Dashboard Design Principles (Excerpt #2 from Creating and Automating Dashboards eStudy)

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As evaluators, we frequently face the challenge of accurately and efficiently producing large numbers of near-identical reports and dashboards.

In January 2013, Ann K. Emery and Agata Jose-Ivanina led a 3-hour webinar for the American Evaluation Association about automating dashboards with Word and Excel.

This excerpt summarizes questions to consider when designing a dashboard.

Published in: Technology, Business

Dashboard Design Principles (Excerpt #2 from Creating and Automating Dashboards eStudy)

  1. 1. Creating and Automating Dashboards Using MS Word and Excel by Ann K. Emery & Agata Jose-Ivanina eStudy for the American Evaluation Association January 2013 Excerpt 2: Dashboard Design Principles
  2. 2. Who Why When What Where How Dashboard Design: Questions to Consider
  3. 3. Who Why When What Where How Dashboard Design: Questions to Consider
  4. 4. Who Questions to Consider Who will be using this information? What types of decisions do they make? What information do they need? What information do they already have? What information are they expecting? How will my dashboard add value for them?
  5. 5. Who Questions to Consider How much time do they have? How much prior experience do they have? Do they enjoy or fear data? Are they familiar with metrics and terminology?
  6. 6. Who Two levels of information Dashboards Strategic Operational More info: “6 Golden Rules to Successful Dashboard Design” by Geckoboard, http://www.geckoboard.com/building-great-dashboards-6-golden-rules-to-successful-dashboard-design/
  7. 7. Example Designing dashboards for nonprofit leaders Board, Executive Director Senior Managers Program Managers Frontline Staff
  8. 8. Example Designing dashboards for nonprofit leaders Strategic Operational
  9. 9. Who Why When What Where How Dashboard Design: Questions to Consider
  10. 10. Why Questions to Consider Why are you designing a dashboard? What’s the core purpose of this dashboard?
  11. 11. Lesson Learned Don’t drown in data
  12. 12. Cool Trick Select top 3 reasons for creating a dashboard  Help management define what is important  Educate people in the organization about the things that matter  Set goals and expectations for specific individuals or groups  Help executives sleep at night because they know what’s going on  Encourage specific actions in a timely manner  Highlight exceptions and provide alerts when problems occur  Communicate progress and success Source: “A Guide to Creating Dashboards People Love to Use” by Juice Analytics, http://www.juiceanalytics.com/wp-content/uploads/2010/11/Guide_to_Dashboard_Design.pdf
  13. 13. Hot Tip Connect to existing logic models More info: Logic Model Workbook by Innovation Network , http://www.innonet.org/client_docs/File/logic_model_workbook.pdf
  14. 14. Cool Trick Push to the appendix More info: Juice Analytics, “A Guide to Creating Dashboards People Love to Use” http://www.juiceanalytics.com/wp-content/uploads/2010/11/Guide_to_Dashboard_Design.pdf
  15. 15. Who Why When What Where How Dashboard Design: Questions to Consider
  16. 16. When Questions to Consider How often is information needed? How often does data need to be refreshed? When will you collect data? How much turnaround time is available?
  17. 17. Cool Trick Create different dashboards Strategic Operational
  18. 18. Who Why When What Where How Dashboard Design: Questions to Consider
  19. 19. What Questions to Consider What’s the main content that will be included? What are the other deliverables? What kinds of comparisons can be made? What types of visualizations will you include?
  20. 20. Hot Tip Comparisons are key More info: Stephen Few in “Rich Data, Poor Data: Designing Dashboards to Inform,” http://www.perceptualedge.com/articles/Whitepapers/Rich_Data_Poor_Data.pdf
