Feb 152017
 

Overview

Prior to working the last 18 months with Jeffrey Shaffer and Andy Cotgreave on the upcoming The Big Book of Dashboards I tended to look at BANs — large, occasionally overstuffed Key Performance Indicators (KPIs) —  as ornamental rather than informational.  I thought they just took up space on a dashboard without adding much analysis.

I’ve changed my mind and now often recommend their use to my clients.

In this blog post we’ll see what BANs are and why they can be so useful.

Examples of BANs

Here are several examples of dashboards featured in The Big Book of Dashboards, all of which use BANs.

Figure 1 -- Complaints dashboard by Jeffrey Shaffer

Figure 1 — Complaints dashboard by Jeffrey Shaffer

Figure 2 -- Agency Utilization dashboard by Vanessa Edwards

Figure 2 — Agency Utilization dashboard by Vanessa Edwards

Figure 3 -- Telecom Operator Executive dashboard by Mark Wevers / Dundas BI

Figure 3 — Telecom Operator Executive dashboard by Mark Wevers / Dundas BI

Why these BANs work

The BANs in these three dashboards are useful in that they provide key takeaways, context, and clarification. Let’s see how they do these things.

Key takeaways

If you had to summarize the first dashboard in a just a few words, how would you do that? The BANs shown in Figure 4 get right to the point.

Figure 4 -- Concise complaints summary (we'll discuss the colors in a moment).

Figure 4 — Concise complaints summary (we’ll discuss the colors in a moment).

The same can be said of the BANs in the Agency Utilization dashboards. By looking at the first two BANs in Figure 5, we can see that the agency made $3.8 million but could make $3.4 million more if it were to meet its billable goals.  That is the most important takeaway and it’s presented in big, bold numbers right at the top of the dashboard.

Figure 5 -- If we had to distill this entire dashboard down to one key point, it would be that the current sales are $3.8M but they could be $3.4M more.

Figure 5 — If we had to distill this entire dashboard down to one key point, it would be that the current sales are $3.8M but they could be $3.4M more.

Context

The Three BANs in the Telecom Operator Executive dashboard (Figure 3) not only provide key takeaways but also provide context for the charts that appear to the right of each BAN.  Consider the strip shown in Figure 6 which starts with the proclamation that ARPU (Average Revenue Per User) is $68.

Figure 6 -- What contributes to ARPU being $68, and how does prepaid ARPU compare to postpaid?

Figure 6 — What contributes to Postpaid ARPU being $68?

The images to the right explain everything that goes into making the $68 (Comparison of Postpaid to Prepaid, Voice, Data, Addons breakdown, etc.)

Note that the dashboard designer packs a lot of very useful information into the box that surrounds the BAN; specifically, ARPU is up $6 YTD, but is down in Q4 compared to Q3 (that’s how to interpret the line atop the shaded bars).

Clarification

The BANs in Figures 1 and 3 aren’t just conversation starters /  key takeaways, they are also color legends that clarify the color coding throughout the dashboard.

Consider the Complaints dashboard; the BANs indicate that Closed is teal and Open is red. Armed with this knowledge we know exactly what to make of the chart in Figure 7.

Figure 7 -- Everything prior to November 2016 is closed and only a handful of things in November are open.

Figure 7 — Everything prior to November 2016 is closed and only a handful of things in November are open.

The same goes for the Agency Utilization dashboard. The BANs inform us that blue represents Fees and green represents Potential so I know exactly how to interpret bars that are those colors when I look at a chart like the one shown in Figure 8.

Figure 8 -- Because the BANs told me how to interpret color, we can see that for Technology the company billed $883K but could bill an additional $1,762K if it were to hit its targets.

Figure 8 — Because the BANs told me how to interpret color, we can see that for Technology the company billed $883K but could bill an additional $1,762K if it were to hit its targets.

Conclusion

BANs can do a lot to help people understand key components of your dashboard: they can be conversation starters (and finishers) provide context to adjacent charts, and serve as a universal color legend.

