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Adaptable Information Workshop slides

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Slides for my full-day information architecture workshop. Will teach in Minneapolis, MN (November 12, 2012) and Toronto, ON (November 29, 2012) Details: http://rosenfeldmedia.com/workshops/

Slides for my full-day information architecture workshop. Will teach in Minneapolis, MN (November 12, 2012) and Toronto, ON (November 29, 2012) Details: http://rosenfeldmedia.com/workshops/

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  • Need to make strong point of context of large orgs\n
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  • Explain what I mean by redesign\n
  • MICHIGAN STORY SHOULD BE SHORTER\nALSO, TRY TO COME UP WITH A NON-ACADEMIC SITE AS SHORTER EXAMPLES (MICHIGAN AS DEEP DIVE)\n
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  • http://en.wikipedia.org/wiki/File:Voltaire.jpg\n
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  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
  • Amazing drawing by Eva-Lotta Lamm: www.evalotta.net\n
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  • More great illustrations by Eva-Lotta Lamm\n
  • Onion courtesy Eva-Lotta Lamm\n
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  • http://recentissuetoday.com/wp-content/uploads/2010/06/pink_sprinkled_donut.jpg\n
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  • http://www.deadlysins.info/wordpress/wp-content/uploads/2010/04/donut.jpg\n
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  • In this example, we analyzed AIGA’s top 500 unique queries for a specific month--these accounted for exactly 37% of all search activity. We used Microsoft’s “LEN” function to count the number of characters in each query, and then calculated the queries’ mean and median lengths (10.648 and 10, respectively). \n<big chart>\nSorting by query length, we see that the maximum length among these 500 queries was 62 characters, but that is something of an outlier; the next longest was 36, then 28 and flattening out (apparently, Zipf is everywhere):\n<small chart>\nBased on this data, we might be safe using a search entry box with a width in the 15-20 characters range. If horizontal real estate isn’t at a premium, a width of 30 characters would be even better.\n\n
  • Zipf is everywhere):\n<small chart>\nBased on this data, we might be safe using a search entry box with a width in the 15-20 characters range. If horizontal real estate isn’t at a premium, a width of 30 characters would be even better.\n\n
  • Zipf is everywhere):\n<small chart>\nBased on this data, we might be safe using a search entry box with a width in the 15-20 characters range. If horizontal real estate isn’t at a premium, a width of 30 characters would be even better.\n\n
  • Zipf is everywhere):\n<small chart>\nBased on this data, we might be safe using a search entry box with a width in the 15-20 characters range. If horizontal real estate isn’t at a premium, a width of 30 characters would be even better.\n\n
  • Zipf is everywhere):\n<small chart>\nBased on this data, we might be safe using a search entry box with a width in the 15-20 characters range. If horizontal real estate isn’t at a premium, a width of 30 characters would be even better.\n\n
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  • Might have this already in the SSA workshop slides\n\n
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  • Mention Sandia’s example\n
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  • Anchors will be liked by good leaders, and will outlast bad leaders\n
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  • Transcript

