that’s under common, and inexperienced for above. Additionally, word that it’s extra pure for individuals to instinctively affiliate values on high as higher than these under. The graph under illustrates the final level.

As you’ll be able to see, inexperienced represents college students who carry out above common, whereas pink is reserved for individuals who underperform. Semantic shade cues make this chart much more readable than it could in any other case be with one other shade scheme.

On Which Charts To Use

Knowledge visualization can induce a good quantity of friction when completed incorrectly. Be sure that to decide on probably the most appropriate sort of chart to ship the correct of knowledge. Under, you’ll discover a kind of complete checklist of charts you should utilize to symbolize the data featured in your dashboard, relying on the roles they fulfill.

NB: Most charts serve multiple objective. For example, a pie chart is used to check values, present composition, and information distribution. As such, I’ll point out these charts a number of occasions relying on the use case. Nevertheless, I’ll solely give a short rationalization for every chart as soon as.


Usually used to symbolize fractions of a complete. Pie charts work nice each time you must examine a comparatively low variety of segments which might be comparable by way of their dimension. Conversely, having too many segments or tiny segments makes the chart too arduous to learn. A significant con of pie charts is their lack of ability to indicate modifications over time.

Stacked Bar
Particularly helpful when evaluating classes. Identical to the pie charts, the extra complicated they get (extra sequence & classes), the more durable they’re to learn. A bonus that stacked bar charts have over pie charts is the flexibility to see modifications over time. One other factor to look out for is that when you will have sequence that adjust of their worth, it will get more durable to check them visually. For instance, check out the instance under, it’s not apparent whether or not the orange sequence for “Eyebrow pencil” is bigger or smaller than that of “Basis”.

Excellent for visualizing the variations of sure classes inside a number of dimensions. Identical to the remainder of the charts we’ve gone over to this point, they’re straightforward to learn however get more and more more durable to understand as soon as the classes and dimensions begin to pile up. Moreover, it is best to keep away from utilizing Mekko charts if the variations amongst components are too drastic.

Stacked Column
A good way to indicate comparisons between classes. You might need observed that this chart sort bears a robust resemblance to a stacked bar chart. Although there are variations in naming, it is best to know that horizontal bars often go from highest to lowest worth (or vice versa), whereas vertical ones suggest one other order rationale.

A very frequent method of representing quantitative information. Typically used to indicate the rise or lower of varied information sequence over time. The most important con of any such visualization is that it’s arduous to attach a selected level of the graph to a price on each axes. And, as all the time, the extra info you cram in, the much less readable it turns into. Lastly, if the graphs overlap, then one space will go over one other and vice versa. Subsequently, space charts are good for serving to see the massive image with out an excessive amount of regard for being extraordinarily exact.
You may also discover a similarity between space and line charts. The previous ought to be used when there’s an emphasis on a part-to-whole relationship.

This type of chart is commonly used within the monetary business to show the motion of worth and its incremental path in the direction of an endpoint. These charts, not being all too frequent, may not be probably the most intuitive to learn, so they need to higher be reserved for professionals who take care of waterfall charts typically.

A sensible choice whenever you’re trying to current a sequence of values. These values (additionally known as markers) are usually related by straight line segments. The road chart mimics the disadvantages of the world chart, apart from the colour overlapping downside.

Showcase the composition:

Stacked Bar,
Stacked Column,

Distribution of Knowledge:

Scatter Plot
A good way to emphasise the relationships between one or a number of numeric variables and/or their distribution throughout two axes. The most important downside with utilizing scatter plots for UX functions, it’s that any such chart is significantly more durable to learn than all the different ones we’ve mentioned to this point. As such, scatter plots ought to be reserved for knowledgeable customers solely.

Generally used to current monetary information. Bubble charts are much like scatter plots, nonetheless, they supply a extra in-depth understanding of the info, since they’ve 3 axes.

Correlation and relationship between values:

Scatter Plot,

If we had been to summarize the charts above in a matrix, it could look one thing like this.

It’s only becoming that we summarized the varieties of charts and their utilization as an infographic. 😄

Be suggested although, that I’ve indicated what these charts are usually used for. Theoretically, if you happen to wished to, you possibly can do a bubble chart, the place every bubble is a pie chart. Voila, your bubble chart can now additionally present the composition of every bubble. After all, it’s simpler stated than completed, as a result of often, bubbles differ of their dimension drastically. Anyhow, you get the concept: the matrix is a common guideline, however you may get extra artistic with charts if you wish to at your individual discretion.

Balancing Between The Complexity And Effectivity

So right here’s a factor. As you might need observed, numerous charts can be utilized for comparable functions. That doesn’t imply, nonetheless, that these charts are equally good for a sure activity.

Typically, when you slender down your alternative to some charts that appear to work greatest, you then wish to be sure that they’re the least complicated they may very well be. Under, I’ve outlined a few of the charts we’ve talked about by the diploma of their complexity and effectivity.

In a nutshell, you wish to maximize effectivity and reduce complexity. That is the top-left quadrant. These charts are straightforward sufficient to be understood by center faculty college students. You need to persist with these for the “shopper” persona, i.e. a mean Joe. The extra you progress towards the appropriate, the extra causes it is best to should consider your customers could be snug with studying them.

What’s Subsequent?

In case you’d prefer to proceed studying about dashboards and the points of their design, listed below are some sources my staff and I’ve discovered useful (to an rising diploma of complexity):


Knowledge-heavy functions: How you can design good charts
High 16 Kinds of Chart in Knowledge Visualization
Dashboard Design: greatest practices and examples
How you can design and construct an incredible dashboard
Dashboard UI Design: 14 Finest Practices for Stakeholders


Refactoring UI
Lovely Visualization: Knowledge by way of the Eyes of Specialists (Principle in Follow)
Practical Artwork, The: An introduction to info graphics and visualization (Voices That Matter)

Scientific papers

Visualization Criticism – The Lacking Hyperlink Between Data Visualization and Artwork
Ideas of Efficient Knowledge Visualization

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