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Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
Email research by Victoria Bellotti from PARC
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Email research by Victoria Bellotti from PARC

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  • If a typical knowledge worker has 70 to-dos at any given time of which 80% get done in 2 weeks, that means that people do about 1400 to-dos a year. Think about how often you can recall failing to do an important to do; it’s not very often and certainly a drop in the ocean compared to the hundreds you succeed in doing in time.
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    1. PIM Research at PARC<br />Victoria Bellotti<br />Principal Scientist (bellotti@parc.com)<br />
    2. Overview<br />Personal information management (PIM) in the wild<br />And overload<br />Embedding resources in email<br />Activity management<br />What is PIM?<br />Personal information management means dealing with documents, messages, scheduling events, to-dos, contacts, notes<br />Essentially the work we do to make it possible to do our work<br />© 2010 PARC | Confidential <br />
    3. Postulating PIM<br />3 of 25<br />
    4. The Reality of PIM<br />PARC | 4<br />
    5. Overload: Analysis of Time Spent in Email<br />Microanalysis of samples of video observation of email triage<br />The time that people are focused on dealing with incoming email<br />Heavily interleaved with:<br />Reading, skimming, editing, organizing, prioritizing, phone calls etc.<br />Breakdown of time spent<br />23.1% reading email<br />6.2% scanning inbox<br />2.4% deleting messages<br />2% looking for messages<br />9.5% filing messages<br />1.1% spent adding attachments<br />0.8% opening attachments<br />Most of the rest spent writing email and editing documents<br />20% of time looking around, searching for and organizing information<br />This likely overflows into the rest of the day since email is an archive<br />5 of 25<br />
    6. Overload: Analysis of Thread Complexity<br />Quality not quantity<br />~50% messages are threaded<br />Index of complexity<br />No. of threads X (days per thread/steps per thread)<br />Seems to be a better indicator of overloading than quantity<br />Obviously because there’s more to remember to keep track of<br />6 of 25<br />Active threads of the manager who complained the most about overload<br />
    7. Personal Knowledge Pad<br />
    8. Snapshot To-do Study<br />Average about 70 to-dos and 11 places<br />Only 14% of to-dos on paper-lists and e-lists<br />2/3 online, 36% in email, 12% in e-calendar<br />Distributed across the workplace and elsewhere<br />The to-do doesn’t describe the task<br />Natural language may not be used<br />Contextual and personal cue<br />To-dos have multiple roles:<br />Reminders: “I would like to remember to do this at an appropriate time”<br />Planning tools: “What must I do next?”; “What needs doing soon?”<br />Status indicators: “Done”; “Important”; “Priority”<br />Indices: “What content is involved in this task?”; “How do I access it?”<br />A significant minority of to-dos may not get done<br />
    9. All(most) in the Head<br />A relatively tidy and explicit list<br />Non specific<br />Acronyms<br />Incomplete sentences<br />Nonsense<br />Illegible<br />An untidy and less explicit list<br />“Beth blah blah”<br />Manager at PARC<br />
    10. To-dos in the Wild<br />We interviewed people in detail about their to-dos once a week for four weeks with a final 5th interview.<br />We classified them<br />What they were about and where they were stored<br />We also coded them for about 30 factors that might affect their getting done, e.g., importance, consequence of not doing, difficulty, etc.<br />Each week we asked whether the last week’s to-dos were done<br />PARC | 10<br />
    11. Significant Determinants of Prioritization: Getting Things Done in a Week<br />Hard-to-forget tasks<br />Can’t-do-it-now tasks<br />Factor Significance (random chance of data)<br />Urgency <0.1%<br />Customer <0.1%<br />Is a meeting <0.1%<br />Involving others (not mtg) <0.1%<br />Importance 0.1%<br />Non-discretionary 1.5% <br />Common 5.6%<br />Social<br />Having no reminder 1.2%<br />On a to-do list negative <0.1%<br />