    • 1. Adaptable Information ArchitectureHow to say no to your next redesign Lou Rosenfeld •  lou@rosenfeldmedia.com Rosenfeld Media UX Workshops •  Fall 2012
    • 2. Hello, my name is Lou www.louisrosenfeld.com | www.rosenfeldmedia.com
    • 3. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 4. What isinformation architecture?
    • 5. Definition The art and science of structuring, organizing and labeling information to help people find and manage it.
    • 6. Three circles
    • 7. Three tracks1. Top-down navigation: Anticipates interests/questions at arrival2. Bottom-up (contextual) navigation: Enables answers to emerge3. Search: Handles specific information needs
    • 8. What is redesignand why should it die?
    • 9. Why am I so down onredesign?
    • 10. Why am I so down onredesign?
    • 11. Redesign ishollow, meaningless,and a vanity.It is the true definitionof insanity.
    • 12. A story in the Ann ArborNews
    • 13. UM was going to redesign itsGateway
    • 14. UM was going to redesign itsGateway
    • 15. UM was going to redesign itsGateway
    • 16. UM was going to redesign itsGateway
    • 17. $250,0 00
    • 18. $250,0work study students! 00
    • 19. $250,0work study students! 00 WebObjects!
    • 20. They even had a ribbon-cutting
    • 21. This became...
    • 22. ...this
    • 23. ...this
    • 24. ...this
    • 25. ...this
    • 26. Then they did itall over again
    • 27. Then they did itall over againand again
    • 28. Then they did itall over againand againand again
    • 29. Then they did itall over againand againand againand again
    • 30. Where we are today
    • 31. Where we are today
    • 32. Where we are today
    • 33. Where we are today
    • 34. Where problems are undefinedlies insanity and vanity
    • 35. Where problems are undefinedlies insanity and vanity We attempt the impossible: “boil the ocean” in no time at great cost
    • 36. Where problems are undefinedlies insanity and vanity We attempt the impossible: “boil the ocean” in no time at great cost We believe the unbelievable: unwarranted claims from agencies and software vendors
    • 37. Where problems are undefinedlies insanity and vanity We attempt the impossible: “boil the ocean” in no time at great cost We believe the unbelievable: unwarranted claims from agencies and software vendors We become irresponsible: unwarranted declarations of victory at the expense of our teams and users
    • 38. See the problem differently
    • 39. Your site is acomplex adaptive systemJohn Holland:“A Complex Adaptive Systemis a dynamic network ofmany agents acting in parallel,constantly acting and reactingto what the other agents aredoing.”
    • 40. Examples of CAS
    • 41. Examples of CAS
    • 42. Examples of CAS
    • 43. Your site is a moving targetbuilt on moving targets
    • 44. Your site is many sites, products,things out of your control more John Holland: “The control of a complex adaptive system tends to be highly dispersed and decentralized... “The overall behavior of the system is the result of a huge number of decisions made every moment by many individual agents.”
    • 45. “The perfect is theenemy of the good.”Voltaire mighthave added:“Constant changemeans never havingto say you’re sorry.”
    • 46. You can’t redesignBut you must refine1. Prioritize: Identify the important problems regularly2. Tune: Address those problems regularly3. Be opportunistic: Look for low-hanging fruit
    • 47. Prioritize becausea little goes a long way
    • 48. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
    • 49. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
    • 50. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
    • 51. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
    • 52. A handful of queries/tasks/ways to navigate/features/ A little goes a long waydocuments meet the needs of your most important audiences
    • 53. (and the tail is quite long)
    • 54. (and the tail is quite long)
    • 55. (and the tail is quite long)
    • 56. (and the tail is quite long)
    • 57. (and the tail is quite long)
    • 58. Zipf in text
    • 59. A little really does goa long way A handful of... • queries • tasks • ways to navigate • features • documents ...meet the needs of your most important audiences
    • 60. Unverified rumor:90% of Microsoft.com’s content has never been accessed
    • 61. From prioritization......to a report card (repeat regularly)
