Iain Curtain, Ranzal Hyperion Consultant conducted this presentation at OAUG's recent Connection Point conference in Seattle, July 20-21.

1. Iain Curtain
Edgewater Ranzal
WHY DATA VISUALIZATION IS IMPORTANT
IN DELIVERING ACTIONABLE INSIGHT

2. Agenda
• Introduction
• Design examples
• Understanding the customer
• What makes good design
• How to apply this to reporting
• Summary and examples
• Questions

3. About

4. Customer Sample

5. Design Examples
- Lots of images
- Attention not drawn
to specific items
- Too much color
- Visuals used when
charts or data could
convey messages
better
- Waste of valuable
screen real estate

6. Design Examples
- 3-D rendering
makes it harder to
interpret the values
- Forecasted Units
and Dollars lines
connect the regions,
when they are
distinct data points
- Dollars and Year
Ago Dollars are
stacked, when they
are also distinct
values
- Excessive use of
the word ‘Region’

7. Design Examples
- Recent example of
visuals over
substance and
meaning
- Very difficult to
determine
correlation between
circle sizes

8. Design Examples
- Dark images and
background distract
the viewer
- Cannot determine
trends with only 2
data points
- Confusing as 2010
values are not
circles
- Visuals used when
charts or data could
convey messages
better

9. Customer Maturity
Customers are on a
reporting journey and
determining what their
requirements and
future plans are
Scorecards important in
understanding where
they are, what their
Dashboards needs are and where
they think they are
going.
Mgmt Reports You must satisfy the
pre-requisites before
climbing up the
Operations pyramid.
Foundation

10. Customer Maturity
Areas to grow
Consider 3 different
part of the organization
at different stages of
maturity:
- Finance = Area 1
- Logistics = Area 2
- Manufacturing =
Area 3
Maintain current
operations
business
Area 1 Area 2 Area 3

11. User Requirements
• Talk to users
• Listen to users
• Ask why, why, why?

12. Good design concepts
• Memory limits
• Encoding data for rapid perception
• Gestalt principles of perception

13. Memory Limits
• Iconic memory – visual cues, pre-conscious
/pre-attentive processing
• Short term memory – conscious
processing, 3-9 chunks only
• Long term memory

14. Data Encoding
- How many 3’s can
you find?
- As there is no
1723957695026398027384956012 encoding of data,
we process
9847536970898726547867925019 sequentially –
attentive processing
2005928976548102985079827158 - very slow!
0297456478597069873940588698
5726327189506972915069871256
2783789

15. Data Encoding
- 7 is the correct
answer
- Much easier to see
when data is in a
1723957695026398027384956012 different color, the
same goes for
9847536970898726547867925019 bolding, size, shape
and orientation
2005928976548102985079827158 changes as well
0297456478597069873940588698
5726327189506972915069871256
2783789

16. Gestalt Principles
Here we see:
• Proximity
- 2 groups rather than
7 blogs
- 2 different sets
within the groups
- 2 further groups
• Similarity within the groups
• Enclosure

17. Gestalt Principles
Our minds:
• Closure - Close
- Continue
- Link
even though these can
• Continuity be seen as discrete
items.
• Connection

18. Applying concepts
• Focus on the value add you are showing by organising
and minimising the data shown.
• Arrange information in a way that makes sense, making
sure that the important data stands out.

19. Edward R Tufte
• Tufte provided lots of thought around how we view and
perceive data

20. Data Ink Ratio
• Key concepts: reduce non data ink from graphics, focus
on the values
• Reduce graphic paraphernalia (chartjunk)

21. Chartjunk
• Which of these has clutter
and unnecessary items?
• Which is easier to see the
data?

22. Colin Ware
Colin Ware
Information Visualization -
Perception for Design, 2000
“We can easily see patterns
presented in certain ways, but if they
are presented in other ways they
become invisible.”

23. Colin Ware
We distinguish the
items if different in
terms of:
• Color - Color – either hue or
intensity
- Form – can also be
size, shape,
orientation
• Form

24. Colin Ware
We distinguish the
items if different in
terms of:
• Position - Position
- Motion:
flashing/moving
should only be used
for real time data or
issues requiring
immediate attention
• Motion

25. Stephen Few
• Combined previous theories and melded with current
designs and dashboard and communication ideas

26. Stephen Few
This simple example
shows how we can’t
easily compute size
variations in area.
The large circle is 16
time larger.
Pie and area charts
should not be used as
we cannot quickly
recognize the
differences.

27. How does this help us?
• Simplify – reduce the data presented
• Simplify – concentrate on important
information
• Simplify – remove unnecessary color and
distractions

28. Examples
Top example is very
difficult to read and
interpret numbers.
Bottom report is
cleaner and can easily
see the items without
distracting border and
shading.

29. Examples
Top example is very
distracting and difficult
to focus on areas that
need attention.
Bottom report is much
cleaner and easier to
see items needing
attention.

30. Design Examples
Much easier to
compare the different
market capitalizations
when presented as a
bar chart.
Also much easier to
see the best/worse if
ordered.

31. Design Examples

32. Design Examples
1,600 1,500.0
1,400
1,200
1,000
UK
800
Germany In charting the previous
600
North America graphic, it’s obvious
400
165.8 that there is no
US$ Millions
200 128.573.5
20.4 25.2 4.3 45.0 2.9 relationship between
0
2005 2009 2010 the years or countries.
Maybe a table would
1,600 1,500.0 have been better?
1,400
1,200
1,000
2005
800
2009
600
400 2010
128.5 165.8
73.5
US$ Millions
200 4.3 45.0 20.4 25.2 2.9
0
UK Germany North America

33. Edward R Tufte
The Visual Display of
Quantitative Information, 1983
“Graphical excellence is that which
gives the viewer the greatest
number of ideas in the shortest time,
with the least ink in the smallest
space.”

34. Iain Curtain
Consultant
iain.curtain@ranzal.com
http://thinsliced.wordpress.com/
202 683 0874
www.ranzal.com