Short answer
Designers should consider incorporating elements into data visualizations that acknowledge uncertainty and complexity, prompting users to engage more deeply with the information and make more considered judgments.
- Field
- User-Centred Design
- Source
- Accounting and Business Research (2017)
- Method
- Rhetorical analysis of data visualizations
- Evidence
- Moderate effect
Designing data visualizations that acknowledge and even prompt ambiguity, rather than striving for absolute clarity, can lead to more nuanced and effective decision-making in complex management contexts. This user-centred design research insight is drawn from a 2017 study published in Accounting and Business Research. Using Rhetorical analysis of data visualizations, researchers explored how this design variable affects real-world outcomes. The key design takeaway: Designers should consider incorporating elements into data visualizations that acknowledge uncertainty and complexity, prompting users to engage more deeply with the information and make more considered judgments.
Data Visualizations Should Embrace Ambiguity to Enhance Decision-Making
Designing data visualizations that acknowledge and even prompt ambiguity, rather than striving for absolute clarity, can lead to more nuanced and effective decision-making in complex management contexts.
Accounting and Business Research · 2017
Key Findings
- 01Data visualizations in management controls should be conceived beyond their purely representational function.
- 02Embracing ambiguity, rather than suppressing it, in data visualization design can lead to wiser judgment.
- 03A visual rhetorical framework can inform the design of effective data visualizations like dashboards and reports.
Application
Design takeaway
Designers should consider incorporating elements into data visualizations that acknowledge uncertainty and complexity, prompting users to engage more deeply with the information and make more considered judgments.
How to apply
When designing dashboards or reports for complex projects, consider how to visually represent areas of uncertainty or multiple potential interpretations, rather than forcing a single, definitive view.
Project actions
- 01When presenting data, think about how the visual design itself communicates a message about certainty or uncertainty.
- 02Consider using visual cues that invite questions rather than just providing answers.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Applies theoretical concepts from rhetoric to practical design challenges.
- +Provides a framework for analyzing and designing data visualizations for complex environments.
Limitations
It can be challenging to balance showing ambiguity with providing enough clarity for users to act. Overdoing ambiguity might lead to confusion or inaction.
Reliability & validity
The study's reliance on rhetorical analysis and a single case study may limit generalizability. Validity could be enhanced through user studies to confirm the impact of design choices on judgment.
Think critically
To what extent can 'embracing ambiguity' lead to paralysis or misinterpretation if not carefully managed within the design?
Design Principles
"Design data visualizations to reflect the inherent ambiguity of complex decision-making environments, thereby fostering deeper user engagement and more robust judgment."
In many professional domains, decisions are made under conditions of uncertainty and complexity. Traditional design approaches often aim to simplify data, but this research suggests that embracing ambiguity in visualizations can better reflect reality and encourage deeper critical thinking from users.
What This Means for Your Design
Sometimes, making something look too simple can be misleading. For important decisions, it's better if a chart or graph shows that there's some uncertainty or different ways to look at the information, which helps people think more carefully.
How to use in your project
- 1.Reference this research when discussing how your design choices for data presentation influence user understanding and decision-making.
- 2.Use it to justify design decisions that might intentionally include elements of ambiguity to encourage critical thought.
Add to My Project
Quick Cite
Paragraph starter
The design of data visualizations for complex management contexts should move beyond a purely representational function to embrace ambiguity, as suggested by Quattrone (2017). By acknowledging and even prompting uncertainty, visualizations can foster more nuanced judgment and wiser decision-making, reflecting the realities of complex organizational environments.
Source
Accounting and Business Research
Embracing ambiguity in management controls and decision-making processes: On how to design data visualisations to prompt wise judgement
journal · 2017
View sourceQuestions About This Research
- What does the research say about data visualizations should embrace ambiguity to enhance decision-making?
- Designers should consider incorporating elements into data visualizations that acknowledge uncertainty and complexity, prompting users to engage more deeply with the information and make more considered judgments. Evidence: Accounting and Business Research (2017).
- Why does "Data Visualizations Should Embrace Ambiguity to Enhance Decision-Making" matter for design?
- In many professional domains, decisions are made under conditions of uncertainty and complexity. Traditional design approaches often aim to simplify data, but this research suggests that embracing ambiguity in visualizations can better reflect reality and encourage deeper critical thinking from users.
- How can designers apply this research?
- Designers should consider incorporating elements into data visualizations that acknowledge uncertainty and complexity, prompting users to engage more deeply with the information and make more considered judgments.
- What were the main findings?
- Data visualizations in management controls should be conceived beyond their purely representational function.. Embracing ambiguity, rather than suppressing it, in data visualization design can lead to wiser judgment.. A visual rhetorical framework can inform the design of effective data visualizations like dashboards and reports.
- What research method was used?
- Rhetorical analysis of data visualizations.
- How strong is the evidence?
- Evidence strength is rated Moderate effect, based on a 2017 journal from Accounting and Business Research.
- What should I do differently in my next project?
- When designing dashboards or reports for complex projects, consider how to visually represent areas of uncertainty or multiple potential interpretations, rather than forcing a single, definitive view.
- What are the limitations?
- The analysis is primarily theoretical and based on a single case study of a dashboard; further empirical testing with diverse user groups and contexts would be beneficial.