    12. Conclusions<br />People are good at prioritizing<br />Only 1% of cases of dropping the ball (but none high priority)<br />They just need more help with the PIM<br />Resources need to be embedded in their work habitat<br />PARC | 12<br />
    13. Significant Determinants of Prioritization: Getting Things Done in a Week<br />Are these more important?<br />Are these less important?<br />Factor Significance (random chance of data)<br />Urgency <0.1%<br />Customer <0.1%<br />Is a meeting <0.1%<br />Involving others (not mtg) <0.1%<br />Importance 0.1%<br />Non-discretionary 1.5% <br />Common 5.6%<br />Why should we care about this data?<br />Aren’t people supposed to be bad at prioritization?<br />Having no reminder 1.2%<br />On a to-do list negative <0.1%<br />
    14. Prioritization and “Dropping the Ball”<br /><ul><li>Well how bad are they?</li></ul>68% done in a week<br />81% done by final interview<br />79% I1,81% I2,83% I3and 80% I4done by final (I5) interview<br />Little happens after two weeks (lifespan of active to-dos)<br />16% were not done but with good reason (16+81=97)<br />Only 3% cases of dropping the ball (all non-critical)<br />Our participants are successfully optimizing<br />Contradicts the popular press<br />Resources are working as reminders, status and prioritizers<br />
    15. Optimization<br />No. Tasks<br />The Challenge<br />The challenge is to keep the dotted line as far to the left as possible<br />This may move to the right in cases of overload, but that’s OK...<br />As long as the line is straight<br />Popular idea of poor prioritization is not supported<br />So we probably don’t need to help with this<br />But why do people think they are bad prioritizers?<br />Slight evidence that assessing low importance tasks takes so much time that you might as well do them<br />But... task management time and effort contributes to overload<br />Documented as 20% of time in email<br />How do we lower this cost?<br />Make it MUCH easier; automate the drudge work<br />Not Done<br />Done<br />High Value<br />Low Value<br />Overload<br />Poor prioritization<br />
    16. Embedding Resources in Email<br />16 of 32<br />
    17. 17 of 25<br />TaskMaster<br />In a small trial half of its users continued using it for months after end of study even though it lacked many features of Outlook<br />
    18. Optimizing for Activity Inferencing(under DARPA CALO Program)<br />PARC | 18<br />
    19. Project Objectives<br />Goals<br />Simplify PIM and activity management<br />UI that increases explicitness of activity context for better ML<br />Design Innovation<br />UX construct “Activities” that people can interact with<br />System offers different human-meaningful ‘types’ (e.g. meeting, hiring)<br />User creates instances of each type<br />System populates the instance with predetermined containers & behaviors<br />When user drags content to activity good stuff happens<br />Meanwhile machine learns about this instance of the human activity<br />RQ1. Will users adopt pre-designed structures?<br />RQ2. Can we incent users to label their content precisely? <br />
    20. TV-ACTA<br />TaskVista (TV) to-do list<br />Activity-Centered Task Assistant (ACTA) embedded in Outlook<br />Pre-designed folder component structure<br />Paper to-dos<br />Drag-and-drop anything into Activity: automatic organization into contacts, documents, correspondence<br />Drag-and-drop or type-in to-do and Promote to Activity<br />
    21. More Features: Unified Content Collection<br />
    22. Structured Documents<br />Drag-and-drop Agenda with Attendees and Final Materials Presentations and Documents<br />
    23. Structured Email:One menu-selection to email agenda to all Attendees<br />
    24. Useful Activity-Related Forms Links<br />
    25. Instant Map<br />No need to type in address again; address came from agenda<br />
    26. Evaluation<br />RQ1. Will users adopt pre-designed structures?<br />Yes, more Activities created than folders<br />RQ2. Can we incent users to label their content? <br />Yes, users selected specific Activity types and used components<br />Users find Activity template approach appealing in spite of bugs and even without ML benefits<br />Justifies further exploration of this approach<br />
    27. Ongoing Research: Logging and Visualizing plus Activity Inferencing<br />PARC | 27<br />
    28. Hybrid Field Research<br />PARC | 28<br />

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