Picture Superiority Effect

"A picture is worth a thousand words."

Picture Superiority Effect

1. An image is much easier remembered than words..

2. An image can explain an idea much better than words.

3. An image is easier to understand than words.

4. An image will convince more easily than words.

5. An image can hold more information in the same space than words.

6. An image will encode and decode information much quicker than words.

information density and attention

Communication

1. focus

   • relevance

     • right data

     • meaningful visualisation

   • central message

     • problem statement

       • insight

         • impact

           • recommendation

             • action

2. structure

   • understanding

     • story telling

     • McCandless technique

   • visualisation

   • sequence

   • logic

   • presentation outline

     • introduction

       • problem statement

       • context

       • objective

     • main part

       • data

       • analysis

       • findings

     • conclusion

       • insight

       • recommendation

         • action

3. form

   • audience

   • purpose

   • medium

     • oral

     • written

   • language

     • technical

     • non-technical

   • scope

     • short (i.e. five minutes, five pages)

     • long

McCandless Technique

1. introduce your visualisation by name

2. anticipate obvious questions from the audience

3. state the insight you are showing as central message

4. provide supporting evidence for the insight

5. explain why it matters

Audience

Business Stakeholders

• communication tasks

  • focus on result

    • final report

      • Know your audience!

        • hierarchy

          • What are the roles of my audience?

            • Who is the core decision maker in my audience?

          • Does my audience know me?

        • knowledge

          • What does my audience already know?

            • technical vs. non-technical background knowledge

              • terminology

              • procedures

                • best practice

          • What will keep my audience engaged?

            • What will be my audience's perspective?

              • What problem does my audience want to solve?

              • What does my audience need to learn?

          • Do I know enough myself?

            • Can I teach?

              • Can I break down to basics?

• communication forms

  • content

    • balance between concise and explanatory enough

      • concise

        • sort sentences

        • keep topics shorts (three or four short sentences per statement is enough)

        • stick to the main points

          • details

            • don't get lost in details

            • avoid technical details

            • keep details in footnotes in a written appendix

      • calm

        • don't use buzzwords

        • don't exaggerate

        • expect questions

          • anticipate questions

      • clear

        • speak clearly

        • clear sentences 

        • simple designs

        • easy examples

        • logical order

          • topics

          • sentences

        • technical aspects

          • don't use technical jargon

        • give time for questions at the end

  • audience relation

    • connect to audience and feedback

      • verbal

        • e.g. meetings

        • e.g. phone calls

      • non verbal

        • e.g. facial expression

        • e.g. gesture

    • foresee audience and expectation

      • visual

        • e.g. charts

        • e.g. images

      • written

        • e.g. email

        • e.g. reports

  • interaction

• interactive tools give power to the user

  • users with power interact

    • interactive users are attentive and engaged

Data Specialists

• communication tasks

  • focus on analysis technique

    • technical report

      • explain

        • reproduction

          • methodology

          • process

            • step-by-step

            • data

              • ETL

              • cleaning

        • possible follow-up analysis

Data Story

Story

• connecte sequence of events

  • told by

    1. word

    2. image

    3. performance

Important is the connection with your audience!

Components

1. data

   • data foundation

     • credibility

     • reliability

     • setting

   • exploratory focus

     • analysis

       • trends

         • KPI

       • patterns

2. visualisation

   • visual anchor

     • show, not tell

       • easy to remember

     • accessible for the audience

       • easy to understand

3. narrative

   • linear sequence

     • logical structure

     • start ↦ main ↦ end

   • dramatic element

     • surprises

   • main point

     • relevance

Advantages

Data story telling makes the insight into data:

