Dashboard Storytelling
By Zach Gemignani
May 7, 2007
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Everyone wants a dashboard and the promise of a world in which the intricacies of your business are clearly laid out on a single page. Dashboards can make running your business as easy as driving a car, where slight adjustments and careful attention to warnings mean smooth sailing on the road to success.
I'm not so convinced. For someone who is, check out the mysterious Dashboard Spy. He/she has a massive collection of dashboard screenshots and describes these precious morsels as "simple to understand and impressive to look at, these scorecards are becoming 'must-haves' for all enterprises."
If we already live in a dashboard-centric world, we might as well do them right. I see at least three areas where dashboards need improvement: depth, information display, and storytelling.
Depth. Stephen Few makes a worthwhile distinction between dashboards and something he calls "faceted analytical displays" (FADs):
- A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance.
- A faceted analytical display is a set of interactive charts (primarily graphs and tables) that simultaneously reside on a single screen, each of which presents a somewhat different view of a common dataset, and is used to analyze that information.
We might consider dashboards a static version of FADs (or we could consider FADs a versatile dashboard). If that's true (and I'm sure Stephen will step in to correct me), then who wants a plain dashboard? Why build something that only raises questions but doesn't give the user any ability to drill down, explore, tweak parameters, or otherwise try to answer those questions?
Information display. Like most reporting, dashboards suffer from poor information design. Here's our list of blogs that preach the right way and highlight the offenders. Here are two particularly misguided design approaches that I've seen recently...
Just because it is called a dashboard doesn't mean you need to take the concept literally (via Dashboard Spy)
Just because you can make it shiny doesn't mean you should. Crystal Xcelsius not only vigorously embraces pie charts, but they add a "reflective kidney bean" to further derail the information display.
Storytelling. Most dashboards are loose affiliations of charts—a hodgepodge of graphics on the same topic intended to offer a full view of a situation. It is the same problem so many people run into in creating PowerPoint presentations.
You want the information to easily slide into the viewer's brain and stick when it gets there. The best dashboards have story-like features such as:
- Set the stage. What is the context? Who are the characters?
- Focus on only the important elements and themes; don't try to be a comprehensive account of everything that happened. Ruthlessly cut extraneous content.
- Offer recognizable characters to spare the reader's precious attention. There is a high cost to asking readers to learn from scratch. For dashboards this means terms, metrics, graphics, and metaphors that are familiar within the organization.
- Create flow and cohesiveness from chapter to chapter. Themes and characters reappear chapter after chapter. A good dashboard isn't a bunch of disjointed charts, but a logical flow from one analytical examination to the next.
- Levels of detail. Some elements of the story span the entire experience; other details provide the insights and seasoning to keep your interest.
Here's a good example of a dashboard (perhaps FAD) from Visual I-O that has many of these storytelling elements.
In contrast, the following dashboards (courtesy of Dashboard Spy) don't attempt to explain anything to the reader:
If you've seen a worse dashboard, sent it our way and we'll put together a gallery of the worst of the worst. Please redact any company-specific information.
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9 comments | Show all comments only the last 5 are shown
nixnut said:
According to Steve dashboards and FADs serve two distinct purposes. In Steve's words:
The greatest clarification that is needed today is a distinction between dashboards, which are used for monitoring what’s going on, and displays that combine several charts on a screen for the purpose of analysis.
So dashboards are for monitoring and FADs for analysis.
A dashboard displays predefined measures that may come from a multitude of data sets.
A FAD will usually display different views of one dataset.
A dashboard is for displaying answers to existing questions.
A FAD is for discovering new things of interest in a data set. Manipulating a FAD leads to new questions and (hopefully) answers to these questions.
So why would one be satisfied with a mere dashboard? A dashboard can display measures covering a great number of areas of interest using data from a large number of sources. The value of having all the measures that are important for your work available in one display may outweigh the value of being able to directly manipulate the display to slice, dice, drill up/down/left/right etc. I think having a seperate tool for analysis makes more sense then forcing your dashboard to do a job it is not designed for or trying to make your analysis tool be a dashboard as well. Use the right tool for the job.
Also analysis might not be the most effective way to spend your time on or even be your job. I reckon a senior manager is more likely to put an assistant onto finding an answer to a question raised by a dashboard measure than performing the analysis himself. In operational monitoring you may just need to keep track of things and inform the relevant team if the value of a measure reaches a threshold. Finding out why the threshold is reached would not be your job.
Zach said:
Putting aside qualifiers like "it depends on the situation", I don't think I agree with the distinction as you've described it. A couple reasons:
* Senior managers should be willing to spend some time examining data beyond looking for a warning light. That isn't to say they should be running logistic regressions, but it is worth the mental effort to discover which division is causing a deviation or understanding sales variance by day of the week. In my experience, understanding nuance is what separates the good leaders (enter political joke here: _____)
* More generally, I think it is artificial to make a strong distinction between raising questions and answering questions. Granted it may be difficult or impossible in some situations to have a tool that does both. Why not make that the goal? The Visual I-O tool shown above will highlight strong and weak performance, and the ability to cut the data will help answer some of the questions about this performance.
