Dr. Rafael E. Matos
Senior Operations Research Analyst – WBB Inc.
President – Military Operations Research Society (MORS)
Abstract
•
As described by Stephen Few, a leader in visual presentation of data, we experience
the world predominantly through our eyes. Recognition of vision’s unique power has
led to the development of many new forms of visual communication. Our eyes are now
seen as valuable targets for visual content hoping to make an impression. Some forms
of visual communication remain primitive by comparison, crudely attempting to deliver
information that is far too important to be displayed so poorly.
–
–
•
Graphs — the visual representation of quantitative information — are often sad examples of a
crude visual medium. This is particularly sad, because the skills and technology needed to
effectively present quantitative information in graphs are not complicated, but they remain rare
nonetheless. Graphs were invented to bring meanings in quantitative data to light, which could
not be discerned from a table of numbers. Whether you display data in a table or a graph
should not be an arbitrary decision. They serve very different purposes.
Tables work marvelously when you wish to look up particular values or you need precise
values. Graphs, however, make meaningful relationships between values visible by giving them
size, shape, and color. There is no substitute for a well-designed graph when you wish to see
or communicate meaningful trends, patterns, and exceptions in quantitative data.
We will examine and highlight some of the proven most effective ways to set up and
display analytical information in simple, yet effective pictures that would increase the
ability of your audience to really SEE what you are SAYING. We would also highlight
common pitfalls of visual design of charts and graphs and propose a set of measures to
fix these for effective communication of the real message.
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Overview
• Background
• Graphical Displays
• Complex Charts
• Multivariate Chart Example
• Summary
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“I See…” Or “I Understand…”
One of the leading lights in visualization research today is Dr. Colin Ware of the University
of New Hampshire. He expertly explains the importance of visualization and how it works.
“Why should we be interested in visualization? Because the human
visual system is a pattern seeker of enormous power and subtlety. The
eye and the visual cortex of the brain form a massively parallel
processor that provides the highest-bandwidth channel into human
cognitive centers. At higher levels of processing, perception and
cognition are closely interrelated, which is the reason why the words
‘understanding’ and ‘seeing’ are synonymous. However, the visual
system has its own rules. We can easily see patterns presented in
certain ways, but if they are presented in other ways, they become
invisible… The more general point is that when data is presented in
certain ways, the patterns can be readily perceived. If we can
understand how perception works, our knowledge can be translated
into rules for displaying information. Following perception based
rules, we can present our data in such a way that the important and
informative patterns stand out. If we disobey the rules, our data will
be incomprehensible or misleading…”
(Information Visualization, Second Edition, Colin Ware, Morgan Kaufmann Publishers, 2004, page xxi)
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“I See…” Or “I Understand…”
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“When you change the way you look at
things… the things you look at change”
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I Need to Present Data
• What are the results of the analysis?
• What is the best means to display them?
• Table, graph, both, neither needed to
communicate the message?
• If a graph, what is the best means to show the
values?
• Where to display variables?
• Where would you place other objects?
• Is there a particular data to highlight?
• Is there a message I need to convey?
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We will always
have
PowerPoint…
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Sadly, “we will always have Power Point”
• Keep them simple.
• Use few words.
• Make sure the words are spelled correctly.
• Have a time budget for your slides.
• DON”T READ THE SLIDES!!
• Make sure the material on the slide is large enough that it can be seen in the
back.
• Don’t read the slides
Force them to look at you and to listen to you by having nothing else for them to do.
