Cutting and Pasting Up: Understanding Users with Task Trail

Intel ConfidentialInternal Use Only – Do Not Distribute

Cutting and Pasting Up: Understanding Users with

Task Trail

Eleanor WynnPrincipal Engineer

Intel Information TechnologyCarlos Jensen

Heather LonsdaleOregon State University EECS

December 16, 2009

IT.intel.com 12/15/20092

Complexity on the Desktop•Information workers are

– doing kindergarten tasks (cut & paste) – to create post-graduate content (strategy)

•Users focus on information, projects, presentations

•Focus on applications creates user overhead •How much overhead? A lot!

– Machine learning tracks behavior– Provides empirical view of desktop activity

Volume/diversity of content demands innovation


Users: overwhelmed by desktop

windows were an innovation 29 years ago; they complicate multi-tasking work


Research Q: How Bad is It?To find out we used two machine learning tools

(plus interviews):

• Task Tracer links activity to a project • Task Trail tracks data reuse

• Tools built and research conducted by Oregon State University CSEE Machine Learning Group– Tom Dietterich– Jon Herlocker– Carlos Jensen – Simone Stumpf

Problem too fine-grained to observe with other methods


Findings Task Tracer StudyTask Switching

• Application switches: 1/minute• Window switches: 1/40 secs• Resources used per day: 40+• % of time navigating: 90• IE search repeat rate: 33%• Folder revisit rate: 41%• Recovery time from

interruptions:10minutes

% Intel multi-teaming

LessonLesson: need more context retention : need more context retention in desktop designin desktop design


Multi-Tasking:Projects Per Day

12/06/22 Oregon State University 6

8

7

3

2

7

10

0

2

4

6

8

10

12

s1 s2 s3 s4 s5 s7

Med

ian

Proj

ects

Per

Day


Re-Finding Information

12/06/22 Oregon State University 7

0%

10%

20%

30%

40%

50%

60%

70%

s1 s2 s3 s4 s5 s6 s7

Perc

ent t

hat o

f ope

ns th

at a

re re

-find

s

Email

Web

Docs

All

3854 cases551/person-month

Email and web are the biggest opportunities.

It’s not about the time savings, it is the It’s not about the time savings, it is the flow stateflow state


What Task Trail Tracks• .Net application runs under Windows:

– Word, Excel, PowerPoint, IE and Outlook • Using Microsoft APIs tracks provenance related events

– File opens & closes– Rename– File moves– Save as– Copy-paste– Attachment– Uploads– all stored in a database.

• Networks visualized with yEd software package


Participant Summary• 24 subjects, different roles & groups

– 37.5% Female study population (9 subjects)• 18 completed study (5+ weeks of active participation)

– 25% study mortality rate, no gender bias• Reasons for dropping out:

– Problems with Internet Explorer and some Web 2.0 websites (1)– Incompatible with some older hardware/software configurations

(3)– Start of sabbatical (1) – 1 subject excluded due to database problems


Study Overview

Average Median St.Dev Max Min Total

Participation (Active work days) 42.94 43 12.92 63.0 21.0 730

# of unique MS Office documents 165.8 161 87.68 335 26 2,807

Document reuse (sessions) 1.78 1.61 0.41 71 1

Activ

e w

ork

days

Subjects Longitudinal data collected on use and reuse of documents and information on the desktop from subjects in a variety of IT roles.

18 subjects observed over total of 730 workdays, interacting with 2,819 Word, Excel, and PowerPoint documents (primary focus of study)

Tracked information access, reuse and cross-application flow


Findings Task Trail: Inter-Application Information Transfer

1%

1

%

10%

3%

8%

4%

11%

12%

8% 3%

17%6%

Information flows between apps, docs have permeable boundaries


•Provenance networks are: common, complex, span applications. •Average of 15.7 provenance networks used in normal work; •Average size: 7.6 documents, 11 edges•Largest network had >100 nodes, 300 edges

Provenance NetworksProvenance Networks

Information DNA


Large Graph Examined

Master Spreadsheet

79 individual test scripts

NODE COLOR KEYExcelPowerPointWordOutlook/Web (White))


Provenance Network Facts & Concerns

• Centered on small set of high value repositories

• Importance of tracking information source for:– Data currency– Data quality based on source– Attribution to original sources

Permeable boundaries mean mixing different data age & quality, lose sources, meanwhile users hyperactive


Interim Outcomes•New opportunity to revive a ’00 solution

Problem is deeper information design


Possible Solutions 1: After-the-fact solutions

•Intelligent software to clean up the mess– File search with context of use data– Interruption recovery via context retention– Associative suggestion from pattern-matching

This is doable, product exists but takes too much user overhead to assist learning


Outlook UI Associated Project(s)Smart Desktop

Toolbar

One Search Folder for Each Project

Project(s) associated with selected items


Possible Solutions 2: New Information Framework

•Redesign solutions:–Totally rethink information objects

–Not a KM problem–Visualization not an end in itself

–has to rely on the objects

Call to action: more work, please!

Documents

Cutting and Pasting Up: Understanding Users with Task Trail