LEXPIERIK

HR ANALYTICS DATA VISUALIZATION & ANALYSIS

DESIGN IS THINKING

MADE VISUAL

SAUL BASS

BY VISUALIZING INFORMATION, WE TURN IT INTO A LANDSCAPE THAT

YOU CAN EXPLORE WITH YOUR EYESDAVID MCCANDLESS

FORM FOLLOWSFUNCTION

LOUIS HENRY SULLIVAN

WHY WE ARE HERE

COLLEGE #9STORYTELLING

COLLEGE #7THEORY

COLLEGE #8DATA ANALYSIS

THE HISTORY OF DATA VISUALIZATION

1600-

1699

Measurementandtheory1600 16991626 1644 1686

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1600-

1699

Measurementandtheory1600 16991626 1644 1686

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1600-

1699

Measurementandtheory1600 16991626 1644 1686

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1700-

1799

Newgraphicforms1700 179917821701

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1700-

1799

Newgraphicforms1700 179917821701

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1700-

1799

Newgraphicforms1700 179917821701

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1800-

1849

Beginningsofmoderngraphics184918441800 1821 1833

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1800-

1849

Beginningsofmoderngraphics184918441800 1821 1833

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1800-

1849

Beginningsofmoderngraphics184918441800 1821 1833

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1800-

1849

Beginningsofmoderngraphics184918441800 1821 1833

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1850-

1899

TheGoldenAgeofstatisticalgraphics189918901850 1863 1882

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1850-

1899

TheGoldenAgeofstatisticalgraphics189918901850 1863 1882

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1850-

1899

TheGoldenAgeofstatisticalgraphics189918901850 1863 1882

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1900-

1949

Themoderndarkages194919331900 1911 1924

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1900-

1949

Themoderndarkages194919331900 1911 1924

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1900-

1949

Themoderndarkages194919331900 1911 1924

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1900-

1949

Themoderndarkages194919331900 1911 1924

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1950-

1999

Re-birthofdatavisualization19991950 1965 1982 1983

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1950-

1999

Re-birthofdatavisualization19991950 1965 1982 1983

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1950-

1999

Re-birthofdatavisualization19991950 1965 1982 1983

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

1950-

1999

Re-birthofdatavisualization19991950 1965 1982 1983

Source:ABriefHistory ofDataVisualization - MichaelFriendly (http://www.datavis.ca/papers/hbook.pdf)

THIS IS NOW

SOME VISUALIZATION THEORY

• 4-9items• size• decay/pushout

• shapes• colors• intensity• movement

wesee with our brain,not our eyes

our mindsees thingsthat arenot there

VISUAL PERCEPTION

VISUAL CODING THE DATA

1265493578987234687321357987246872465795432749

VISUAL CODING THE DATA

1265493578987234687321357987246872465795432749

VISUAL CODING THE DATA

VISUAL CODING THE DATA: COLOR

VISUAL CODING THE DATA: EXPLICIT ASSOCIATION

Train

Plane

Bus

Metro

Plane

Bus

VISUAL CODING THE DATA: IMPLICIT ASSOCIATION

HOTCOLD

HOTCOLD

✔

✔

✘

✘

☺

☺☹

☹

LENGTH WIDTH ORIENTATION

SIZE SHAPE ENCLOSURE

GROUPING INTENSITY HUE

RAPID PERCEPTION WITH PREATTENTIVE VISUAL ATTRIBUTES

ICONIC MEMORY

SHORT TERM MEMORY

GESTALT PRINCIPLE OF VISUAL PERCEPTION

“WESEEWITHOURBRAIN,NOTOUREYES”

• Proximity

• Closure

• Similarity

• Continuity

• Enclosure

• Connection

PROXIMITY

CLOSURE

SIMILARITY

CONTINUITY

ENCLOSURE

CONNECTION

CONCLUSION

VISION&OPINIONS

VISION&OPINIONS

“ABOVE ALL ELSE SHOW THE DATA”

EDWAR

DTU

FTE

EDWAR

DTU

FTE

“WE ARE OVERWHELMED BY INFORMATION,

NOT BECAUSE THERE IS TOO MUCH, BUT

BECAUSE WE DON'T KNOW HOW TO TAME IT”

STEPHE

NFEW

STEPHE

NFEW

“VISUALISATION IS NOT SOMETHING

THAT HAPPENS ON A PAGE OR ON A

SCREEN; IT HAPPENS IN THE

MIND”

ALBE

RTOCAIRO

ALBE

RTOCAIRO

“THE HUMAN VISUAL SYSTEM IS A PATTERN SEEKER

OF ENORMOUS POWER AND SUBTLETY.