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An Example of Data
Anscombe's Quartet comprises 4 data sets of 11 points each:
I
For all four:
II
III
IV
x
y
x
y
x
y
x
y
10
8
13
9
11
14
6
4
12
7
5
8.04
6.95
7.58
8.81
8.33
9.96
7.24
4.26
10.84
4.82
5.68
10
8
13
9
11
14
6
4
12
7
5
9.14
8.14
8.74
8.77
9.26
8.10
6.13
3.10
9.13
7.26
4.74
10
8
13
9
11
14
6
4
12
7
5
7.46
6.77
12.74
7.11
7.81
8.84
6.08
5.39
8.15
6.42
5.73
8
8
8
8
8
8
8
19
8
8
8
6.58
5.76
7.71
8.84
8.47
7.04
5.25
12.50
5.56
7.91
6.89
• Mean of the x values = 9.0
• Mean of the y values = 7.5
• Equation of the least-squared regression line is: y = 0.5x + 3
• Sums of squared errors (about the mean) = 110.0
• Regression sums of squared errors
(variance accounted for by x) = 27.5
• Residual sums of squared errors (about the regression line) = 3.75
• Correlation coefficient = 0.82
• Coefficient of determination = 0.67
(F.J. Anscombe, "Graphs in Statistical Analysis," American Statistician, 27 [February 1973], 17-21)
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What does this mean ?
• Analysis of the data suggests
that it is similar
• But is it ?
• Let’s look at the data when
it is plotted
Completely Different Data Sets
Using line plots reveals the differences among the data sets
I
III
y = 0.50x + 3.00
R² = 0.67
16
16
12
12
8
8
4
4
0
y = 0.50x + 3.00
R² = 0.67
0
0
5
10
15
20
0
5
II
16
10
IV
y = 0.50x + 3.00
R² = 0.67
16
12
12
8
8
4
4
0
15
20
y = 0.50x + 3.00
R² = 0.67
0
0
5
10
15
20
0
5
10
This quartet is used as an example of the importance of looking at your data before analyzing it in
Edward Tufte's book, The Visual Display of Quantitative Information.
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15
20
Looking Beyond Data Points
•
•
•
•
•
Spatial Plot of Hits Taken by Returned Aircraft
Each mark = one or more entry holes caused by damage mechanisms
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Task: Determine
what survivability
enhancements need
to be added to
tactical aircraft
Data collection:
location of entry
holes on aircraft
returning from
combat missions
What is this data
telling you?
What do all these
data points have in
common?
What is missing?
Overview
• Background
• Graphical Displays
• Complex Charts
• Multivariate Chart Example
• Summary
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Text Charts
• Some analytic briefs require you
to use a lot of text charts
• Try to skip a line between all
major bullets – like this
– Most organizations have their
own template and PowerPoint
Rules Of Engagement (ROE)
• Use the PowerPoint template
– Avoid adding a text box
– Option to add a new text chart,
paste the formatted text box on
the chart where needed, and
adjust the size
– Bill Gates will take care of the rest
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• Using colored text often
helps
• BOLD text preferred
when using colors
• Darker shades better
– Than many standard
colors
Standardize your message box
Dark box with white text
Dark text on light color
Examples of Graphical Displays
60000
OM
Non-Productive
Workload (Hrs/Week)
Productive
87
Sleep
Messing
Personal Needs
Sunday
Training
Service Diversion
PM
30000
20000
10000
Watchstanding
Maintenance
•
Pie Charts show what proportion of the total each category
comprises
Thousands
–
rs
in
Department
•
If knowing about a “part of the whole” is an important
consideration, then pie charts are a better choice
8
Stacked Bar Charts display both the totals and the elements
in each category
800
7
Hours Allocation
Hours Employed
700
6
600
1st term EAOS
Career EAOS
USNR EAOS
Retire
Attrition
Trng Attrition
5
4
3
500
400
300
2
200
1
100
0
0
J
•
O
th
e
14
3
Ad
m
14
7
De
ck
Ai
r
0
Su
4
CM
D
56
FM
CS
O
56
SD&T
40000
AI
M
14
OUS
50000
pp
ly
Re
ac
to
r
W
ea
po
ns
O
pe
ra
tio
ns
En
gi
ne
er
in
g
81
F
M
A
M
J
J
A
S
O
N
D
Sand Charts display the same data as a stacked bar chart, but as a
function of an ordered sequence (such as time)
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0
•
5
10
15
20
25
30
Area & Column Charts allow the display of discrete data against
a backdrop of continuous data
Line Charts or Plots
•
•
•
•
•
•
•
•
•
Graph shows the TOS an aircraft has versus its
range from the base or ship
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Excel default is not the
optimum
Font is 10 pt
Line size and color are OK
Legend not bad but small
Now make some minor mods
Recommend 12 point bold for
text and 14 pt for axis labels
and titles
Use different line styles
Color helps
Use legend or arrow or title box
to reinforce
Line Charts (2)
•
Aircraft TOS vs. Range
•
(hrs)
•
•
•
•
(NM)
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•
Improvements aid data
presentation