  21. 21. Cool Trick Aim for 1-2 comparisons Section vs. Overall Section vs. Section Community Scores Section Section Section 1 2 3 Section 4 Section Section Section 5 6 7 Overall Scores Community 1 75% 69% 77% 72% 70% 52% 70% Community 2 75% 77% 75% 71% 59% 67% 58% 68% Community 3 Community vs. Community 84% 91% 82% 85% 80% 76% 83% 72% 80% Community 4 62% 61% 57% 59% 49% 51% 49% 55% Community 5 74% 67% 55% 71% 69% 62% 54% 64% Community 6 72% 72% 69% 72% 62% 70% 70% 69% Community 7 46% 28% 30% 34% 19% 26% 22% 29% Community 8 84% 79% 85% 78% 64% 83% 79% 79% Community 9 50% 50% 54% 41% 15% 41% 36% 40% Community 10 93% 79% 77% 76% 66% 77% 75% 77% Community 11 66% 68% 67% 72% 63% 59% 66% 66% Community 12 88% 73% 88% 86% 74% 81% 77% 81%
  22. 22. Community Scores Section Section Section Section Section Section Section Overall 1 2 3 4 5 6 7 Scores Community 1 84% 75% 69% 77% 72% 70% 52% 70% Community 2 75% 77% 75% 71% 59% 67% 58% 68% Community 3 91% 82% 85% 80% 76% 83% 72% 80% Community 4 62% 61% 57% 59% 49% 51% 49% 55% Community 5 74% 67% 55% 71% 69% 62% 54% 64% Community 6 72% 72% 69% 72% 62% 70% 70% 69% Community 7 46% 28% 30% 34% 19% 26% 22% 29% Community 8 84% 79% 85% 78% 64% 83% 79% 79% Community 9 50% 50% 54% 41% 15% 41% 36% 40% Community 10 93% 79% 77% 76% 66% 77% 75% 77% Community 11 66% 68% 67% 72% 63% 59% 66% 66% Community 12 88% 73% 88% 86% 74% 81% 77% 81% Too. Many. Comparisons. 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Section 1 Section 2 Section 3 Section 4 Section 5 Section 6 Section 7 Overall
  23. 23. Community Scores Section Section Section Section Section Section Section Overall 1 2 3 4 5 6 7 Scores Community 1 84% 75% 69% 77% 72% 70% 52% 70% Community 2 75% 77% 75% 71% 59% 67% 58% 68% Community 3 91% 82% 85% 80% 76% 83% 72% 80% Community 4 62% 61% 57% 59% 49% 51% 49% 55% Community 5 74% 67% 55% 71% 69% 62% 54% 64% Community 6 72% 72% 69% 72% 62% 70% 70% 69% Community 7 46% 28% 30% 34% 19% 26% 22% 29% Community 8 84% 79% 85% 78% 64% 83% 79% 79% Community 9 50% 50% 54% 41% 15% 41% 36% 40% Community 10 93% 79% 77% 76% 66% 77% 75% 77% Community 11 66% 68% 67% 72% 63% 59% 66% 66% Community 12 88% 73% 88% 86% 74% 81% 77% 81% Section vs. Section, Section vs. Overall
  24. 24. Community Scores Section Section Section Section Section Section Section Overall 1 2 3 4 5 6 7 Scores Community 1 84% 75% 69% 77% 72% 70% 52% 70% Community 2 75% 77% 75% 71% 59% 67% 58% 68% Community 3 91% 82% 85% 80% 76% 83% 72% 80% Community 4 62% 61% 57% 59% 49% 51% 49% 55% Community 5 74% 67% 55% 71% 69% 62% 54% 64% Community 6 72% 72% 69% 72% 62% 70% 70% 69% Community 7 46% 28% 30% 34% 19% 26% 22% 29% Community 8 84% 79% 85% 78% 64% 83% 79% 79% Community 9 50% 50% 54% 41% 15% 41% 36% 40% Community 10 93% 79% 77% 76% 66% 77% 75% 77% Community 11 66% 68% 67% 72% 63% 59% 66% 66% Community 12 88% 73% 88% 86% 74% 81% 77% 81% Community vs. Community
  25. 25. Community Scores Section Section Section Section Section Section Section Overall 1 2 3 4 5 6 7 Scores Community 1 84% 75% 69% 77% 72% 70% 52% 70% Community 2 75% 77% 75% 71% 59% 67% 58% 68% Community 3 91% 82% 85% 80% 76% 83% 72% 80% Community 4 62% 61% 57% 59% 49% 51% 49% 55% Community 5 74% 67% 55% 71% 69% 62% 54% 64% Community 6 72% 72% 69% 72% 62% 70% 70% 69% Community 7 46% 28% 30% 34% 19% 26% 22% 29% Community 8 84% 79% 85% 78% 64% 83% 79% 79% Community 9 50% 50% 54% 41% 15% 41% 36% 40% Community 10 93% 79% 77% 76% 66% 77% 75% 77% Community 11 66% 68% 67% 72% 63% 59% 66% 66% Community 12 88% 73% 88% 86% 74% 81% 77% 81% Year 1 vs. Year 2
  26. 26. Hot Tip Choose the right chart
  27. 27. Rad Resource Chart Chooser juiceanalytics.com/chartchooser
  28. 28. Rad Resource Chandoo.org’s “How to Select the Right Chart for Your Data” http://chandoo.org/wp/2010/04/19/chart-selection-process/
  29. 29. Rad Resource Andrew Abela’s “Chart Suggestions” diagram extremepresentation.typepad.com/blog/2006/09/choosing_a_good.html
  30. 30. Who Why When What Where How Dashboard Design: Questions to Consider
  31. 31. Where Questions to Consider How will you group the data? Where will you put the most important data? How much white space will you leave?
  32. 32. Hot Tip Grouping Structure intentionally Relationships Flow For more information: “A Guide to Dashboard Design” by Juice Analytics http://www.juiceanalytics.com/wp-content/uploads/2010/11/Guide_to_Dashboard_Design.pdf
  33. 33. Example Grouping
  34. 34. Hot Tip We read from left to right, top to bottom
  35. 35. Cool Trick Take advantage of valuable real estate
