Horacio Herrera-Richmond, design manager, Anthony Nolan Visit the CharityComms website to view slides from past events, see what events we have coming up and to check out what else we do: www.charitycomms.org.uk

1. DATA

2. DATA

3. Design
Verb:!
!Decide upon the look and
functioning of (a building, garment, or other
object), typically by making a detailed drawing
of it.
A
DATAVISUALISATION
STORY

4. PROCESS

5. A Data visualisation STORY
Process
DATA STORY
A B

6. A Data visualisation STORY
Process
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A

7. A Data visualisation STORY
Process
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A

8. STORY

9. STORY

10. A Data visualisation STORY

11. A Data visualisation STORY

12. A Data visualisation STORY
Process
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A

13. A Data visualisation STORY
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

14. A Data visualisation STORY
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
CONSIDER THIS
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

15. A Data visualisation STORY
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
Choose
the best chart
for your story.
Seek out
interesting
patterns
and trends
in the data
Find a story
in the data
that will
resonate with
your audience
Experiment
with colour,
space and text until
the information
is beautiful...
DO THIS
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

16. A Data visualisation STORY
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
Choose
the best chart
for your story.
Seek out
interesting
patterns
and trends
in the data
Find a story
in the data
that will
resonate with
your audience
Experiment
with colour,
space and text until
the information
is beautiful...
Web Producer
Data Analyst
Journalist
Designer
Web Producer
Data Analyst
Journalist
Data Analyst
Designer
USE ONE OF THESE
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

17. A Data visualisation STORY
Choose
the best chart
for your story.
Seek out
interesting
patterns
and trends
in the data
Find a story
in the data
that will
resonate with
your audience
Experiment
with colour,
space and text until
the information
is beautiful...
Web Producer
Data Analyst
Journalist
Designer
Web Producer
Data Analyst
Journalist
Data Analyst
Designer
USE THESE TOOLS
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

18. A Data visualisation STORY
INTEGRITY FORMFUNCTIONMEANING
Web Producer
Data Analyst
Journalist
Designer
Web Producer
Data Analyst
Journalist
Data Analyst
Designer
TO PRODUCE
DATA STORY CHART DESIGN
What does
your audience
care about?
Which charts
will bring
your story
to life?
Does your chart
look good?
Is it a
credible and
comprehensive
dataset?
A B
A
Process

19. A Data visualisation STORY
Anyone seeing your
design will find its story
truthful, meaningful,
useful and beautiful.

20. TRUTH

21. A Data visualisation STORY
Evidence
The author of Beautiful Evidence believes
that if you notice the chart first
and not the data - then you’ve failed.
Theorist
He has spent most of his life in Universities,
in particular Yale and Princeton.
Present all data to
show top-level trends
Never cheat data
Design should be minimal
or invisible
First loyalty is to data
Information
His book Information is Beautiful
is an attempt to apply graphic design
principles to data journalism.
Practitioner
He writes blogs and produces infographics
for a range of publications,
including the Guardian and Wired.
Selective use of data to
guide reader to key story
Tweak visuals if it
makes the story clearer
Design should be used to
emphasise the story
First loyalty is to audience
LOVES
ROLE
DISPLAY
DESIGN
ACCURACY
1
2
3
TUFTE VS MCCANDLESS
That’s Not The Way I See It...
There are many different approaches to data visualisation - but two in particular have generated the most discussion.
Edward Tufte favours a traditional statistics-based approach, favouring clarity and accuracy.
David McCandless is more interested in teasing stories out of data and then making them as visually appealing as possible.
Evidence
The author of Beautiful Evidence believes
that if you notice the chart first
and not the data - then you’ve failed.
Theorist
He has spent most of his life in Universities,
in particular Yale and Princeton.
Present all data to
show top-level trends
Never cheat data
Design should be minimal
or invisible
First loyalty is to data
Information
His book Information is Beautiful
is an attempt to apply graphic design
principles to data journalism.
Practitioner
He writes blogs and produces infographics
for a range of publications,
including the Guardian and Wired.
Selective use of data to
guide reader to key story
Tweak visuals if it
makes the story clearer
Design should be used to
emphasise the story
First loyalty is to audience
Tufte McCandless
LOVES
ROLE
DISPLAY
DESIGN
ACCURACY
1
2
3
That’s Not The Way I See It...
There are many different approaches to data visualisation - but two in particular have generated the most discussion.
Edward Tufte favours a traditional statistics-based approach, favouring clarity and accuracy.
David McCandless is more interested in teasing stories out of data and then making them as visually appealing as possible.
Evidence
The author of Beautiful Evidence believes
that if you notice the chart first
and not the data - then you’ve failed.
Theorist
He has spent most of his life in Universities,
in particular Yale and Princeton.
Present all data to
show top-level trends
Never cheat data
Design should be minimal
or invisible
First loyalty is to data
Information
His book Information is Beautiful
is an attempt to apply graphic design
principles to data journalism.
Practitioner
He writes blogs and produces infographics
for a range of publications,
including the Guardian and Wired.
Selective use of data to
guide reader to key story
Tweak visuals if it
makes the story clearer
Design should be used to
emphasise the story
First loyalty is to audience
Tufte McCandless
LOVES
ROLE
DISPLAY
DESIGN
ACCURACY
1
2
3