Font changed to 12 pt
bold
Label font increased to
14 pt
Line colors modified to
use dark colors – try to
avoid pastels
Use different line styles
for B&W copies
Paste as a picture, not an
Excel chart – allows you
to crop
Legend moved to the top
Line Charts (3)
•
Help the audience follow
the data by adding
“directions” on how to
view the data
•
Purpose is to compare
the TOS across the
aircraft at the range
needed to execute the
mission
•
Adding simple arrows
gets the entire audience
focused on the issues
quickly
(hrs)
Aircraft TOS vs. Range
(NM)
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Line Charts (4)
(hrs)
Aircraft TOS vs. Range
Minor delta ~ 1.0 hour
•
Analyze data on the plot
to save time and get to
the point
•
Assume the scenario in
use has a 600 NM range
to station for A/C “A”,
A/C “B”, and A/C “C”
•
Adding simple arrows
gets the entire audience
focused on the issues
quickly
3.0 hours
less TOS
(NM)
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Pie Charts
• Useful format
• Example shown is the breakdown
of work day of a sailor
• Good format for showing
breakdown of contributions to a
sum
– Example is where a segment of
the population or system is
identified by its relative size
– The contribution to the product by
this segment is then shown
– Normally to show how one
segment is key to production or
has a higher workload
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Stacked Bar Charts
Workload (Hrs/Week)
60000
OM
OUS
50000
SD&T
FM
40000
PM
30000
CM
20000
10000
O
th
er
s
in
Ad
m
De
ck
CS
O
D
AI
M
ly
Re
ac
to
r
W
ea
po
ns
O
pe
ra
tio
ns
En
gi
ne
er
in
g
pp
Su
Ai
r
0
Department
• Stacked Bar Charts display both the totals and the elements in
each category
• Good for showing the elements contributing to the total
– Also to show differences in the contributing elements of a system
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Area & Column Charts
• Area & Column Charts allow the display of discrete data against a backdrop
of continuous data
• Useful in specific situations
• Used in manpower studies
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Sand Charts
•
•
•
•
Sand Charts display the same data as a stacked bar chart, but as a function of an
ordered sequence (such as time)
Common use is aircraft inventory over time
Good format to show big picture and total inventory against the requirement
Other formats needed to present more detailed assessment
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Combination Chart
• Good format to display related data on a single chart
• Data should be relevant to each other
• Help your audience by clearly noting the scales and relevant axes
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Quadrant Type Charts
• Data sometimes is best displayed on an X – Y plot
• Not always obvious what the data tells us
• Following example comes from the Broad Area Maritime Surveillance
Unmanned Aerial Vehicle (BAMS UAV) Manpower Concept of Operations and
Manning assessment
– Five different alternatives were evaluated
– Key factors
• Operational capability or ability to support the Fleet
• Manpower demand on the Navy – less is better
– When none of the five appeared optimum, derivatives to five manning concepts
were constructed – take the best and modify
– Results shown on next chart
– Note the arrows to focus the audience quickly to results
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BAMS MP Assessment Results
More Capability
8 Unit Manning Alternatives Evaluated
Fewer Personnel
• Alternatives 6, 7 & 8 evaluated in addition to the initial five alternative concepts
• Alternative names specific to the analysis and are not relevant for our discussion
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Bubble Charts
• Allows you show multiple variables on a single chart
– X axis variable, Y axis variable, and the bubble
– Bubble can be colored to show another variable
– Bubble sizes can vary to show magnitude: cost, priority, importance, …
• Preferred to most 3D format charts
• Full size example on the next slide
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Sample Bubble
The axes show the gaps impact on the warfighter in a
Major Contingency Operation (MCO) and in the Global
War On Terrorism (GWOT), while the colors show the
likelihood of occurrence
Impact on MCO/GWOT outcome
Colors show likelihood of occurrence
Alternatives are numbered in this
example to avoid classifying the chart
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Classification and Alignment of Requirements
Using Business Rules
Consequence (Importance)
Level of Effort
High
High
Standard
Low
Med
Consequence and Quality
aligned, but LOE suggests
process and/or personnel
inef f iciency.
