1. By Ali Alkhuraiji, PhD student Supervisors Prof Shaofeng Liu, Dr Fenio Annansingh, Plymouth University. Knowledge Network Modelling (KNM)to Support Decision Making For Strategic Intervention In IT Project-Oriented Change Management.

2. Presentation outline

3. To address the issues through the investigation of knowledge network modelling (KMM)in supporting work performance (WP) and decision making (DM) for strategic intervention in IT project- oriented change management (ChM). Objectives 1- To understand the state of art in KMM to support DM in ChM 2- To identify Key issues and key challenges 3- To investigate Knowledge mobilisation (KMM) channel through WP and DM. 4- To develop a conceptual framework model 5- To validate the proposed model in practical setting 6- To draw up a multifaceted set of recommendations Research Context

4. Research Questions 1- What are the key issues of change strategies that have an impact on leading multiple IT change projects? 2- To what extent KM mobilisation (KMM) can have an influence on the change throughout projects? 3- What are the most influential factors affecting KM networks within the process of change? 4- How can organisations learn from previous change projects?

5. Issues : Lack of 1- Top management support in identifying KM channel in ChM process. 2- Project documentation & lack of procedural knowledge in ChM. 3- Coordination among parties. 4- Employees involvement in KMM &ChM.. Issues : Lack of 1- Top management support in identifying KM channel in ChM process. 2- Project documentation & lack of procedural knowledge in ChM. 3- Coordination among parties. 4- Employees involvement in KMM &ChM.. Challenges : How to address 1- the interoperability, issues, coordination, cooperation and authority of regulation to support DS. 2- The issues of understanding of the full scope of continuous effort required for the success of the projects in DS process. 3- Issues of aligning the key factors of project oriented for long term strategic vision. Challenges : How to address 1- the interoperability, issues, coordination, cooperation and authority of regulation to support DS. 2- The issues of understanding of the full scope of continuous effort required for the success of the projects in DS process. 3- Issues of aligning the key factors of project oriented for long term strategic vision. Key issues & challenges

6.  Knowledge Management (KM)  Change Management (ChM)  IT impact on ChM  Post-research Limitations Literature Review

7. Knowledge What is knowledge? Knowledge is defined as “justified true belief” and also “a dynamic human process of justifying personal belief towards the truth” (Nonaka & Takeuchi 1995, p.58). What is knowledge? Knowledge is defined as “justified true belief” and also “a dynamic human process of justifying personal belief towards the truth” (Nonaka & Takeuchi 1995, p.58). How do we differ knowledge from information and data?

8.  What is Knowledge management then?  Where is it?  Why do we need it? Knowledge Management  Knowledge management VS Information management  History  Similarities  Differences  Knowledge can be in two most popular forms  Tacit  Explicit

9. Change Management is alerted  Types and cases of change radical partial  strategies used through the history planned change models and theory Incremental Theory emergent theories.

10.  One of the change’s main driver  The significant growth  Fundamental role towards work performance and decision making What has been shifted towards managing IT project from change management perspective?  A new approach for managing by project (Project Oriented PO)  This needs:  A strong project management culture  Reconsidering issues of policy and structure in ChM  Decision making strategy  Function integration  Solving knowledge assets issues  One of the change’s main driver  The significant growth  Fundamental role towards work performance and decision making What has been shifted towards managing IT project from change management perspective?  A new approach for managing by project (Project Oriented PO)  This needs:  A strong project management culture  Reconsidering issues of policy and structure in ChM  Decision making strategy  Function integration  Solving knowledge assets issues IT impact on ChM

11.  Insufficiency of addressing underpinning issues of KM in PO.  Recent studies has taken the approach of ChM Life-cycle development.  Shortages of addressing the issue of tracing Knowledge channel.  lack of identifying KM structural networks key elements (Nodes)  Absence of addressing on-going IT projects issues.  Insufficiency of addressing underpinning issues of KM in PO.  Recent studies has taken the approach of ChM Life-cycle development.  Shortages of addressing the issue of tracing Knowledge channel.  lack of identifying KM structural networks key elements (Nodes)  Absence of addressing on-going IT projects issues. Post-research Limitations

