Tucana HR Analytics Data Visualisation, April 2014 (London)

© 2009 IBM Corporation

Can You See It?Visualising Your Data For Impact

Mark Tristam Lawrence @mtlawrenceLearning Intelligence Leader, Global Business Services #PADDHR

10 April, 2014

© 2014 IBM Corporation2

“Daddy, how much do you love me?”

A. “Infinity plus infinity”

B. “More than most”

C. “This much”

D. “Right now?”

E. “110%”

IBM Presentation Template Full Version#PADDHR

© 2014 IBM Corporation3

“Daddy, how much do you love me?”

A. “Infinity plus infinity” ? + ?

B. “More than most” ?

C. “This much”

D. “Right now?” ?

E. “110%” ???!!

IBM Presentation Template Full Version#PADDHR


#PADDHR

Video Source: Andrew Marritt. Reprinted with permission. Visit www.OrganizationView.com for more information.

23 Sec


#PADDHR

http://www.infovis.info/visuals/Gallery_of_Data_Visualization/Re-Visions_Minard/napon.gif

http://www.infovis.info/visuals/Gallery_of_Data_Visualization/Re-Visions_Minard/napon.gif


#PADDHR

http://www.senchalabs.org/philogl/PhiloGL/examples/worldFlights/

http://www.senchalabs.org/philogl/PhiloGL/examples/worldFlights/


#PADDHR

Global Human Capital Trends 2014: Engaging the 21st-century workforce

A report by Deloitte Consulting LLP and Bersin by Deloitte


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Outline

Death by ToolsetIt’s a competitive marketplace, and growing – choose wisely

The Value of VisualisationSome examples of good and bad visualisations

Psychology and ScienceHow, and why, does it work?

Four Pillars of VisualisationA framework for you to take away and put to use

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Why Now?#PADDHR


Growing Market Competitiveness

Magic Quadrant for Business Intelligence and Analytics Platforms, 2014

•New : split between “BI and Analytics Platforms” and “Advanced Analytics Platforms”

•Data Discovery as a response to data explosion

•Suggestion that traditional BI (OLAP and ad hoc querying) has reached a plateau

https://www.gartner.com/technology/reprints.do?id=1-1QLGACN&ct=140210&st=sb

#PADDHR



Growth in Choice#PADDHR


Differentiate to Discover Value

• Where does Visualisation fit within the spectrum of Business Intelligence?

• How relevant is the Cloud to Data Visualisation?

• How do you ensure that you are adding value?Engagement

Data

Cloud

#PADDHR


Data: Business Intelligence Spectrum

Architect

Data ScientistETL OLAP Business Analyst

Visualisation

Business-User

Data

#PADDHR


Cloud: Visualisation InfrastructureCloud

#PADDHR


#PADDHR

Get Interactive!

http://www.theguardian.com/world/interactive/2011/mar/22/middle-east-protest-interactive-timeline

Cloud

http://www.theguardian.com/world/interactive/2011/mar/22/middle-east-protest-interactive-timeline


Cla

ssro

omeL

earn

ing

Engagement: Aesthetic = EffectiveEngagement ?#PADDHR


What about Infographics?

Created by Mark Tristam Lawrence, IBMinfogr.am

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Engagement

http://infogr.am/


Visualisation Types

Need Option Need Option

See Relationships Between Data Points

Track Rises and Falls, Over Time

Compare Sets of Values

See the Parts of a Whole

‘Many Eyes’ visualisation options

(Courtesy of Noah Iliinsky, IBM)

Analyse Text

Think about what you want to achieve

#PADDHR


How Do We Make Decisions?

“Let the dataset change your mindset”

(Hans Rosling)

“Bias” is the conflict between intuition and logic

• ‘Attentional Blindness’

• ‘Confirmation Bias’

• ‘Risk Aversion’

#PADDHR


Make Your Decision#PADDHR


Pre-Attentive Processing

“It is easy to spot a hawk in a sky full of pigeons”(Colin Ware)

Sat

urat

ion

Col

our

Pos

ition

Siz

eS

hape

Enc

losu

reM

arki

ngs

Line

Wid

thO

rient

atio

n

#PADDHR

Diagram Source: TDWI, 2011. Reprinted with permission. Visit tdwi.org for more information.


An Experiment

Numberphile’s Sarah Wiseman explains: https://www.youtube.com/watch?v=kCSzjExvbTQ

55%!