Low consequence, but High quality.
With LOE high, you are paying a
premium f or High quality that may not
be needed. Take risk and reduce
requirement to bring it in line with
importance.
Low
Low
Medium
Quality (Performance)
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High
Stoplight Charts
• This is a very useful format
especially when the analysis is
qualitative in nature
• Good when the audience has a
common understanding of the
issues being analyzed
• Must define each stoplight
• OK to have multiple sets of
definitions on one chart
• If your audience gets focused on
debating the definitions then
choose another format
• Stoplights can be added using
“Insert – symbol” (Ω) command
– Wingdings 2 has a good bullet
• Or, paste a circle
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Common stoplight definitions
• Green 
– Meets requirement
– Fully capable
• Yellow  or
– Partially meets requirement
– Acceptable
– Partial capability
• Red 
– Not operationally suitable
– Lacks required capability
•
Blue  (not always used)
– Exceeds requirement
– Meets objective requirement
– Increases unit capability
Weapon Guidance Factors
Weather
ECM
Target
Area
Clutter
Radar






Imaging Infra Red






GPS






Radar + Data Link
/





GPS + Data Link






IIR + Data Link






Weapon Guidance

No Impact
Impacted
.

Major Impact 
Decoy
Jamming
Data Link GPS
Use a light background color so the yellow contrast
The circle with an outline ( ) shows better but you
must paste and then align horizontally and vertically
Overuse of Color
•
•
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Issue: overusing color can detract from the message
Read the COLOR of the words below
Using Color
100
98
96
94
• Issue – when to use color to
highlight or differentiate
across the data output
92
90
88
86
100
98
• Keep it simple when the
data is the same category
and the variable (e.g.) is
different fiscal years
96
94
92
90
88
86
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• Top column chart is
adequate while the multicolor lower chart provides
no additional value
Visual Pattern Recognition
• Do not include visual differences in a graph that
do not correspond to actual differences in the
data.
500
450
102
400
100
350
98
300
96
250
94
200
92
90
150
88
100
86
50
84
0
FY00
FY01
FY02
FY03
FY04
FY05
Gains
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FY06
FY07
FY08
FY09
FY10
FY11
Losses
FY12
FY13
FY14
FY15
Using Color (2)
Mean days
between Supplies
Replenishment
Mean days
between Refueling
•
– The analysis consists of a series of column charts
where we want to facilitate the ability to follow the
trends
– The chart compares bars or columns of 2 or more
variables on the same plot
Weapons Employed & Aircraft Lost
16
14.56
14
12
10
8.11
8
6.11
• Excel does this for you
5.44
6
– There are others
4.3
4
2.00
2.00
2
0.00
0.00
0
Profile 1
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Color differentiation useful in several situations
Profile 2
Profile 3
Profile 4
•
Note that lower chart has values listed to assist in
following the analysis
3D Versus 2D
Mean days between Supplies
Replenishment
• Top column chart adds no
value with 3D
– Data is relatively simple
• Lower chart is a good
example of when to use 3D
– Allows multiple factors to be
depicted on a single chart
• Clearly shows that the P-3
and P-8 have similar
performance, the EP-3 is
less, and the E-2D has
significantly less endurance
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Alternate Displays
• Good summary on a single chart
• Avoid the pink shades if possible
• Don’t presume Bill Gates is a color whiz
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Alternate Displays
• No
• Pastels are for the Easter Bunny
• Selective use of lighter colors OK
when they complement or highlight
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Alternate Displays
• Note that black, grey, and white are
perfectly adequate for the 3 variables
• Chart should be consistent with data
labels on the columns
• Two range columns (above) use the same
Y axis scales – correct use !!
