Help as Knowledge Management: Taking Care of Scarce Resources through Informal Encouragement JD...

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Help as Knowledge Management:

Taking Care of Scarce

Resources through Informal Encouragement

JD Eveland, Ph.D.

December 11, 2000

Today’s Context

• Organizations are increasingly technology dependent

• Technology isn’t self-implementing• Traditional model: expensive machines,

cheap/replaceable people• Current model: cheap machines,

expensive people• Thus: new kinds of “joint optimization”

The socio-technical balance has shifted…

• Crucial resource is knowledge• Knowledge is most critically

embedded in the organization’s people

• It’s very easy for knowledge to walk out the door…

• Informal relationships make the system work

“Help” as a key need

• Knowledge is unequally distributed• Knowledge is a social event• The organization works only

because people help each other• Most help is informal• Most organizations aren’t set up to

encourage helping relationships

The CGU Studies

• CGU -- a private graduate school

– 2000 students, 200 staff

– Diverse small programs, no “technical”

departments

– Distributed environment

– Major transition in computing support• Pre/Post surveys on computer use and help• Further analysis on organizational and

physical distance

Project Structure

• Three survey rounds– Pre-hardware– One year of experience– Network experience

• Surveys covered:– Demographics– Capabilities used– Information work– Satisfaction– Expectations– Interactions with others

Interaction networks surveyed

• People with whom they work regularly

• People to whom they go for help when they have problems with the computer

• People to whom they provide such help

Connections in the network

Work networkHelp network

WithinWork group

AcrossWork groups

WithACC

OutsideCGU

140 (31%)

68 (16%)

125 (29%)

103 (24%)

184 (57%)

73 (22%)

11 (3%)

59 (18%)

436 327

Average help relationships, by function

Faculty

Dep’t staff

Admin. Staff

Supervisors

ACC staff

Relations N

1.44

1.53

1.59

.12

17.6

36

13

32

15

9

0

20

40

Cumulative number of individuals

Numberof help

relations

1 100 200 350

Break point forHigh providers

Cumulative distribution of help relationships

Patterns of help

HighProviders

Non-Providers

HighProviders

Non-Providers ACC

OutsideSources

10%

26%

14%

4%

22%

10%

54%

60%

RECIPIENT

Source

What distinguished a “high provider”?

• A wider range of information work• Use more computer tools• Have more computer education

• Nothing demographic!– Age, status, experience, tenure, and gender are

unrelated to helping

But they do...

Various networks…

• Working relations• Administrative distance• Helping relations• Physical distance

Work Relationships

Help relationships

Help relationships without ACC

Operationalizing “distance”

Art toManagement

= Barrier

Factor of 6

• Working relationships are most important to helping

• More than two physical barriers become a problem to helping

• The formal structure doesn’t matter much in helping

So...What did we find out by correlating the

networks?

Help

Admin. Closeness

Physical closeness

Work help admin. Close.

.60

.14

.28

.17

.21 .08

Conclusions here...

• People get computer help from those with whom they share work problems

• The formal structure is less important than either working relationships or physical distance

• People don’t walk far to get help

Overall Conclusions

• Help networks tend to be workgroup-based,

with central support

• “High providers” focus help networks and

channel expertise into them

• Help providers are just like us, only more so

• Help networks need support and cultivation

Practical consequences

• We reorganized the CGU help system• For the future, we need to…• Understand technology use as a

knowledge management problem• Recognize the knowledge based in

people• Build systems to encourage sharing• Understand limits of formal

arrangements