12.  The following three slides will highlight three areas:  First Graph: An integration between KM and ChM terms at broad level.  Extracting the factors that highly possibly play role in KMM in IT PO.  Second graph: shows underpinning issues in KM channel based on SECI 1995 Model.  Third graph: A Framework to Support DS in ChM Conceptual Framework

13. Knowledge Management (KM) Change Management (CH) KM Strategies KM Life Cycle, Lee & Hong (2002) KM Certificates Systems, tools Change Strategies Project Management Change Agent Activities Focused of change Capacity of change Process & Models Traditional Management Managing by project IT project KM Mobilisation Community of practice. Knowledge transfer process and models. Systems (websites, social networks, software, email. Projects orientation. People. Organisational structure. Organisational capacity. Organisational Strategy. Knowledge mapping. Leveraging intellectual assets. Tasks and decision. Culture. Process. Support Decision Making and work performance Right People Right format (systems, software) Knowledge Transfer Right Information

14. Nonaka &Takeuchi SECI Model 1995 Nonaka &Takeuchi SECI Model 1995 Socialisation Tacit to Tacit Socialisation Tacit to Tacit Internalisation Explicit to Tacit Internalisation Explicit to Tacit Combination Explicit to Explicit Combination Explicit to Explicit Externalisation Tacit to Explicit Externalisation Tacit to Explicit Knowledge Networks of interactions Knowledge Transfer Knowledge networks of interpretation and translations Right Format (systems, database) Institutional Knowledge networks (knowledge base) Powerful Knowledge and information Knowledge Networks of influence Right People

15. Change Management Knowledge Management Mobilisation IT-Project Oriented Change Management Enhancing Decision Support system and work performance Integration of the two approaches Framework of Knowledge network modelling to support decisionmaking and work performance for strategic intervention in ITproject-oriented change management Correlation of the Core competences linked to the four factors Alignment needed between the four keys areas identified Knowledge Mobilization Organisational culture (Trust, accceptance, community of practice, collaborations, incentives, rewards, typologies, behaviours and leadership) Organisational capacity (Readiness, Capability, Resources ) Organisational strategy (process and Models) Strategic orientation, Structure, politics and process "policy") managing by projects Knowledge Infrastructure Knowledge base (project portfolio, project categorisation, networks, knowledge sharing tools and techniques,IT project evaluation Change agents, Human resource management is the key in aligning project team within the four areas and creating intra & external- organisational knowledge networks

16.  Graphs shows how the research methodology is structured.  The selected case study details. Research Methodology & Case Study overview

17. Hybrid Research Methodology Qualitative Approach Quantitative Approach Multiple Case Studies (Yin, 2009) Data Collection Method Unstructured & Semi-structured interviews Document review Thematic data Analysis Social networks Analysis Document Analysis Thematic data Analysis Social networks Analysis Document Analysis Data Analysis Method

18. Case Study Details  Background.  Criteria to select the targeted sample  Interviews participants

19.  To establish new “practical” insight into Knowledge Management mobilisation (KMM)  To add a new knowledge layers of “know who” in addition to the already existing layers of “know how”, “Know what”, “know why” and “know with”  To identify the key issues of KMM in IT projects change focused that have an impact on DS.  To determine key factors of KMM in project oriented change management for structural knowledge network  To develop Change Management Knowledge Network Model (CMKNM) that provides traceability and connection of procedural knowledge to “lessons learned” and can be used by practitioners to improve their strategic DS in the plan and the management of change.  To establish new “practical” insight into Knowledge Management mobilisation (KMM)  To add a new knowledge layers of “know who” in addition to the already existing layers of “know how”, “Know what”, “know why” and “know with”  To identify the key issues of KMM in IT projects change focused that have an impact on DS.  To determine key factors of KMM in project oriented change management for structural knowledge network  To develop Change Management Knowledge Network Model (CMKNM) that provides traceability and connection of procedural knowledge to “lessons learned” and can be used by practitioners to improve their strategic DS in the plan and the management of change. Key Contributions

20.  The literature review shows KM and ChM concepts are widely described as interwoven. Organisations that fail to address ChM issues underpin KM issues (e.g. KMM), are highly likely to consider KM as complementary concept, hence ignoring its value. KM has been perceived to be the key power of change project success.  Conceptual framework  Research methodology including research approach, strategy, data collection technique and data analysis technique.  Contributions in aspect of KMM, Know how and CMKNM Conclusions