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More on Simplicity
Display neither more nor less than what is relevant to your message.
• Extraneous content not only wastes people’s time, it makes it harder for them to get to the
data and its meaning
• Don’t design a display that doesn’t contain everything people need to make sense of it.
• Include every piece of information that is part of your message — even notes to explain what
might not be clear — otherwise you’re communicating poorly
Investments Distribution
Investments Distribution
$30
Monthly Amounts
Monthly Amounts
30
25
20
15
10
5
0
Stocks
$20
$15
$10
$5
$0
Bonds
Investment Type
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$25
Annuities
Mutual
Funds
Stocks
Annuities
Bonds
Investment Type
Mutual Funds
Scales
Mean days
between refueling
• Issue – Excel will select for you the “best”
scale to display the range of data
• Common within one brief for the scale to
change multiple times
– May be intentional or unintentional
• Scale change often not an issue but will
may some reviewers skeptical
Mean days between Supply
Replenishment
– Are scales tailored to skew the output?
• Using a previous example, the relative
difference does not change but the Y axis
scales change
– In this example, probably not a factor
Note: scale change
from previous chart
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• Disclaimer an option or use the same
scale on all charts
Scales (2)
•
•
•
•
Another issue is one or both axes not starting
at zero
In the upper chart, the overlap of the data
may make the chart useless
The lower chart presents a clear distinction
across the 5 alternatives
Note that the upper chart Y axis starts at zero
– Starting a higher value serves to expand the data
plots in the lower chart
•
Questions
– Was the scale change from necessity because
this is the issue?
– Or, was the scaled changed to advocate an
alternative?
– Is the difference so minor that this is the insight?
•
May give a misleading impression unless
noted explicitly
– Common in the media
•
Recommend using 0/0 for the origins on all
data plots
– Note clearly on the chart when origin is not zero
(truth in lending)
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Tables
SCORECARD - Metrics & Attributes of Facilities
Metric 1
Metric 2
Metric 3
Metric 4
Metric 5
Facility 1
3127
3013
9663
3.09
3.21
Facility 2
274
289
1109
4.05
Facility 3
656
994
3547
5.41
Facility 4
645
1172
5268
Facility 5
452
485
1605
Facility 6
38
72
Facility 7
15
22
Facility 8
396
311
Metric
6
Metric 7 Metric 8 Metric 9
Facility
$313,578
$100
$104
$32
3.84
$90,206
$329
$312
$81
3.57
$183,903
$280
$185
$52
8.17
4.50
$235,278
$365
$201
$45
3.55
3.31
$91,193
$202
$188
$57
239
6.29
3.32
$1,138
$30
$16
$5
192
12.80
8.69
$1,223
$82
$55
$6
748
1.89
2.40
$29,027
$73
$93
$39
• Tables routinely used to summarize data
• This table represents a typical data summary
• Improvements to consider
• Use the same decimal places for consistency
• Do not use more decimal places than needed
• What does the delta of 0.0031 mean ?