22. CARTOGRAPHY

23. OR WHAT
TO LEAVE OUT

24. A Data visualisation STORY
Maps

25. A Data visualisation STORY

26. A Data visualisation STORY

27. A Data visualisation STORY

28. A Data visualisation STORY

29. A Data visualisation STORY
Geographical accuracy
Data lookup
Choosing the right approach

30. A Data visualisation STORY
Geographical accuracy
Data lookup
Pattern perception
Choosing the right approach

31. SOME OF
OUR WORK

32. A Data visualisation STORY
THE LIFESAVERS – ANTHONY NOLAN ANNuAL REpORT ANd AccOuNTS 2015 THE LIFESAVERS – ANTHONY NOLAN ANNuAL REpORT ANd AccOuNTS 20158 9
THE YEAR IN NUMBERS
italladdsup
toagreatyear
brand new RS-II machines in our
laboratories – the next step in our
groundbreaking Third Generation
Sequencing strategy.
355,800
research papers
published
by our staff.
41
£11.4mincome from fundraising, in the last year
– including the RGF grant and fundraising
income from our trading subsidiary.
In total, we raised over £11.4 million in this
financial year, compared to £8.3 million
for 2013/2014 – no mean feat in a static
UK charity fundraising market.
34
people received a
grant as part of our
new Patient Grants
Programme, which
offers financial
support to patients
with low income
and limited savings.
53,129potential donors recruited – more than any
year since 1986.
1,259patients given a chance of life.
42countries came to the
World marrow Donor
Association (WMDA)
biennial international
conference, which we
hosted – the event saw
over 300 delegates in
attendance, some from
as far afield as China
and Australia.
9,000people signed our
#SaveALifeat16 online
petition, prompting over
100 MPs to get behind
our proposal.
553,873potentiallifesavers
By the end of the financial year
we celebrated reaching 553,873
people on the register.
£1.47mraised from the Virgin London
marathon 2014, smashing our
£1.1M target. We also saw
of our incredible runners taking
to the streets of London, cheered
on by 800 volunteers.
new Anthony Nolan
nurses in post at the
Royal Marsden in
Sutton, and Newcastle,
with a third on the way
later this year.
500
potential donors recruited
by marrow (our affiliated
student groups) in the last
academic year.
Marrow groups now recruit
of those who go on to
donate from the Anthony
Nolan register.
12,000
44,830young people educated
about stem cell donation
through R&Be talks and
visits across the country.
28%
impressions on our social media channels
over the financial year, with 10,600
new Twitter followers, and 16,200 new
Facebook followers.

33. A Data visualisation STORY
,0 9 7 2
POTENTIAL LIFESAVERS ON THE REGISTER
IN YOUR COMMUNITY
AVERAGE
AGE
MALE
10%
RANKING
OUT OF 650
CONSTITUENCIES
504
Young, male donors are much
more likely to be selected by
transplant centres
27
Enter your postcode *
ChECk your STATS
How is your community doing in the search for lifesavers?
Every day, incredible individuals aged between 16-30 from
communities across the country join our stem cell donor
register.
How many potential lifesavers live near you? Enter your
postcode below to find out.
CoMMuNITIES
Versus
CANCer

34. A Data visualisation STORY
,0 9 7 2
POTENTIAL LIFESAVERS ON THE REGISTER
IN YOUR COMMUNITY
AVERAGE
AGE
MALE
10%
RANKING
OUT OF 650
CONSTITUENCIES
504
Young, male donors are much
more likely to be selected by
transplant centres
27

35. A Data visualisation STORY
PRICING
BREAKDOWN X%
X%
X%
AdmINIstRAtIve OveRheAds X%
Costs incurred to Anthony Nolan for facilitating
the import, including shipping administration,
donor selection, search and provision, clinical
liaison and facilitation, and patient support.
QuAlIty AssuRANCe X%
Associated fees to ensure that all imports and
exports are properly licensed and accredited
and meet the highest standards.
ReGIstRy CONtRIbutION X%
A contribution to cover the costs of growing
the UK registry, including donor recruitment
and collection of cord.

36. A Data visualisation STORY
£60
It costs
£60 to
recruit and
retain each
new person
on the
register.
WE NEED MORE
YOUNG MEN
Young men aged 16-30
are the most likely to
be chosen to donate –
over half of those who
donated in the last two
years were young men.
But they only make up
15% of the register.
£2.12M
In 2014-15 we spent
£2.12 million on
groundbreaking
research.
30-70%
Transplantation is a complicated procedure and the probability
of long-term survival can range between 30-70% depending
on a variety of factors.
Only 20% of black, Asian or minority ethnic
transplant recipients receive the best match.
The figure for Northern European transplant
recipients is 60%.
BAME
The average age of
our donors is 31.
The most common
age of donors is 23.
ANTHONY NOLAN IN NUMBERS
Every year, we update the organisation’s
key stats, to ensure our messaging and
communications are as accurate as possible.
This infographic showcases a few key stats
that you’re likely to use over the coming year.
EvERY 2O MINUTES
SomEonE IS dIagnoSEd wITh Blood cancEr.
3
1,200
We helped over 1,200 people
last year. But anthony nolan
can only find the best possible
match for around 60% of
transplant recipients.
Early indications from
anthony nolan’s recent
research are confirming
that the use of donors
under 30 is associated
with a trend towards
better survival rates.
31
23
15%
we give the chance
of life to three people
every day.
60%BEST
POSSIBLE
MATCH
20%

37. A Data visualisation STORY

38. A Data visualisation STORY

39. A Data visualisation STORY

40. THANK YOU

41. A Data visualisation STORY

42. Visit the CharityComms website to
view slides from past events, see
what events we have coming up
and to check out what else we do:
www.charitycomms.org.uk

43. 12 May 2016
London
#charitycreative
Creatives Group
Data visualisation