#PADDHR

https://www.youtube.com/watch?v=kCSzjExvbTQ


Positioning…

ZMost Important

(Topic 1)

Supporting(Topic 1 or 3)

Secondary focus(Topic 2)

Least Important(Topic 2 or 4)

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…Layout

KPI

KPI

Supporting Detail

#PADDHR


Visual Formatting#PADDHR


35 Sec

#PADDHR


Less Is More…#PADDHR


Case Study:“The Data Storm – Retail And The Big Data Revolution”

#PADDHR


Case Study – “The Data Storm”

What works well?

What doesn’t work so well?

#PADDHR



What works well?


#PADDHR



What works well?


#PADDHR


Case Study – “The Data Storm”Conclusions

•Sharp, contrasting and ‘slick’ graphics•Appealing banner•Uncluttered and mostly fits to one screen•Clear signposting for downloading data•Text highlights helps to focus attention•Abilities to choose filters are clear•Available on internet browser, via multiple devices and ability to share via social media

•Poor prioritisation or positioning of charts•Use of inefficient visualisation types•Inefficient use of space•Inconsistent dimensions and design•Unverifiable textual highlights•Hidden navigational links•Missing confirmation of limits set•Missing confirmation, or explanation, of measures

What works well?


Even using a tool like Tableau (which suggests visualisation types based upon the type of data it finds), there is no guarantee that your visualisation will be perfect! You need to follow a structured model.

#PADDHR


The 4 Pillars of Visualization

Informed by Purpose, Content

and Structure

Noah Iliinsky, Centre for Advanced Visualization, IBM

#PADDHR


What’s Next for Data Visualisation?

• Harnessing the Opportunities afforded by the capture of Big Data?

• Geo-spatial Analysis and Interactive mapping?

• Interacting with Visualised Data constructs?

“data is the new soil”David McCandless, The Beauty of Data Visualisation, 2010 (TEDGlobal)

#PADDHR

http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization

http://simia.net/wikiglobe/


Visualisation ‘White Papers’

Choosing Visual Properties For Successful Visualizations

• Creating Effective Visualizations• Choosing the right visual propertiesLearn how to properly choose the visual property (position, shape, size, color and others) to encode the

different types of data that will be presented in a visualization. http://bit.ly/successfulvis

Choosing A Successful Structure For Your Visualization

• Know your purpose• Select how much data you need

The structure defines the landscape for presenting your data and consequently defines what sort of information will be most readily available from your visualization.

https://ibm.biz/structurevis

#PADDHR

http://bit.ly/successfulvis


http://bit.ly/successfulvis



References

Additional Research and Articles:Gartner: Magic Quadrant for Business Intelligence and Analytics Platforms


Gartner: Magic Quadrant for Advanced Analytics Platformshttp://www.gartner.com/technology/reprints.do?id=1-1QXWE6S&ct=140219&st=sb.

The Data Storm | An Economist Intelligence Unit Report Commissioned By Wipro

http://public.tableausoftware.com/views/The-data-storm_0/Home

Be Inspired:Play with the example visualisations in Google WebGL

http://www.chromeexperiments.com/globe

Imagine the possibilities with Dr Jo-Ann Kuchera Morin’s tour of the “Allosphere” (University of California)

http://www.ted.com/talks/joann_kuchera_morin_tours_the_allosphere

Eminent #dataviz:•Stephen Few (perceptualedge.com/)

–Show Me The Numbers (2nd ed., Analytics Press, 2012)

•Ed Tufte (edwardtufte.com/)–The Visual Display Of Quantitative Information (2nd ed., Graphics Press, 2012)

•Nathan Yau (flowingdata.com/)–Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics (John Wiley & Sons, 2011)

•Hans Rosling (gapminder.org/)

Some notable IBMers I’d recommend:•Noah Iliinsky (complexdiagrams.com/) @noahi

•Jonathan Sidhu @jmsidhu

•Graham Wills (workingvis.com/) @GrahamWills

•Steve McDougal @mcdouster

#PADDHR


http://www.gartner.com/technology/reprints.do?id=1-1QXWE6S&ct=140219&st=sb.


Can you see it, now?

Mark Tristam Lawrence +44 (0)7917 270138Learning Intelligence Leader, Global Business Services

@mtlawrence#PADDHR


Appendices


A note on the novelty value of Infographics

Do we think the audience were really assessing the content, or the visual impact?

#PADDHR

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