• Help the audience understand the format
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Facility
Attributes Score
0.70239
0.65034
0.48051
0.71529
0.65003
0.56279
0.38204
0.43205
Tables (2)
SCORECARD - Metrics & Attributes of Facilities
Facility
Facility 1
Facility 2
Facility 3
Facility 4
Facility 5
Facility 6
Facility 7
Facility 8
•
•
•
•
Metric Metric Metric Metric Metric Metric Metric Metric Metric
1
2
3
4
5
6
7
8
9
3127 3013 9663
3.09
3.21 $313,578 $100 $104
$32
274
289
1109
4.05
3.84
$90,206 $329 $312
$81
656
994
3547
5.41
3.57 $183,903 $280 $185
$52
645
1172 5268
8.17
4.50 $235,278 $365 $201
$45
452
485
1605
3.55
3.31
$91,193 $202 $188
$57
38
72
239
6.29
3.32
$1,138
$30
$16
$5
15
22
192
12.80
8.69
$1,223
$82
$55
$6
396
311
748
1.89
2.40
$29,027
$73
$93
$39
Facility
Attributes
Score
0.70239
0.65034
0.48051
0.71529
0.65003
0.56279
0.38204
0.43205
Increase font so easily readable
Use background fill to show viewer whether this is a matrix or data in rows or
columns
Use different format for the header row or columns and align to the bottom or left
side
Center data except dollar figures that present best when right justified
46 of 62
F-35 Weapon Carriage
Good example of a table with graphics
Internal
11
Loading 1 - (2) GBU-32
10
9
8
7
6
5
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
4
Loading 2 - (3) GBU-32
GBU-32
1K JDAM
Loading 3 - (4) GBU-32
Loading 4 - (5) GBU-32
Loading 5 - (6) GBU-32
Loading 6 - (7) GBU-32
NO TANK
Loading 7 - (8) GBU-32
Loading 8 - (9) GBU-32
Loading 9 - (10) GBU-32
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
AIM-120
Loading 10 - (11) GBU-32
GBU-31
2K JDAM
Loading 11 - (2) GBU-31
Loading 12 - (3) GBU-31
Loading 13 - (4) GBU-31
Loading 14 - (5) GBU-31
MIX
LOAD
Loading 15 - (6) GBU-31
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NOTAIM-120
READILY AVAILABLE
AIM-120
Loading 16 - (2) GBU-32 / (2) GBU-31
Loading 17 - (2) GBU-32 / (4) GBU-31
3
2
1
Dashboards…
From This…
…To These
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Dashboards
Elegance in communication is often achieved through simplicity of design.
Accessions
Re-Enlistments
Transfer Gains
Ops Returns
Grad Education
MWR Satisfaction
Total Force %
49 of 62
Overview
• Background
• Graphical Displays
• Complex Charts and Primers
• Multivariate Chart Example
• Summary
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Complex Plots
• Briefer: “As you can clearly see,
admiral, the driving factor on
aircraft required is the distance
to station”
• Admiral Hornblow: “No, I can’t”
• So how do we use a plot that is
complex, has lots of good
information, and get the
audience on our side?
• Use a primer
• Note: this is a Slice V chart that
displays 3 or 4 variables
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Complex Chart Primer
For a given Distance to Station
#A/C Req’d is the minimum
number of aircraft required to
execute the mission assuming
they are all 100% available
Loiter is the Time on Station
shown by shading legend
Dist to Sta
200
300
400
500
600
700
800
900
1000
#A/C Reqd Loiter Time
2
4.47
2
3.95
3
3.43
3
2.92
4
2.40
4
1.88
6
1.37
9
0.85
>20
0.30
#A/C Req’d adjusted for each
MC rate to achieve 90%
Confidence that the mission
will succeed translates to
Total # A/C Required
MC Rate is Availability (Ao) =
0.85 / 0.90 / 0.95 / 0.99
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Shading is: Time On-Station (Hours)
Primer (2)
3
•
Use an example to help the
viewer understand the
goodness of the chart
•
Provide interpretation
guidelines before
presenting the data
2
4
1.
2.