HOWEVER, THE VISUAL SYSTEM HAS ITS OWN

RULES.”

COLINW

ARE

COLINW

ARE

VISION&OPINIONS

“I am more passionate in my criticism, however, perhapsbecause I frequently and directly encounter the ill effectsof McCandless’ influence.”

“ …eye-catching but difficult toread and often inaccurate.”

“I argued that without providingthis counterpoint, he was abdicating his responsibility as a teacher and a journalist.”VI

SION&OPINIONS

THEABSOLUTETRUTH

CHOOSE THE RIGHT VISUALIZATION

SIMPLE

MORECOMPLEX

EVEN MORECOMPLEX

COMPARISON COMPARISON(over time)

RELATION DISTRIBUTION COMPOSITION FLOW/PROCESS

CHART BASICS

?1x

CHART BASICS

CHART BASICS

SOMEVISUALIZATIONTOOLS

DESKTO

PTO

OLS

DESKTO

PTO

OLS

TABLEA

UDE

SKTO

P

QLIKSENSE

MSPO

WER

BI

TABLEA

UDE

SKTO

P

TABLEA

UDE

SKTO

P

QLIKSENSE

QLIKSENSE

MSPO

WER

BI

MSPO

WER

BI

TABLEA

UDE

SKTO

P

QLIKSENSE

MSPO

WER

BI

CASUSHRDATADRIVENSTORYTELLING

INTRODUCTION &WORKSHOPAPPROACH

INTRODUCTION & WORKSHOP APPROACH

FINDTHE STORY

DESIGNTHESTORY

TELLTHESTORY

CASUSHRDATADRIVENSTORYTELLING

SOURCES

COMBINE THE DATA ANALYSE THE DATA FILTER THE DATA

FIND THE NARRATIVE

TEST THE STORYTELL THE STORY

SKETCH THE IDEA

DESIGN THE STORYDATA DRIVEN

DESIGN DRIVEN

STORY DRIVEN

INTRODUCTION &WORKSHOPAPPROACH

INTRODUCTION &WORKSHOPAPPROACH

goo.gl/UyNnM2

THE DATASET

FACTS & FIGURES

SIMPLE

MORECOMPLEX

EVEN MORECOMPLEX

COMPARISON COMPARISON(over time)

RELATION DISTRIBUTION COMPOSITION FLOW/PROCESS

SOURCE: VISUELE READER ® DE BETEKENAAR

VISUAL ALPHABET

SOURCE: VISUELE READER ® DE BETEKENAAR

SYMBOLS AS LABELS

SOURCE: VISUELE READER ® DE BETEKENAAR

STORYLINE OR PROCESS

SOURCE: VISUELE READER ® DE BETEKENAAR

WHAT IS IT ABOUT

SOURCE: VISUELE READER ® DE BETEKENAAR

SIMPLE EFFECTS

DATA

GROWTH

SUCCESS

GROUP

HAPPINESS

HOME

DATAVISUALIZATION

TELLTHESTORY

WORDS TO ICONIZE

A GOOD STORY HAS A …

THEME

A GOOD STORY HAS A …

STRUCTURE

A GOOD STORY HAS A …

CONCLUSION

LENGTH WIDTH ORIENTATION

SIZE SHAPE ENCLOSURE

GROUPING INTENSITY HUE

RAPID PERCEPTION WITH PREATTENTIVE VISUAL ATTRIBUTES

3 STORYTELLING TIPS

1. KNOW YOUR AUDIENCE

2. IMPROMPTU SPEAKING

3. PRESENTING

YOUR STORY SHOULD HELP THEM MAKE DECISIONS + ANSWER THEIR NEEDS

DON’T READ OUT THE STORY….BUT REALLY TELL IT

WHEN PRESENTING BE CONFIDENT, SPONTANIOUS + IMPROVISE

LEXPIER

IK

DATA

VISU

ALIZA

TION

AND

DATA

DRIVE

NST

ORYT

ELLIN

G

THE

LOG

ICA

LST

EP

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SIG

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