    • 62. Treat your site like an onion Each layer is cumulative informationlayer usability content strategy architecture indexed by search 0 engine leave it alone leave it alone squeaky wheel issues 1 tagged by users addressed refresh annually tagged by experts (non- test with a service 2 topical tags) (e.g., UserTesting.com) refresh monthly tagged by experts “traditional” lab-based titled according to 3 (topical tags) user testing guidelines deep links to support structured according 4 contextual navigation A/B testing to schema
    • 63. Be an incrementalist:tune because things change
    • 64. From projects to processes:a regular regimen of design Example: the rolling content inventory
    • 65. Impact of change on design(queries)
    • 66. IRS before 4/15
    • 67. Before April 15IRS before 4/15
    • 68. IRS after 4/15
    • 69. After April 15IRS after 4/15
    • 70. Be an opportunist:look for the low-hanging fruit1. Top-down navigation: Anticipates interests/questions at arrival2. Bottom-up (contextual) navigation: Enables answers to emerge3. Search: Handles specific information needs
    • 71. Life by a thousand cuts 50% of users are search dominantx 5% of all queries are typos, fixed by spell checking. 2.5% improvement to the UX 50% of all users are search dominantx 30% (best bet results for top 100 queries) 15% improvement to the UXDitto for improving content, search results design,navigation design…
    • 72. Summary Site redesign is wasteful, expensive, and ineffective 1. You don’t have a single, perfectible site 2. You do have a collection of living, changing pockets of content and functionality You can refine 3. Prioritize the problems that are most important to your users 4. Regularly address these problems 5. Identify opportunities to make small improvements that go a long way
    • 73. Prioritizing and TuningTop-Down Navigation
    • 74. The data-driven main page:Who wants what and when?
    • 75. Who wants what?US English speakers
    • 76. Who wants what?German speakers
    • 77. When do they want it?
    • 78. Commerce sites get it
    • 79. The IRS gets it
    • 80. But really, who caresabout the main page?
    • 81. But really, who caresabout the main page?
    • 82. The risk of main page fixationFrom Tony Dunn’s Tales from Redesignland(http://redesignland.blogspot.com/)
    • 83. Focusing on main page =taking Zipf too far...plus lots of competition (Google, ads/landing pages)
    • 84. The tail that wags the dog:site map drivesimproved site hierarchy
    • 85. Site map by tool, unit, and format
    • 86. Site map by tool, unit, and format
    • 87. Site map by tool, unit, and format
    • 88. User-centered site mapUser-centered site map...
    • 89. Asking the possiblefrom your site index
    • 90. Specialized site indices
    • 91. Specialized site indices
    • 92. Specialized site indices Cisco’s site indices are specialized by content type (products, services)
    • 93. Best bet-based site indices MSU’s site index is built on popular information needs (based on best bet search results)
    • 94. Going broad and deep withguides (AKA microsites)
    • 95. Kansas main pages loves guides
    • 96. Kansas main pages loves guides
    • 97. But the guides need a littlework
    • 98. Vanguard’s main page lovesguides
    • 99. Vanguard’s main page lovesguides
    • 100. The Tax Center is a guide
    • 101. One more example: IRS
    • 102. One more example: IRS
    • 103. ...e-filing is presented assequential steps
    • 104. Summary: Top-down navigation Prioritize main page content and layout 1. Confuse as necessary by diverting attention 2. Counter politics with data; e.g., use seasonality to drive design Tune and prioritize site-wide navigation 3. Use the site map as a skunkworks for site-wide hierarchy 4. Base site indices on specialized content or popular information needs (e.g., best bets) 5. Use guides (micro-sites) as narrow/deep complement to broad/shallow navigation schemes
    • 105. Break
    • 106. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 107. concert calendar album pages artist descriptions TV listings Exercise: Content Modelingalbum reviews discography artist bios
    • 108. Lunch
    • 109. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 110. Prioritizing and TuningContextual Navigation
    • 111. Establishing Desire LinesUse Content modeling • Site search analytics
    • 112. Where do searches begin?Not just the mainpage, according to aUser InterfaceEngineering study(http://is.gd/j1NHeS)
    • 113. Using site search analyticsto identify desire lines
    • 114. Choose acommon contenttype (e.g., events) 
Where should 
users go from here? 