1
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Begin at MC rate = 0.90
Follow plot to a range of
800 nm
3. Go to the vertical axis or wall
4. Follow wall to annotated axis
8 aircraft required with these
parameters
Primer (3)
Aircraft required increases significantly
beyond 700 nm
•
While not a primer, the data
plot can be annotated to
enhance the comprehension
of the analysis
•
Example
– This is representative of
analysis of surveillance
aircraft
– While the MC rates are high
here (represents
commercial aircraft
availability), the MC rate
had minor impact on the
force structure
– Driver: where is the fight
relative to the basing
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Aircraft required insensitive to MC rate
- except at max range to station
More on Primers
• Use detailed lead-in charts to set the stage before getting into
the analysis
• Intent is to make the audience comfortable with how you will
present the data
• You want to get the data presentation discussion complete
before you get to the meat of the analysis
– Focus on the output only
• PowerPoint animation features used to “build” to show the
flow
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Comparing Data Output
This chart could be annotated as:
• DDG can go 20% longer between refueling than
a CG
• 1 day delta divided by 5 day CG interval
• Not a good use of %
• The 1 day delta is not operationally meaningful
Mean days
between refueling
• Focus is using percentages
• Analysts always want to do
their job – analyze results
• Percentages can be misused
• Pitfall is that a well-intended
assessment can be rightfully
criticized by the audience
– Solid analysis can then be
torpedoed by a simple error
• Comments on the left are
accurate – but are they
operationally meaningful?
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Overview
• Background
• Graphical Displays
• Complex Charts and Primers
• Multivariate Chart Example
• Summary
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Multivariate Data Displays
SUW Engagement versus 20 small boat targets
= Reloader Capacity Expended
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One chart displays Kill Range, time, rounds to kill, threat envelope and
magazine loads expended for three different engagement scenarios
Alternate Displays
• Note that black, grey, and white are
perfectly adequate for the 3 variables
• Chart should be consistent with data
labels on the columns
• Two range columns (above) use the same
Y axis scales – correct use !!
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Overview
• Background
• Graphical Displays
• Complex Charts
• Multivariate Chart Example
• Summary
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Summary
• Lines, columns, rows, tables, and stoplights are among the tools you
can use to present the data and/or data output
• Ensure data charts of any type are legible
– Clear legends
– Axes labeled and font size legible
– Lines thick enough to be easily seen, vary colors and/or dashes as
needed
• Use lead-in tutorials, examples when data format may be complex
• Use arrows to show the flow from the independent to the dependent
variable (the answer or output)
• Table rows or columns shaded to emphasize data orientation
• Label the data on (e.g.) columns
• Use minimum decimal places
• Highlight with circles, boxes, ovals, key data – make it stand out
• If the audience must ask you about the chart format in the middle of
data results discussion, you failed
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Bibliography
The Visual Display of Quantitative Information, Edward R. Tufte, Graphics Press, 1983. "A tour de force." The
baseline and initial standard for this topic.
Information Dashboard Design: The Effective Visual Communication of Data, Stephen Few, O'Reilly Media,
2006. This book addresses the visual design of dashboards. Written by one of the foremost experts in the field of
data visualization.
Show Me the Numbers: Designing Tables and Graphs to Enlighten, Stephen Few, Analytics Press, 2004
The first book to provide practical and comprehensive instruction in the design of business tables and graphs.
Compared with Tufte's book on charting, Few is more applied and provides more explicit guidelines for everyday
datasets. Also, Few emphasizes business information, whereas Tufte emphasizes scientific datasets.
Turning Numbers into Knowledge: Mastering the Art of Problem Solving, Jonathan G. Koomey, Ph.D.,
Analytics Press, 2001.
Information Visualization: Perception for Design, Second Edition, Colin Ware, Morgan Kaufmann, 2004. This
book combines a strictly scientific approach to human perception with a practical concern for the rules governing
the effective visual presentation of information.
A Field Guide to Digital Color, Maureen Stone, A. K. Peters, 2003. Perhaps no aspect of information display is as
commonly misunderstood and misapplied as color. This book explains how color works, both physically and
perceptually, and applies this knowledge to multiple fields and technologies, including computer-based information
display.
Perceptual Edge Website. Visual Business Intelligence for enlightening analysis and communication,
Website dedicated to topics on visual presentations. There is a large library of whitepapers and other brief
publications on the subject.
http://www.perceptualedge.com/
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Dr. Rafael E. Matos
Senior Operations Research Analyst – WBB Inc.
President – Military Operations Research Society (MORS)