1. better to follow

2. easier to understand

3. more convincing

4. harder to forget

5. to inspire action

Emotional Connection

fact ⇄ intellect ⇄ narrative ⇄ emotion ⇄ feeling 

Narrative

• make your story relevant

  • bigger picture

  • larger effort

  • context

  • business objective

• make your story relatable

  • context

  • simple charts

    • at short explanatory texts to the charts

  • familiar designs

    • use colours

    • use simple design elements

• create action with your story

  • business objective

  • next steps

Elements

• characters ⇢ stakeholders

• problem ⇢ business problem

• setting ⇢ relevant background

• plot ⇢ insight

• resolution ⇢ solution and recommendation

Narrative Plot Ideas

• hazard

  • evil villain

  • magic spell

  • ugly monster

  • difficult riddle

  • unrelenting fate

  • perilous journey

  • fortunate solution

  • divine intervention

  • life-threatening danger

  • discovering the unknown

• virtue

  • brave hero

  • fair maiden

  • innocent child

  • lucky outcome

  • joyous sidekick

  • affectionate love

  • growing friendship

  • surprising revelation

Narrative Arch

Freytag's Pyramid

1. exposition

   • context

     • justify the importance for audience

     • show relevance for audience

   • main characters

   • conflict introduction

     • problem statement

       • problem itself

         • precise

         • concise

         • relevance for audience

       • foreshadowing solution method

       • scope of problem

     • engage emotionally

2. rising action

   • leaving

     • events

       • tension

         • memorable keywords

         • epistemology

           • frequent: specific observation of evidence ⇨ induction ⇨ general theory for prediction

           • sometimes: outcome prediction from general theory ⇨ deduction ⇨ experimental test as a specific observation of evidence

       • suspense

3. climax

   • release tension

   • suspense relief 

4. falling action

   • return

   • build solution

     • foreshadowing resolution

5. resolution

   • conflicts solution

     • solution of problem statement

       • main points

         • clear

         • takeaway message

       •  path forward

         • enact change

           • call for action

             • immediate response

             • compel emotionally

             • order

           • first step

             • Kaizen

               • gradual constant small improvement

               • improve standard operation

               • reduce waste and redundancy

     • show empathy with audience

       • admit difficulty

       • hint stress relief

Team Roles

1. subject expert

   • knows the business problem, not the analytical techniques

   • sets the context

2. analyst

   • knows analytical techniques, not the business problem

   • discovers insights

3. visualiser

   • understands the context

   • understands the insight

4. reviewer

   • evaluates

   • gives feedback

Graphical Excellence

1. make large data sets coherent

2. show the data

3. many numbers in a small place

4. data before design

   • avoid visual distractions

   • use only design element when they help to present the data more clearly

5. avoid distortions

6. offer different levels of aggregation, from overview to detail

7. offer easy access to comparisons

8. serve one clear purpose:

   • description

   • exploration

   • tabulation

   • decoration

Data and Non-Data

example:  Data vs Non-Data

• a visualisation is composed of data and non-data

  • data

    • holds information

    • is essential

      • that is what you focus on

      • when deleted, information is lost

    • is redundant

      • redundant data is like non-data

      • does not hold crucial informations

      • can be deleted without loss of information

  • non-data

    • does not hold crucial informations

    • can be deleted without loss of information

    • furthermore, redundant data is non-data

Data Ratio

measure the data and non data by the visual space it takes up in a report

data ratio = data / visualisation = data / (data + non-data)

visualisation = data + non-data = 1

<=> data = 1 - non-data

<=> non-data = 1 - data 

=> visualisation = 1 + 0 = 1

create a high data ratio:

• avoid non-data

• avoid redundant data

Data Density

data density = visualisation / page = visualisation / (visualisation + empty space)

page = visualisation + empty space = 100%

<=> visualisation = 1 - empty space

<=> empty space = 1 - visualisation

=> page = 60% + 40% = 100%

The ratio from data to empty space should be around 3:2 i.e. a data density of around 60%, and the empty space makes up 40%.

Plotting

• cartesian plot

  • categorical plot: distribution of one quantitative variable within categories of one categorial variable

    • metric over category

      • column /bar chart

        • capture relationships between categories

      • count plot

      • box plot

        • visualise distributions

      • point plot

      • dot plot

  • relational plot: relationship between two quantitative variable

    • connected observation, often in time

      • metric over time

        • line chart

          • capture a trend

    • unconnected observation

      • metric on metric

        • scatter plot

          • metric on metric

            • capture relationships between variables

• polar plot: only useful for circular aspects (like time, or compass direction)

  • pie plot

  • rose plot

Third Variable

a 2D plot can show a third variable with

• colour

• shape

• subgroup charts side by side

Histogram

visualise distributions

used for continuous quantitative values

shows the shape a of a variable's distribution in bins

modality: the number of peaks in the distribution is called unimodal, bimodal, and trimodal, etc.

skewness: symmetric vs. pushed to the right (i.e. left-skewed) or left (i.e. right-skewed)

kurtosis: curvature of the distribution

Other

Pareto chart

Dark Statistics

dark statistics

Ressources

• https://en.wikipedia.org/wiki/Misuse_of_statistics

• https://en.wikipedia.org/wiki/Spurious_relationship

• The Visual Display of Quantitative Information Paperback by Edward R. Tufte

• How to Lie with Statistics by Darrell Huff