Note: While I’ve tried to show how effective BANs can be I did not address how a particular font can help / hurt your BAN initiative. 

The Big Book of Dashboards co-author Jeff Shaffer has been studying font use and has a fascinating take on the new fonts Tableau added to their product this past year. You can read about it here.

 Posted by on February 15, 2017 1) General Discussions, Blog Tagged with: , , , ,  2 Responses »
Aug 112015
 

Overview

So, here’s why until recently I’ve recommended that my clients avoid large dashboards.

We’ve been working on a collection of killer dashboards and we’re all set to make a big presentation to the CEO. This thing is so high profile we get to use the executive conference room with the super bright projector and the 120-inch screen.

Our dashboards are all 1,325 x 1,000 pixels, but they’re going to look fantastic on that giant screen.

We’re incredibly well prepared.

At least we think we’re incredibly well prepared because when we arrive an hour early we discover the top resolution of that ever-so-fancy projector is 1,280 x 800 and our ever-so-well-crafted dashboards won’t fit on the screen.

Tableau Desktop and Reader will not scale the dashboard intelligently.

It doesn’t fit! Tableau Desktop and Reader will not scale the dashboard intelligently and we end up with the dreaded scroll bars.

Yikes, we have scroll bars! What are we going to do?

And don’t suggest using Tableau’s “Automatic” dashboard setting as it will just squish the different visualizations and won’t scale the fonts.

Let your browser scale the dashboard

While Tableau Desktop and Reader cannot scale your dashboard, Tableau Public, Tableau Online, and Tableau Server — with the help of your browser — can scale the dashboard, and scale it intelligently.

For example, using Tableau Public with the  “Zoom” feature in Google Chrome…

Using Google Chrome's "Zoom" Setting

Using Google Chrome’s “Zoom” Setting

… allows us to “fit” the dashboard on our large, but relatively low-resolution, screen.

It fits!  Thank you, browser.

It fits! Thank you, browser.

Conclusion

If you are presenting your work using Tableau Desktop or Tableau Reader then you either have to compose for the lowest-common-denominator screen or live with scroll bars.

If, however, Tableau Public, Tableau Online, or Tableau Server are an option, you should be able to use your browser’s zoom feature to make sure your dashboards fit on the screen.

May 232014
 

Overview

I’ve had a spate of requests from clients to show how survey responses rank across different categories and I’ve come up with a way that makes it very easy to see where the big stories are.

Note that this approach works for any measure that can be ranked, not just survey responses.

Let’s see what I mean…

Consider the bar chart below that shows the results to a survey question “indicate which of the following that you measure; check all that apply”.

Figure 1 -- Percentage of respondents that measure selected items, ranked from highest to lowest.

Figure 1 — Percentage of respondents that measure selected items, ranked from highest to lowest.

Traditional approach to showing rank within a category

Now, suppose you wanted to see the percentages and rankings broken down by different demographic components (e.g., location, gender, age, etc.).  There are myriad Tableau knowledge base articles and blog posts on how to do this and they lead to results that look like the one shown in Figure 2.

Note: Pretty much all of those articles and blog posts are now obsolete as they make clever use of the INDEX() function.  With Tableau 8.1 you can use the RANK(), or one of its variations, and not have to go through as many hoops.

Figure 2 -- Traditional approach to showing ranking within a category.

Figure 2 — Traditional approach to showing ranking within a category.

I find this a tough read.  Even if I add a highlight action it’s still hard for me to see where a particular item ranks across the four categories.

Figure 3 -- Ranking within a category with highlighting.

Figure 3 — Ranking within a category with highlighting.

Don’t try to show everything at once

My solution is place the Generation on the Columns shelf and to not show everything at once, but to instead allow the user to explore each of the possible responses and see how these responses rank across the different categories.

Consider the dashboard shown below where the top worksheet shows the responses across all categories.

Figure 4 -- Dashboard with no item selected.

Figure 4 — Dashboard with no item selected.

Now see what happens when we select one of the items in the list.

Figure 5 -- Dashboard with an item selected shows that items rank and percentage across different generations.

