Stephen Few is respected for his unflinching critique of
poor dashboard design and ever since he trained me in the subject I look at
dashboards through a different lens.
I had this in my mind when I went to SITS2013 this week
where there were over 30 IT Service Management (ITSM) software vendors jostling
for attention. When you read the brochure-ware its hard to tell them apart;
they all ‘do’ ITILv3, SaaS, mobile apps and so on. Could ITSM tools be compared
on their ability to effectively visualise the critical few measures that IT teams need to
make decisions and act on them? Are the software vendors enlightened enough to
help you with this challenge or will they leave you exporting data to Excel in
frustration once the novelty of their mobile app has worn off?
I’ve collected and critiqued a rogues gallery of 8 dashboards
being demonstrated enthusiastically on vendor’s exhibition stands. I’ll concede
that these displays could, I hope, be customised to alter the visualisations. I’m
more interested though in how these products look when they come out of the box
because:
a.
This is what vendors think is ‘good’ design
and spend development dollars embedding in their products.
b.
This is what users will end up looking at daily
unless they invest in doing something different.
Mr Few classifies 13 dashboard design pitfalls in
all but here are the 6 most common:
Pitfall 1. Exceeding the boundaries of a single screen.
Pitfall 2. Supplying inadequate context for the data
Pitfall 3. Choosing inappropriate display media
Pitfall 4. Ineffectively highlighting what’s important
Pitfall 5. Cluttering it with useless decoration
Pitfall 6. Misusing or overusing color
So here’s my assessment of the 8 dashboards with their
pitfalls in brackets:
The most important display region of the dashboard should
be the top left of the screen. This one has a navigation tree which isn’t the
best use of this space and the dark blue of this panel draws the eye away from the
charts themselves (4). There’s a huge amount of white space which, whilst
useful for separating regions, is wasteful of valuable screen real estate which
is probably why there’s a need for so much navigation (1)
There are 4 different chart types (3) most commit the sin
of being in 3D which destroys comparisons, (5) one of which commits the
cardinal sin of being a pie chart where rotational angles and areas are hard to
evaluate (3). The bar chart bottom left is the best of the bunch but the bars
aren’t sorted and there’s no good or bad context (2). In general the colours
have no consistent meaning (6).
This one has different audiences in mind, most of the
panels seem to be job lists for a service desk operator but we have also panels
for SLAs and panels for service response time (2). The use of lists allows some
density but provides very little context (2). As with many dashboards speedometers
have been used as though a car-driving metaphor somehow adds more meaning. The
meters waste space and are complex to read (3) and the traffic lights assume
you aren’t colour blind and should ideally just highlight exceptions (6). The
worklist in the top right probably has the most urgency for a user and if so
should be positioned top-left (4). The PC icons are also wasteful of space and
only offer a binary good/bad state when a variance from target or a time series
would give more context (2). The dark green and cyan panels also draw the eye
to low value data (4).
This example at least give prominence to the encoded data
over decoration but we have fat axes on the charts (5) and a pie chart with an impossibly
large number of part-to-whole pieces which aren’t sorted in any order (3) and
multiple colours (6). One of the bar charts is a least sorted by value but
there’s no target context (2) and the use of a red fill implies ‘bad’ (4 & 6).
The panels could probably be resized but they make poor use of space and the region
and table headers are distracting decoration (5).
This is a collage of charts on a presentation slide which
probably intends to illustrate how flexible the reporting is. Everything is in
3D (3), we have a busy pie chart (3) and the tables are superfluous because
values are already encoded in the charts (3). The strong axes and grid lines
don’t communicate any data (5) and all the charts have multiple colours which
invite unwanted comparisons between them (6).
This dashboard suffers from too much embellishment; the
designs of the speedos, traffic lights, meter panels and borders draw the eye
but don’t communicate any data (5). The white on black meter font is hard to
read and could be combined in a single visualisation such as a bullet chart
with an integral target rather than using a separate traffic light (3). The dense
layout make good use of the display space but the most valuable screen real
estate is taken up with a filter panel and logos (5).
This dashboard has a few things to commend it; the use of
sparklines (microcharts) in the tables provide time series context without
taking up too much space although the time periods are unclear. Because the
sparklines have embedded targets, the boxy up/down arrow boxes are a little
unnecessary but the red icons do draw attention to the Critical SLAs in breach.
Since this also seems to be the most important summary information it should be
positioned top left with the other information grouped more logically eg. 7
day/12 month request volumes together, category comparisons together.
Unfortunately
the other visualisations exhibit several pitfalls, especially the use of
multiple chart types for similar categorical data, 3D effects, shading effects
and a pie chart. Sadly, a well-intentioned attempt to show performance over
time in context with target bands fails because the red shading is too
dominant, giving the impression that something is in ‘critical’ state
even though the signal is normal. Because of the wasteful size of these charts,
these red bands dominate the dashboard.
Whilst this display in generally quite pleasing to the
eye we have multiple categorical chart types and pie charts (3), 3D &
shading effects (5) and seemingly random use of colour (6). The size of the
panels and the filters/controls take up valuable screen estate which would also
imply additional that drilldown & navigation is required (1). In the top
left chart the time series axis labels are unreadable and the data point
markers obscure the patterns in the data with red points implying ‘bad’ (6).
There’s some logic in putting a user's high priority
information panels at the top left of the screen but presumably a drill down is
needed in each area to give context (1). These values would have much more
meaning if some comparison could be made visually against target or over time with
a sparkline. The display space usage is generally inefficient and the meter in
particular takes up a lot of space and is less effective that say, a bullet
chart (3). The charts are in 3D with a shaded background and strong gridlines
(5).
In summary, and rather worryingly, I didn’t see a single
ITSM tool at SITS which had put Stephen Few’s wisdom into practice. What does this mean for IT organisations? Bad dashboard and report design impairs the
reader’s ability to rapidly analyse and interpret data in order to make better
decisions and monitor the effect of actions. Using the default, wizard-driven
visualisations in these ITSM tools are potential barriers to acquiring the evidence,
meaning and insight needed to get a return on investment from ITSM software.
What does this mean for ITSM deployments? Performance measures should be deliberately defined and visualised to drive the right results for a particular audience. Dashboards should at least be customised as far as possible to address these pitfalls
for interactive use. For periodic reporting there are options to use external Business
Intelligence tools, perhaps shipping data out to a cost effective SaaS
offering, or firing up the familiar Excel with PowerPivot and publishing via
Sharepoint.
Unless the ITSM vendors wake up to visualisation as a potential differentiator
in an otherwise mature market, more investment and effort will be needed by IT
organisations to effectively communicate meaningful measures and execute
performance improvement.