* FADs need not be constrained to a single data source. Getting the full picture of a situation usually requires tapping into multiple systems.
Michael said:
Nice blog post. I think you made a pretty strong point. There is another angle here but I'm not sure how it fits in. The niche that I am personally interested in is the fact that many dashboards as well as FADs are backwards looking. They rely on the individual to extrapolate what they see, into where sales might end up for the month or the direction sales are headed for the year. With the amount of predictive modeling and simulation analysis that is available, I would really like to see dashboards incorporate much more sophisticated analysis. This doesn't mean that the display of information should be less intuitive, but that the underlying drivers that create the information to be displayed, could be so much more useful.
For example: I know that as of May 7 we have closed 20k in sales. I may also know that historically, in May, we have had 30k in sales booked. I also know that our plan says we should have 35k in sales by the 7th. Of course, there is always uncertainty in any forecast and sales could pick up significantly over the next couple of weeks. Maybe a monte carlo simulation could be run in the background and surfaced to the dashboard in such as way that the indicator tells us that based on current data our expected month end results are:
85% chance of hitting 35k
90% chance of hitting 30k
98% chance of hitting 25k
etc.
Kevin Hillstrom said:
Dashboards are fun to implement when you have a company with 60,000 employees and 130 executives who have differing ideas of what is important.
But if you can get past that, you can really teach leaders what is important via a dashboard.
nixnut said:
Hello Zach,
Perhaps my example of senior managers is a wrong example. I was merely trying to point out that there are groups of dashboard users that would use a dashboard for monitoring and not for analysis. I think that the difference between monitoring and analysis is large enough that the principles of perception and cognition would lead to different designs.
Having a tool that is capable of designing visual displays to cover the full range from monitoring KPI's to sophisticated analysis is indeed something to aim for. Alas such tools are not available yet (at least none that I know of).
While such a tool would allow you to build both dashboards and FAds these are still different things imho. The dashboard would still display the KPI's (or their derived metrics) and the FAD would let you look at the numbers behind the values for these metrics, generate and look at different perspectives, possibly do some simulation etc.
I didn't say FADs are restricted to one data source. I said they would usually work with just one dataset. I suppose my wording wasn't too clear. By dataset I mean a set of data about one subject area. In a dashboard it's natural to display metrics from several subject areas that are not related (other than by organisation) or not related in ways that are useful for filtering. Filtering or brushing as you could do in a FAD would update all the facets in the FAD to reflect the selection made. But in a dashboard that would only update the relevant metrics and leave the rest untouched. If you are interested in playing around with a metric (or a set of related metrics) it would make more sense to me to design a FAD for that purpose and use the dashboard as a starting point to drill down to the FAD from the metric on the dashboard. More sense than trying to force every dashboard to be a FAD that is.
I hope this post makes more sense to you than my first :-)
ltweedie said:
Michael
I entirely agree that dashboards/FADs showing predicitive models are a whole area that is very unexplored!
I did something very similar to this in my thesis in 1997 "The Influence Explorer" (a quick websearch will bring up the relevent papers) where we sampled a response surface model (Nelders generalised linear models to be precise) and then visualised it using interactive histograms, scatterplots and various other tools.
My experience in showing it to users was that it was immensely powerful as a tool to communicate a model. Suddenly analysts were able to make their models real. So that these models became real shared problem representations.
You could explore the relationship between inputs and outputs fluidly and easily.
I still haven't really seen this done in many other places and yet it is such a simple idea to put into practice. Has it?
Lisa
ltweedie said:
Zach/nixnut
Surely adding interactivity is about how much complexity you add to a tool.
I would say the important thing is not whether to add interactivity to a dashboard but whether it is justified in the context. So there will be situations in which allowing a user to interactively track back through time or drill down on a piece of data would be central to the dashboard design.
My hunch is that Responsive (dynamic) interaction enables a user to quickly compare many graphs in a way that is just not the same in static view. I guess we need some research to back this up - anyone know of any?
In an analysis situation we want to provide unlimited freedom. In a dashboard situation we want to provide key information quickly and clearly.
Thus I argue that in a dashboard design one should consider what key activities are going on and assess whether interactivity is appropriate. I believe there will be situations when it is very pertinent.
Lisa
Ted Cuzzillo said:
I like the idea of a “faceted analytics display.” I’m sure FADs are important. I just hate to see Stephen Few opt for this term because inept designers have spoiled “dashboard.”
Dashboard is a valuable metaphor and should be defended. I’m afraid FAD will be forgotten.
Isn’t a FAD just a dashboard with extra features? When they added tachometers to auto dashboards, did dashboards become something else? If you add new software or a new peripheral to your computer, isn’t it still a computer?
Perhaps we could think of it as a simulation dashboard--but still a dashboard. Calling it a simulation dashboard is still stronger than calling it a FAD.
Using “simulation” might force a modifier onto dashboards that don’t interact. How about “dumb”? Then we’d call the really bad dashboards just “dumber.”
Zach said:
Ted, I agree completely. FAD isn't likely to stick. Simulation (or perhaps interactive) dashboard is a good modifier.
said:
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