Figure 5 — Dashboard with an item selected shows that items rank and percentage across different generations.

Okay, not much to report here – Adrenaline Production is ranked first in three categories and second among Traditionalists, although Traditionalists’ measure it quite a bit lower than the other three groups.  Still, we’re not seeing any wide swings.

But look what happens when we select Breathing…

Figure 6 -- Breathing: our first big story.

Figure 6 — Breathing: our first big story.

Now that’s a big story!  And it pops out so clearly.

Reporting vs. interacting

This is all fine and good if you publish this as an interactive dashboard and you expect people to, well, interact; but what happens if you want to publish this as a static graphic in a magazine?

The solution is to find where the big stories are and show those in the magazine; that is, do the work for your reader and show him / her where the big differences are.  In fact, that is exactly what I’ve done in Figure 7.

How the dashboard works

Here’s how the top part of the dashboard is set up.

Figure 7 -- Configuration of top worksheet.

Figure 7 — Configuration of top worksheet.

Rank is defined as

   RANK_UNIQUE([CheckAll_Percent])

Note that we’re addressing the table calculation using Wording.

Notice also that Wording is on the Rows shelf.

The bottom part of the dashboard is set up like this.

Figure 8 -- Configuration of the bottom worksheet.

Figure 8 — Configuration of the bottom worksheet.

Goodness, we can’t tell what any of the bars mean because Generation is on the Columns shelf and Wording is on the Level of Detail and not Rows.  If you put it on Rows you get something that looks like this.

Figure 9 -- Placing Wording on the rows shelf tells a different and harder-to-understand story.

Figure 9 — Placing Wording on the rows shelf tells a different and harder-to-understand story.

The key takeaway is that we cannot make a single visualization that tells the story.  You need both the first and second visualizations working together.

A Filter and a Highlight Action

We use both a Highlight and a Filter action to make the two visualizations work well.  The Filter action is there to make the second worksheet disappear once you clear the selection in the first worksheet; The Highlight action highlights where the item appears in the second worksheet.

Here are the two actions:

Figure 10 -- Two actions tied to the same mouse click.

Figure 10 — Two actions tied to the same mouse click.

The Filter action is defined as follows.

Figure 11 – Definition of the Filter action.

Figure 11 – Definition of the Filter action.

This tells Tableau that when a user selects something from the first worksheet (Percent that Measure-Overall) it should filter the second worksheet (Percent that measure-by Generation)  by the field Temp.  Temp is just a string constant that I’ve placed on the color shelf; it’s only use is that we have to filter by something in order for the Exclude all values setting to work (and that is critical for the behavior of the dashboard.)

Here’s how the Highlight action is defined.

Figure 12 -- Definition of the Highlight action.

Figure 12 — Definition of the Highlight action.

This tells Tableau that when a user selects something from the worksheet on top, Tableau should highlight items in the second worksheet using Wording as the selected field (where Wording is the dimension we placed on the level of detail rather than on the Rows shelf.)

Conclusion

I’ve found this approach to showing of rank across categories very useful and it’s been a very big hit with my clients.  By placing the categories across columns and using highlight actions we make it very easy to see where the big differences are among different respondent groups.

Sep 302013
 

I recently attended the Tableau Customer Conference.  It was a great conference and if you are into Tableau you should definitely go to next year’s event (see http://tcc14.tableauconference.com/seattle/).

In any case, during the myriad networking opportunities I was very pleased by the number of people who told me how much they had gotten out of a blog post I had written over two years ago.  I decided I should revisit that post and see what, if anything, I would write differently.

So, before you read this post, make sure you read that post.

Did you read it?  The comments, too?

I think it holds up quite well but there are some things I would change.

Let’s go through the major points one by one.

Size Matters

I think I’m ready to retract this recommendation for two reasons:

  • The world has gotten a lot smarter about embedding Tableau Public visualizations.  Either folks make sure to get the size right or they have a link to where people can view the full-sized visualization.  Indeed, it’s been awhile since I’ve seen anything that was really mangled.
  • I would hate to handcuff people from doing work that warrants a larger canvas.  For example, have you looked any of the things Kelly Martin is doing over at her VizCandy blog?  Go ahead, click here (but do come back when you’re finished.)

