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Insights From Data Visualization - Stephen Lett (Procter & Gamble)
The document discusses the significance and principles of data visualization in business, emphasizing its role in simplifying complex data for improved decision-making and collaboration. Key factors for effective visualization include understanding the audience, conveying the right message, and adhering to design principles such as avoiding 'chartjunk' and using appropriate colors. The importance of clear communication through effective graphical displays is highlighted as essential for fostering productivity in a competitive market.
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Insights From Data Visualization - Stephen Lett (Procter & Gamble)
- 1. Insights from Data Visualization STEPHEN LETT 19 NOVEMBER 2014
- 2. Introduction Procterand Gamble Global Business Services, Global Service Manager 15 Years Career 3 Years – Planning and Manufacturing Business Intelligence Service Manager.
- 3. Data Visualization DiscussionPoints What is it? Brief overview of what data visualization is and why it is important. What to Know First? Questions to consider when deciding how to best leverage Data Visualization. Visualization Design Few golden tips to remember to make your visualization stand out.
- 4. Quick Survey Whenwas the first line chart and bar graph produced? 1639 1786 1801 1920 William Playfair, Scottish Engineer 1759-1823
- 5. Data Visualization Transformation Reporting Visualizing Business Intelligence
- 6. Data Visualization WHATIS IT?
- 7. What is DataVisualization? Simple Definition: Visual Representation of Information A means of communicating information clearly and effectively through graphical displays
- 8. Edward Tuft, 1983 At their best, graphics are instruments for reasoning about quantitative information. Often the most effective way to describe, explore, and summarize a set of numbers - even a very large set - is to look at pictures of those numbers. Well-designed data graphics are usually the simplest and at the same time the most powerful.
- 9. Why is DataVisualization Important in Business?
- 10. Why is DataVisualization Important in Business? VUCA World Data is the consistent tool that simplifies the VUCA into where we need to focus. Translates into COST SAVINGS Getting to the right answers faster is the only differentiator in competitive markets. Fosters PRODUCTIVITY and COLLABORATION Good graphical representations of data communicates complex ideas with clarity, precision, and efficiency. Getting teams on the same page faster, and individual contributors on a head start for where to focus.
- 11. Data Visualization WHATTO KNOW FIRST?
- 12. 3 Factors toConsider: 1.Who’s the “Who”? 2.What’s the “What!”? 3.How to Motivate towards ACTION?
- 13. Who’s the Who? Know Their Background: Experts in the Field/Subject? Analysts – using the data for projections / transformations? Management – strategic directions? Define Consumerization of Data Instructor Driven Self-Discovery Set the Right Expectations Basic Overview Category Glance Deep Discovery in 1 Vector
- 14. Communication vs Analysis Visualization for Communication Visualization for Analysis Audience General Public Senior Leaders Analysts Intent Summary & Conclusions Explain the Situation Explorations and Observations Data Consumption Immediate Understanding Required Complexity SIMPLE Situational Based Time to Generate Fairly Quick Real-Time**
- 15. What’s the Message? Background / General Knowledge? Summary to Support a Decision? Deep Analysis to Drive a New Activity? Communicating new insights?
- 16. Plan Accordingly! GoodRule of Thumb: Work on Audience and Message understanding and intent BEFORE building any visualizations!
- 17. Motivating Towards ACTION Based on the AUDIENCE and the MESSAGE Pick the visualization that will lean towards ACTION! - If you can communicate the message clearly and efficiently in a simple sentence, DO IT; - If Data Tables are required, use them – but don’t lean on visual perception alone. Manage the message!
- 18. Data Visualization VISUALIZATION DESIGN TIPS
- 19. Key Steps inDesigning your Visualization Data Preparation Clean Data is a MUST: - Eliminate “Noise” (e.g. nulls, missing values) - Clarify data (full set, representative sample, etc) Normalize and Transform Upfront - Aggregate - Filter - Primary / Secondary Keys Choose Your Graph • Amount of Data • Type of Data • Data Relationships • Conclusion for Audience Good Design Principles 1. Avoid “Chartjunk” 2. Use Colors Wisely 3. No Misleading Scales 4. Dual Axis Charts are for Experts
- 20. Good Design Principle1 – Chartjunk What is It? Visual Content that: Adds little / no value Serves little / no purpose Distracts from real data Examples Shadows / Color Effects
- 21. Good Design Principle#2 - Colors If the point is: Consistent performance at 40%+, which chart uses color most effectively ? • Use the same color, except when color differences make a difference • Use a single, neutral background color (if needed at all)
- 22. Good Design Principle#3 - Scaling How are we doing with our budget forecast vs actuals over last 6 months? Notice the “Y-Axis”? Always NOTE if an axis doesn’t start with 0
- 23. Good Design Principle#4 – Dual Axes
- 24. Summary Data Visualizationis: Communicating clearly and effectively through graphics. Know Your Plan 1. Who’s the Who? 2. What’s the “What!”? 3. Motivate to ACT! Golden Design Tips 1. Avoid Chartjunk 2. Use Colors Wisely 3. Beware of Scaling 4. Dual Axes Needed?
- 25. Foundational Principles If the message is simple, keep it simple. If the message is complex, make it look simple. Always tell the truth – don’t use graphs to distort the data.
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- 28. William Playfair Graphs William Playfair, Scottish Engineer 28 1759-1823
- 29. Q3. Is visualizationthe best way to share the data, show the findings, and/or reveal the insight? Does it provide insight or understanding that was not obtainable with the original representation (text, table, etc)? Tables Graphs Data are arranged in columns and rows Data are displayed in relation to one or more 29 axes along which run scales that assign meaning to the values work best when the display will be used to look up individual values or the quantitative values must be precise. work best when the message resides in the shape of the data (that is, in patterns, trends, and outliers).
Editor's Notes
- #5 William Playfair (1759-1823) developed or improved upon nearly all of the fundamental graphical designs, seeking to replace conventional tables of numbers with systematic visual representations. He invented the bar chart, line graph, and pie chart.
- #6 Reporting Visualization Business Intelligence Reporting: Facts and Figures – precise values Visualization: remove the rows/columns – more intuitive / perceptive Business Intelligence: Combining multiple performance measures to understand results and determine focus.
- #9 Edward Tufte is a leading authority on visual design. This course draws heavily on his ideas, and his followers such as Stephen Few. The Visual Display of Quantitative Information, Edward R. Tufte, Graphics Press: Cheshire, CT 1983, Introduction
- #15 ** Will require access to the data source.
- #24 Only useful for comparing data with different units of measure May be more effectively replaced by 2 charts
- #29 http://en.wikipedia.org/wiki/William_Playfair William Playfair (1759-1823) developed or improved upon nearly all of the fundamental graphical designs, seeking to replace conventional tables of numbers with systematic visual representations. He invented the bar chart, line graph, and pie chart.