  36. 36. Example Take advantage of valuable real estate
  37. 37. Cool Trick White space is okay
  38. 38. Cool Trick Sketch on paper Source: “Dashboard sketch” by Kerem Suer, http://cl.ly/5vuY
  39. 39. Cool Trick 3 Sections Sketch within grids 4 Sections 6 Sections
  40. 40. Who Why When What Where How Dashboard Design: Questions to Consider
  41. 41. How Questions to Consider How will you share the dashboards? Will the evaluator be present? How much interpretation vs. presenting findings as-is?
  42. 42. Cool Trick Participatory data analysis More info: “Participatory Analysis: Expanding Stakeholder Involvement in Evaluation” by Innovation Network, www.innonet.org/client_docs/innovation_network-participatory_analysis.pdf
  43. 43. Additional Design Principles
  44. 44. Cool Trick Maximize data-ink ratio Source: Data-Ink Ratio, Infovis Wiki, http://www.infovis-wiki.net/index.php/Data-Ink_Ratio
  45. 45. Cool Trick Maximize data-ink ratio Source: Data-Ink Ratio, Infovis Wiki, http://www.infovis-wiki.net/index.php/Data-Ink_Ratio
  46. 46. Rad Resource Edward Tufte’s books www.edwardtufte.com
  47. 47. Hot Tip Use color to emphasize differences, not to decorate Source: “Assigning a Color System for Graphs” by Stephanie Evergreen, stephanieevergreen.com/assigning-a-color-system-for-graphs/
  48. 48. Cool Trick Use a color palette More color palettes: Design Seeds, design-seeds.com
  49. 49. Hot Tip Tweak default settings
  50. 50. Cool Trick Use Excel elbow grease Coalition Members Barton 70% 47% Brown 68% 56% Crawford / Pittsburg 80% Dickinson 55% 32% 20% Douglas / Lawrence 64% 48% Finney / Garden City 69% 29% Johnson 65% 38% Mitchell / Beloit 79% 40% Riley / Manhattan Sedgwick / Wichita 77% 66% 81% TA Providers Shawnee Thomas / Colby 52% 35% 48% 41% 72%
  51. 51. Rad Resource Light Your Ignite training More info: “Light Your Ignite” training by Stephanie Evergreen/AEA’s Potent Presentations Initiative, http://comm.eval.org/eval/resources/ViewDocument/?DocumentKey=befc82a3-6787-44bd-bfd3-812addb7825e
  52. 52. Rad Resource Potent Presentations Initiative More info: p2i.eval.org
  53. 53. Characteristics of Great Dashboards: Dashboard Hall of Fame
  54. 54. “To do its job, a dashboard must not only present the right measures of what’s going on, it must also: • put those measures into context by including meaningful comparisons, • display them with timely, correct and reliable data, • express them in a manner that directly assesses performance, and • display them in a way that communicates clearly, accurately, and rapidly within the confines of a single screen.” Stephen Few Rich Data, Poor Data: Designing Dashboards to Inform http://www.perceptualedge.com/articles/Whitepapers/Rich_Data_Poor_Data.pdf
  55. 55. Rad Resource Assessing the Effectiveness of a New Dashboard’s Design by Stephen Few, http://www.perceptualedge.com/blog/?p=672
  56. 56. Dashboard Rad of Fame Hall Resource Perceptual Edge dashboard design competition More info: Winners from the recent Perceptual Edge dashboard design competition, http://www.perceptualedge.com/blog/?p=1374
  57. 57. Dashboard Rad of Fame Hall Resource Stephanie Evergreen’s 2012 Personal Annual Report More info: Stephanie Evergreen’s 2012 Personal Annual Report, stephanieevergreen.com/2012personalannualreport
  58. 58. Dataviz Rad of Fame Hall Resource Makeover Contest on Effective Graphs More info: Winners from the recent Makeover Contest on Effective Graphs, http://www.forbes.com/sites/naomirobbins/2012/12/21/visualizing-the-table-of-the-graph-makeover-contest-2/
  59. 59. Dataviz Rad of Fame Hall Resource Storytelling with Data data visualization challenge More info: Winners from the recent Storytelling with Data dataviz challenge http://www.storytellingwithdata.com/2012/12/and-winner-is.html
  60. 60. Dataviz Rad of Fame Hall Resource Visualizations We Like By Juice Labs More info: Juice Labs’ Visualizations We Like,. http://labs.juiceanalytics.com/vizwelike
  61. 61. Dataviz Hall of Fame Hans Rosling’s 200 Countries Video More info: Hans Rosling’s video, www.youtube.com/watch?v=jbkSRLYSojo
  62. 62. Thank you! Ann K. Emery @annkemery Agata Jose-Ivanina @agataji

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