Some great stuff going on there — in fact my reaction when I first saw what she’s producing was “damn, I’m really going to need to ‘up my game'” — but I’ll blog about this at a later date.  In any case, while the constraints of a 650 pixel-wide canvas can in fact be very useful as it forces you to pare down the fluff, by all means use a wider canvas if your viz warrants it.

Never Use Red and Green as Contrasting Colors

I got some grief about this one, but my rationale is still spot on (more about this in a moment).  That said, I will modify the rule so that it reads as follows:

Never use red and green as contrasting colors without an affordance

And just what do I mean by an affordance?

Consider your typical traffic light.  How do people with red-green color blindness deal with traffic lights?  The answer is that they look at the positioning of the light: red is on top, yellow in the middle, and and green is on the bottom. If the light is configured sideways, red is left, yellow is in the middle, and green is to the right.  If there were only a single light that changed color there would be many more accidents — and not just because of confusion among the color-blind; the non color-blind fine the positioning very helpful as well.

So, if you like red and green or feel you must use it, the following two visualizations are acceptable as they both contain an affordance.  Specifically, The first contains arrows that point up or down and the second has bars that ascend or descend.

Affordance1

 

Affordance2

The following view is not acceptable as there is nothing besides the red and green to telegraph high values vs. low values.

NoAffordance

As for having to worry about this at all, I attended Maureen Stone’s session on Best Practices for Using Color: How and Why and came away with two key findings.

1) This woman is brilliant; and,

2) Yes, you need to worry about this. So do yourself and your interactors / viewers a favor and do as I suggest.

Usability

There’s nothing I would remove from this section, but there is so much more that I should add.

I’m not going to do that right now (sorry).

But…

… as I re-read my post there’s one idea I really want to underscore and that is to ask at least one other person to “fly” your dashboard before you publish it.  That person will both break the thing immediately and find the major stumbling points.  Really, it’s amazing how quickly a set of fresh eyes can find all the flaws.

Hover Help

I still completely endorse this practice but will provide one caveat about creating the ersatz calculated field called “Help”: adding this custom field can, in some cases, really slow down performance if you have a large database and are executing a big query against that database.

The very simple workaround is to create a very sparse additional data source (you can do it in Excel) and create the custom calculation in that additional data source.  Indeed, I’ve gotten in the habit of placing my help and navigation control scaffolding in a secondary (and very small) data source.

Navigation – Dealing with Multiple Tabs

My major takeaway in reviewing this is that I can’t wait for Tableau 8.2 to be available as it will have a new feature called Story Points that will be WAY better than the click forward / click back navigation buttons I recommend when publishing multi-tabbed workbooks.  I only saw a very brief demo of Story Points but what I saw was absolutely beautiful.

In the meantime I still recommend you hand-chisel these forward and back buttons and, should you run into performance problems, put any calculated fields you use in a secondary data source as described in the “Hover Help” section above.

Engagement

I agree with everything I wrote but think my examples are dated as the state-of-the-art has improved enormously in the past two years.  In particular, Tableau’s ability to support floating elements has made it easy for the design-savvy among us to do some great things.

By the way, now would be a good time to revisit Kelly Martin’s VizCandy blog.  And when you’re done check out this post at Anya A’Hearn’s DataBlick web site.

They draw you in, don’t they?

As fun and inviting as all this stuff is I have found the best way to get people engaged is to somehow make the visualization about the person who is viewing it.  One of my favorite examples is the one below, a much-scaled down version of an interactive salary dashboard I built awhile back.  The reason this works is that people want to know (and know immediately) how they compare with their peers.  So, if you really want people to use your stuff your “stuff” should be able to answer questions like these:

  • How does my department compare with other departments?
  • How does our company compare with others?
  • How does my performance compare with my peers?

If you do this people will interact with your dashboards, I guarantee it.