GuruScan KM guest lecture Radboud University

GuruScan— know the expert —

user friendly expert management

Bart Verheijen – December 10th 2010

Agenda

• About us

• Case: NOC*NSF

• Workgroup Quickscans

[email protected] 024-3603442

GuruScan

• Dion Slijp– informatics– e-marketing– 8,5 years Océ

• Bart Verheijen– chemistry– management– 5 years Océ


GuruScan products

• Integrated intranet service• Hosted webservice• Knowledge scan• Quickscan workshop• TMS workshop


Customers


Case NOC*NSF


NOC*NSF

• Organized sports Netherlands• 90 sport unions (e.g. KNVB)• 27.000 associations (e.g. NEC)• 170 employees• 5000 direct contacts• 4,7 million people (indirect)


Sport union goals

• Create and uphold rules• Organize competitions• Educate and certify professionals• Talent scouting and development• Organizing events• Fundraising with sponsors


Sport unions

• Sports minded• Non competitive• Same activities• No shared learning

– explanation video (dutch)


http://www.youtube.com/watch?v=UaVFWyZP4Y0




Challenge


Challenge NOC*NSF

• Empower shared learning

• Reach active volunteers in sports

• Towards 2028 Olympics!


Solutions?

• Profile sites• CV database• Yellow pages• Document database

• Cost lot of money No result

[email protected] 024-3603442 Copyright © GuruScan 2010

Pain before the Gain

• Profile systems 3 – 10% active users make profile

• Update profiles 1 – 3%


Documentation

• Documentation follows activity

• Do you report on every thing you do? During work or in off-time?

• 100% knowledge 70% tell 30% write


Knowledge or information

• Did you find what you are looking for?

• What is the answer / question?

• Knowledge = information x person– Person = Experience, Skills, Attitude


How do you solve a problem?

• Search the Internet

• Read book/document

• Follow a course

• Ask a colleague


Copyright © GuruScan2010

Knowledge Networks

• A knowledge network captures who is aware of whose knowledge and skills


“[employees] are roughly five times as likely to turn to a person for information as to an impersonal source”

Tom Allen (MIT)

Knowledge Networks

• Everybody knows somebody with more knowledge on topic X


Henri

German?

nothing

Anna

Melanie

Copyright © GuruScan 2010

Knowledge Networks


Henri

German?

nothing

Anna

expert

Sophie

little

Pete

little

Melanie

muchFrench

Pete

expert

• Combine Personal Knowledge Networks

Copyright © GuruScan 2010

Combined social knowledge networks


Transactive memory system

• Insight in what knowledge is available within a team

• Team which is most effective in finding knowledge amongst each other (and external) is the most successful

• Not the team with the smartest people


Intranet result


Intranet result


Background

• Huijsen et al (2008), ExpertFinder: Collaborative Expertise Localization, I-KNOW ‘08.

• Cross & Parker (2004), The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations.


Quickscan workshopResults and discussion


Quickscan workshop

• December 2nd and 3rd

• 5 groups• 160 participants• 30 minutes


Workshop activities

• Create subjects– too much freedom?

• Make connections– who do you know?

• Extra round• Choose a winner


Winners

• Fleur (Group 1)• Carlijn (Group 2)• Alex (Group 3)• Bas (Group 4)• Felicia (Group 5)


Grand total results

• 1534 subjects • 5912 connections• 160 participants• 255 other people identified


Total network


Common subjects

• Communication• Knowledge management• Organisation skills• Leadership

• and Beer


Levels by workgroup


W1 W2 W3 W4 W5

# Subjects 366 308 279 260 321

Levels

Inexperienced 189 151 224 153 184

Starter 128 106 74 104 64

Advanced 349 337 227 254 340

Expert 195 249 243 131 119

Total 861 843 768 642 707

Connections

• Connections between workgroups


To\from W1 W2 W3 W4 W5

W1 430 29 8 2 32

W2 19 615 3 0 0

W3 19 0 737 0 1

W4 0 0 15 1105 9

W5 20 0 19 2 671

ext 444 771 163 446 352

Total 932 1415 945 1555 1065

Workgroup connections


Workgroup connections


Contact points

• Erik• Maarten• Juliette• Thijs• Demian• Christian


Contact points


Reciprocities


To\from 1 2 3 4 5

1 0.25 0.06 0.14 0.0 0.09

2 0.06 0.25 0.0 0.0 0.0

3 0.06 0.0 0.28 0.0 0.0

4 0.0 0.0 0.0 0.33 0.0

5 0.13 0.0 0.0 0.0 0.26

Reciprocities


Grouping by network


Highest out-degree

• Joost 303• Paula 231• Bartosz 145• Mehdie 141• Lucie 135• Sander 117• Casper 114


Highest in-degree

• Paul 63• Steve 54• Bill 52• Erik 48• Thijs 46• Jori 42• Joeri 42


Ego network C. van Mourik


Transactive Memory

• Knowledge is in people• Knowledge sharing is interaction• Succesfull teams know where to

find necessary knowledge• Share your meta-memory


Questions


• www.guruscan.nl

• [email protected]

• 06 19 342 603(Bart Verheijen)

http://www.guruscan.nl/

mailto:[email protected]

Thanks for your attention


GuruScan KM guest lecture Radboud University

Technology

knowledge networkseverybody

copyright guruscan2010

intranet result

challenge noc

case noc

information x personperson

sport union goalscreate

topic x