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Re-Examining the Jennex Olfman
Knowledge Management Success
Model
Murray E. Jennex, Ph.D., P.E., CISSP, CSSLP, PMP
Profess...
About Me
• Full professor with 17 years experience at San Diego
State University
• Spent 20 years prior in the commercial ...
Introduction
• The Jennex Olfman KM Success Model was
presented in its initial form in 1998 as a OM
Success Model
– Based ...
Jennex Olfman KM Success Model 2006
9/17/2017 Copyright Foundation for Knowledge Management
Some Facts on the Model
• Per Google Scholar, articles presenting the model have been cited
over 1100 times.
• Model used ...
Motivation
• Finding a weakness in the system quality
dimension spurred thought on technology
changes
• Since 2006 much re...
Jennex Revised Knowledge Pyramid
Forthcoming November, 2017, Data Base
9/17/2017 Copyright Foundation for Knowledge Manage...
Re-Specified Model
Technological
Infrastructure
KM Level
User Satisfaction
KM Form
Intent to Use/
Perceived Benefit
Extrin...
Some Observations
• KM Vision part of leadership
• Entrepreneurship, Creativity, Innovation need
special constructs? A que...
Some Observations
• Technical Infrastructure has cloud, social media,
mobile, agents, AI, Analytics, IoT Instagram, voice
...
Conclusions/Future Work
• Biggest changes are:
– KM strategy and Knowledge content process being split
– Adding KM governa...
Measuring KM Success
• We have many models saying what is necessary
to be successful with KM
– Have identified a number of...
Copyright Foundation for Knowledge Management
Research Design
9/17/2017
Copyright Foundation for Knowledge Management
Research Design
• Survey was generated to test the definition
– Items for KM...
Research Design
• Data was analyzed by performing Principle
Factor Analysis to see if items measured
their dimension and i...
Results: Respondent Demographics
Respondents by Position, nearly
a 50/50 split between academia
and practitioners, all wit...
Factor Loadings
Extraction method is principle
component analysis with varimax
rotation and Kaiser normalization,
blanks r...
Chronbach Alphas
9/17/2017 Copyright Foundation for Knowledge Management
Note that a reliability coefficient of .70 or hig...
Regression Results
9/17/2017 Copyright Foundation for Knowledge Management
Final Measures
• Business Process Impact
– improved the efficiency of the
supported processes.
– reduced costs for the sup...
Conclusions
• Good set of 17 measures
– Good internal consistency
– High reliability
– Reasonable fit
• KM Success can be ...
Questions?
9/17/2017 Copyright Foundation for Knowledge Management
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Re-examining the Jennex Olfman KM Success Model

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Presentation by Murray Jennex to the SIKM Leaders Community on September 19, 2017

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Re-examining the Jennex Olfman KM Success Model