    • 115. 
 
 
 
 
 
Analyze frequent queries generated from each content sample
    • 116. 
 


    • 117. 
 
 
Develop logic that automatically links an event to:1. articles that share the event’s topic2. events that share the topic but have differentgeographic locales
    • 118. What content typesshould we be connecting?
    • 119. Important content types emerge from content modeling concert calendar album pages artist descriptions TV listingsalbum reviews discography artist bios
    • 120. Using SSA to prioritize contenttypes
    • 121. Getting content types out ofsite search analytics Take an hour to... • Analyze top 50 queries (20% of all search activity) • Ask and iterate: “what kind of content would users be looking for when they searched these terms?” • Add cumulative percentages Result: prioritized list of potential content types #1) application: 11.77% #2) reference: 10.5% #3) instructions: 8.6% #4) main/navigation pages: 5.91% #5) contact info: 5.79%
    • 122. What should we use toconnect content types?
    • 123. Which metadata attributes will yourcontent model depend upon?
    • 124. More on prioritizing metadata attributes
    • 125. Prioritizing semantic relationships
    • 126. How do weprioritize content?
    • 127. Some content value variables I
    • 128. Some content value variables I UsabilityPopularityCredibility
    • 129. Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility
    • 130. Some content value variables Currency Freshness Authority Follows guidelines (e.g., titling, I metadata) UsabilityPopularityCredibility Strategic value Addresses compliance issues (e.g., Sarbanes/Oxley) Content owners are good partners
    • 131. Subjectively “grade” your content’s value1.Chooseappropriate valuecriteria for eachcontent area2.Weight criteria(total = 100%)3.Subjectively gradefor each criterion4.weight x grade= score5.Add scores foroverall score
    • 132. Subjectively “grade” your content’s value1.Choose Subjectiveappropriate value assessmentcriteria for eachcontent area2.Weight criteria(total = 100%)3.Subjectively gradefor each criterion4.weight x grade= score5.Add scores foroverall score
    • 133. Put the grades together for a moreobjective “report card” Helps prioritize content migrations, refreshes, ...
    • 134. Put the grades together for a moreobjective “report card” Objectifies subjective assessments Helps prioritize content migrations, refreshes, ...
    • 135. Summary:contextual navigation Use content modeling and site search analytics to 1. Identify and prioritize content types 2. Identify desire lines 3. Improve contextual navigation between content types 4. Identify and prioritize metadata attributes Prioritize content areas/subsites by establishing balanced value criteria
    • 136. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 137. Exercise: site search analytics
    • 138. Break
    • 139. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 140. Prioritizing and Tuning Search
    • 141. Make “the Box” accommodatemost searchers’ queries
    • 142. How long are our queries? Top 500 queries (37% of all traffic)
    • 143. Mean = 10.6 charactersMedian = 10 characters
    • 144. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longer
    • 145. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20s 

