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

1. Help as Knowledge Management:Taking Care of Scarce Resources through Informal Encouragement JD Eveland, Ph.D. December 11, 2000

2. 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”

3. 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

4. “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

5. 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

6. 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

7. 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

8. Connections in the network Help network Work network Within Work group 140 (31%) 184 (57%) Across Work groups 73 (22%) 68 (16%) With ACC 11 (3%) 125 (29%) Outside CGU 103 (24%) 59 (18%) 436 327

9. Average help relationships, by function Relations N 1.44 36 Faculty 1.53 13 Dep’t staff 1.59 32 Admin. Staff .12 15 Supervisors 17.6 9 ACC staff

10. Cumulative distribution of help relationships Break point for High providers Number of help relations 1 100 200 350 Cumulative number of individuals

11. Patterns of help Source Outside Sources High Providers Non- Providers ACC R E C I P I E N T High Providers 10% 14% 22% 54% Non- Providers 26% 4% 10% 60%

12. 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...

13. Various networks… • Working relations • Administrative distance • Helping relations • Physical distance

14. Work Relationships

15. Help relationships

16. Help relationships without ACC

17. Operationalizing “distance” Art to Management = Barrier Factor of 6

18. So...What did we find out by correlating the networks? • 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 Help Admin. Closeness Physical closeness .60 .14 .17 .21 .28 .08 Work help admin. Close.

19. 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

20. 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

21. 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