  1. 1. Re-Examining the Jennex Olfman Knowledge Management Success Model Murray E. Jennex, Ph.D., P.E., CISSP, CSSLP, PMP Professor, MIS, Fowler College of Business San Diego State University 9/17/2017 Copyright Foundation for Knowledge Management
  2. 2. About Me • Full professor with 17 years experience at San Diego State University • Spent 20 years prior in the commercial nuclear industry as an engineer, project manager, manager • Founding and current Editor in Chief International Journal of Knowledge Management (in its 13th year) • Founding and current co-Editor in Chief International Journal of Information Systems for Crisis Response and Management • Founding and current co-Track Chair of the Knowledge, Innovation, and Entrepreneurial Systems Track at the Hawaii Conference on Systems Sciences (in its 13th year with 12 years previous experience as a minitrack) 9/17/2017 Copyright Foundation for Knowledge Management
  3. 3. Introduction • The Jennex Olfman KM Success Model was presented in its initial form in 1998 as a OM Success Model – Based on DeLone and McLean IS Success Model – Developed from an in depth, longitudinal case study of OM and knowledge use in a nuclear power plant engineering division • Evolved through discussions/presentations at the Hawaii International Conference on System Sciences, HICSS, in 2002 and 2004 and the DeLone and McLean 10 year revised model • Published in the International Journal of Knowledge Management in 2006 9/17/2017 Copyright Foundation for Knowledge Management
  4. 4. Jennex Olfman KM Success Model 2006 9/17/2017 Copyright Foundation for Knowledge Management
  5. 5. Some Facts on the Model • Per Google Scholar, articles presenting the model have been cited over 1100 times. • Model used to guide design of KM systems/initiatives, assess KM systems/initiatives, and to help determine readiness of an organization to do KM. A review of the first ten pages of citations from Google Scholar found: – 58 of the citations used the model to assess KM success/effectiveness, – 29 citations used the model to help guide design of KM systems/initiatives, – 11 citations used the model to help assess organizational readiness to adopt KM systems/initiatives • Kundapur and Rodrigues (2017) used PLS-SEM to validate the original 2006 model. – model was validated, – there were weaknesses, especially in the system quality dimension. 9/17/2017 Copyright Foundation for Knowledge Management
  6. 6. Motivation • Finding a weakness in the system quality dimension spurred thought on technology changes • Since 2006 much research and innovation has occurred that has spurred my interest in seeing if it is time to re-specify the model – Technology advancement: Cloud, mobile, Big Data, IoT, AI, social media – Process research: KM success measurement, KM governance, KM security, knowledge pyramid – New methods: analytics, business intelligence 9/17/2017 Copyright Foundation for Knowledge Management
  7. 7. Jennex Revised Knowledge Pyramid Forthcoming November, 2017, Data Base 9/17/2017 Copyright Foundation for Knowledge Management
  8. 8. Re-Specified Model Technological Infrastructure KM Level User Satisfaction KM Form Intent to Use/ Perceived Benefit Extrinsic Motivation System Quality Knowledge Quality Richness Linkages Net Benefits Leadership KM Strategy KM Content Process Impact Service Quality KM Strategy KM Governance Leadership/ Management Support Knowledge Content Process Human Infrastructure Interface 9/17/2017 Copyright Foundation for Knowledge Management
  9. 9. Some Observations • KM Vision part of leadership • Entrepreneurship, Creativity, Innovation need special constructs? A question to be answered • Paper document use is there but difficult to see • Trust part of governance/leadership and in accuracy and completeness in knowledge repository • Knowledge economics part of service quality and impacts • Curation is in knowledge content process and knowledge quality • KPI’s needed for all constructs and to be developed 9/17/2017 Copyright Foundation for Knowledge Management
  10. 10. Some Observations • Technical Infrastructure has cloud, social media, mobile, agents, AI, Analytics, IoT Instagram, voice recognition, wearables • Human Infrastructure focuses on capabilities, skills, training, etc. • Form moving to more digital but also moving from structured to unstructured, plus maybe IoT, ADS, video, audio • Level adding more than just mnemonic functions – tagging/search, analytics, text and data mining, sentiment analysis • Interface is about linking human/system interaction and could include AR, mobile displays, heads up displays, voice recognition, etc. 9/17/2017 Copyright Foundation for Knowledge Management
  11. 11. Conclusions/Future Work • Biggest changes are: – KM strategy and Knowledge content process being split – Adding KM governance and KM success measurement – Adding Human Infrastructure and Interface to Technology and expanding Technical Infrastructure, Form, and Level • Flexible for adding new technologies, processes • Future work: – Full literature review to confirm/modify new model – Create/adapt instruments to measure new constructs – Administer and analyze survey – Create final, validated model 9/17/2017 Copyright Foundation for Knowledge Management
  12. 12. Measuring KM Success • We have many models saying what is necessary to be successful with KM – Have identified a number of CSFs – Have identified a number of barriers to success • We have no tested model to show what are indicators of success – Have many case studies that show how that particular organization measured success – We know there needs to be impacts and use • This study proposes a set of success measures 9/17/2017 Copyright Foundation for Knowledge Management
  13. 13. Copyright Foundation for Knowledge Management Research Design 9/17/2017
  14. 14. Copyright Foundation for Knowledge Management Research Design • Survey was generated to test the definition – Items for KM success as well as the four dimensions were generated using the literature – Used a 7 point Likert scale – Survey was tested using an expert panel with some adjustments made • Survey was administered using surveymonkey – KM discussion forums (SIKM, ActKM), KM academic lists, and personal contacts were sent emails soliciting participation – Two follow up emails were sent to encourage participation – Data was collected for 3 months 9/17/2017
  15. 15. Research Design • Data was analyzed by performing Principle Factor Analysis to see if items measured their dimension and if all items were necessary – SPSS was used to run on 96 usable responses (out of approximately 150 responses received) – 25 items were reduced to 20 items • Linear regression was done to ensure items reflected KM success 9/17/2017 Copyright Foundation for Knowledge Management
  16. 16. Results: Respondent Demographics Respondents by Position, nearly a 50/50 split between academia and practitioners, all with knowledge of a particular KM project Respondents experience level 60% with over 6 years experience 9/17/2017 Copyright Foundation for Knowledge Management
  17. 17. Factor Loadings Extraction method is principle component analysis with varimax rotation and Kaiser normalization, blanks represent loadings < 0.5 9/17/2017 Copyright Foundation for Knowledge Management
  18. 18. Chronbach Alphas 9/17/2017 Copyright Foundation for Knowledge Management Note that a reliability coefficient of .70 or higher is considered “acceptable” in most social science research situations.
  19. 19. Regression Results 9/17/2017 Copyright Foundation for Knowledge Management
  20. 20. Final Measures • Business Process Impact – improved the efficiency of the supported processes. – reduced costs for the supported business process. – positive return on investment for the supported processes. – improved the effectiveness of the supported processes. – improved decision making in the supported processes. – improved resource allocation in the supported process. • Knowledge Content – increased use or intention to use of knowledge content. – increased identification of needed knowledge content and knowledge content sources.. – increased demand and/or searching for knowledge content. • Leadership – increased verbal/political support for KM by top management. – increased financial support for KM by top management. – increased awareness of KM by top management. – increased use/reliance on KM by top management. • KM Strategy Impact – changes to my organization’s KM goals. – creation or modification of knowledge related key performance indicators. – changes to the way my organization assessed knowledge use in the organization. – changes in my organization’s incentives for using and sharing knowledge. 9/17/2017 Copyright Foundation for Knowledge Management
  21. 21. Conclusions • Good set of 17 measures – Good internal consistency – High reliability – Reasonable fit • KM Success can be objectively measured (i.e. Numbers can be used) • May be more measures • Link measures to KPIs to measure success • Link stories of success to measures when expressing a value statement 9/17/2017 Copyright Foundation for Knowledge Management
  22. 22. Questions? 9/17/2017 Copyright Foundation for Knowledge Management

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