    • 146. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? 

    • 147. Mean = 10.6 charactersMedian = 10 charactersLong tail queries likely longerTop queries often in low 20sDesired: @30 characters;Can you get that many? 
Safe: @15-20 characters
    • 148. We’ve seen this before:auto-completing queries
    • 149. Auto-completing from aknown, common items (e.g.,
    • 150. Auto-completing from aknown, common items (e.g., Uses known terms: e.g., movie titles and actor/director names
    • 151. Auto-completing from queries
    • 152. Uses common queriesAuto-completing from queries
    • 153. Auto-completing from bestbets
    • 154. Auto-completing from bestbets Uses best bets
    • 155. Making change easy:supporting query refinement
    • 156. The absolutemeaninglessness ofadvanced search
    • 157. The absolute meaninglessness of advanced search 
At University of Alaska-Fairbanks,advanced = expanded search
    • 158. The absolute meaninglessness of advanced search 
At University of Alaska-Fairbanks,advanced = expanded search At the IRS, advanced = narrowed search 

    • 159. Contextualizing “advanced” features
    • 160. Look to session data forprogression and context
    • 161. Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works
    • 162. Look to session data forprogression and context search session patterns 1. solar energy 2. how solar energy works search session patterns 1. solar energy 2. energy
    • 163. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns 1. solar energy 2. energy
    • 164. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy
    • 165. Look to session data forprogression and context search session patterns search session patterns 1. solar energy 1. solar energy 2. solar energy charts 2. how solar energy works search session patterns search session patterns 1. solar energy 1. solar energy 2. explain solar energy 2. energy search session patterns 1. solar energy 2. solar energy news
    • 166. Improving performance forspecialized queries
    • 167. Recognizing proper nouns,dates, and unique ID#s
    • 168. Surfacing specialized contenttypes in search results
    • 169. Tuning Search Results:Handling specialized answers
    • 170. Tuning Search Results:Handling specialized answers
    • 171. Tuning Search Results:Handling specialized answers
    • 172. Tuning Search Results: Handling specialized answers“Product quick links” come directly from product content modelThese results are a strong counterbalance to raw results
    • 173. When raw isn’t good enough:best bet search results
    • 174. best bet #1
    • 175. best bet #1best bet #2
    • 176. best bet #1best bet #2even more best bets
    • 177. best bet #1best bet #2even more best betsraw results
    • 178. best bet #1best bet #2even more best betsraw results
    • 179. best bet #1 best bet #2 even more best betscompetition raw results
    • 180. best bet #1 best bet #2 even more best betscompetition danger? raw results
    • 181. best bet #1 best bet #2 even more best betscompetition danger? data raw results
    • 182. The 0 search results page:search’s equivalent of the 404
    • 183. Tuning Search Results: 0 results pagesNot helpful
    • 184. Tuning Search Results: 0 results pagesNot helpfulMuch better: “Did youmean?” and Popular Searches
    • 185. Summary: Search systems Tune query entry 1. Make “The Box” wide enough 2. Support query auto-completion to focus queries 3. Surface the right features to support query refinement 4. Recognize and take advantage of specialized queries Tune search results design 5. Surface specialized content types as results for specialized queries 6. Complement raw results with best bets 7. Enable recovery from finding 0 search results
    • 186. Changing your workand your organization
    • 187. Doing your work differently1. Processes, not projects2. Rebalancing your research and design
    • 188. From time-boxed projectsto ongoing processes Example: the rolling content inventory
    • 189. What else can roll? Each week, for example... • Analyze analytics for trends • Task analysis of common needs Each month... • User survey • Exploratory analysis of analytics data Each quarter... • Field study • Card sorting
    • 190. Build a practice that’sbalanced and data-driven
    • 191. User Research Landscapefrom Christian Rohrer: http://is.gd/95HSQ2
    • 192. User Research Landscape Ongoing coverage of each of these 4 quadrantsfrom Christian Rohrer: http://is.gd/95HSQ2
    • 193. A balanced research regimen Each week... • Analyze analytics for trends (Behavioral + Quantitative) • Task analysis of common needs (Behavioral + Qualitative) Each month... • User survey (Attitudinal + Quantitative) • Exploratory analysis of analytics data (Behavioral + Qualitative) Each quarter... • Field study (Behavioral/Attitudinal + Qualitative) • Card sorting (Attitudinal + Qualitative/Quantitative)
    • 194. Lou’s TABLE OFOVERGENERALIZED Web Analytics User Experience DICHOTOMIES Users intentions and What they Users behaviors (whats motives (why those things analyze happening) happen) Qualitative methods for What methods Quantitative methods to explaining why things they employ determine whats happening happen Helps users achieve goals What theyre Helps the organization meet (expressed as tasks ortrying to achieve goals (expressed as KPI) topics of interest) Uncover patterns and How they use Measure performance (goal- surprises (emergent data driven analysis) analysis) Statistical data ("real" data Descriptive data (in smallWhat kind of data in large volumes, full of volumes, generated in lab they use errors) environment, full of errors)
    • 195. Getting your organizationto support your work1. Making friends and allies2. Changing your leaders’ minds
    • 196. Making friends and allies
    • 197. Showing content ownershow their content performs
    • 198. Showing content ownershow their content performs
    • 199. Helping marketingdevelop better messagingJargon vs. Plain Language at Washtenaw Community College • Online courses were marketed using terms “College on Demand” (“COD”) and “FlexEd”; signup rates were poor • Compare jargon with “online” (used in 213 other queries) • Content was retitled rather than re-marketed
    • 200. Helping IT say “no” with authorityReduce pressure to solve problems with technologies by making what we have workMinimize radical changes to platforms • Enterprise search • Content management systems • Analytics applications • ...
    • 201. Changing leaders’ minds
    • 202. Talking pointsfor refining, against redesigning 1. Solve the problem(s) 2. Save money 3. Reduce/end radical organizational changes
    • 203. Solving the problem(s)• Forcing the issue: ban the term “redesign” from discussions• Data-driven definition / prioritization / tuning / opportunism• Creating anchors to keep project from spinning out of control: elevator pitch / mission / vision / goals / KPI
    • 204. Steward Brand’s Pace Layeringmodel Typical design focus Stuff that gets ignored: mission, vision, charter, goals, KPI, objectives
    • 205. Example of an anchor:your elevator pitch Read Gamestorming (Gray, Brown, Macanufo); O’Reilly, 2010). http://amzn.to/nnpERG
    • 206. Saving money• Life by a thousand cuts: small changes have huge impacts (see: Zipf)• Reuse and retain technology investments• Retain institutional knowledge• Get more from your (empowered) team and make it pay for itself• Spend less on external support and fire your agency
    • 207. Reduce/end radicalorganizational changes• End the pendulum swing from centralized to decentralized approaches• Reorganize information, not people• Build self-sustaining, steady in-house capabilities to prioritize and tune
    • 208. Being prepared to fail
    • 209. Sometimes your leadersare in a hurry
    • 210. Sometimes your leadersare not very smart
    • 211. Sometimes your organizationis immature
    • 212. Nurit Peres’ Company UX Maturity Model(http://is.gd/x1dOuP)
    • 213. Renato Feijó’s UX Maturity Model(http://is.gd/dul2t2)
    • 214. Always be ready to gounder the radar
    • 215. Summary: changing your workand your organization Do your work differently 1. Move from time-based projects to ongoing processes 2. Build a balanced, data-driven practice Get your organization to support your work 3. Make friends and allies 4. Change leaders’ minds by • Solving problems • Saving money • Reducing radical change Be prepared to fail
    • 216. Discussion
    • 217. Agenda1. Hello / What is information architecture?2. Why redesign should die / The alternatives3. Prioritizing and tuning top-down navigation4. Break5. Exercise: content modeling6. Lunch7. Prioritizing and tuning contextual navigation8. Exercise: site search analytics9. Break10. Prioritizing and tuning search11. Changing your work and your organization / Discussion
    • 218. Say hello Lou Rosenfeld lou@louisrosenfeld.com Rosenfeld Media  www.louisrosenfeld.com | @louisrosenfeld www.rosenfeldmedia.com | @rosenfeldmedia

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