A knowledge audit refers to a systematic process of identifying knowledge assets and their relationship across an organisation. Acquiring a proprietary knowledge audit methodology is not always economically feasible, especially for smaller organisations. A knowledge auditing methodology focusing on core processes includes the following steps [1]: Stage 1: Acquire Organisational Strategic Information This step aims to identify the organisation's mission, vision, and objectives considering its environment, culture, and traditions. Stage 2: Identify Organisation's Core Processes This step aims to identify which organisational processes contribute most to the organisation's overall success and establish criteria for measuring and ranking processes according to their criticality. Stage 3: Prioritise and Select Organisation's Core Processes Core processes with the highest potential impact on organisational performance are selected as the focus of the audit. This does not mean that other processes are omitted from consideration, but some priority level must be established to maximise the use of limited time and resources. Stage 4: Identify Key People This step aims to identify all the people that play a key role in the core processes identified during the previous step. Stage 5: Meeting with Key People Once identified, the key people are introduced to the concept of the knowledge audit. It is crucial to ensure that they understand the processes and motivations behind the knowledge audit and that they feel supported by management. Stage 6: Obtaining Knowledge Inventory During this crucial stage, the existing knowledge assets within the organisation are identified and captured by engaging with key people through questionnaires and interviews. This process can be repeated for processes of decreasing priority until all knowledge assets have been examined and integrated into an overarching inventory. Stage 7: Analysing Knowledge Flow The questionnaires and interviews utilised during the previous steps should include questions regarding how tacit and explicit knowledge flows through the organisation. As with the previous step, the flows identified initially will relate to the highest priority core processes. This process can be repeated for processes of decreasing priority until all knowledge flows within the organisation have been identified and captured. Stage 8: Knowledge Mapping The objective of this step is to create a visual representation of the organisation's knowledge assets (e.g. who has knowledge, where these persons are located, the level of accessibility to them, with who they most often share and exchange knowledge, etc.). The first iteration of the knowledge assets map will focus on the highest priority core processes. This process can be repeated for processes of decreasing priority until a complete map of the organisation's knowledge is created. Stage 9: Knowledge Audit Reporting After a thorough analysis of the knowledge inventory, knowledge flows, and knowledge map of the first core processes, an audit report is presented to management. The report should describe in detail the major findings of the audit and should include the following: The existing status of knowledge assets within the organisation. The knowledge maps generated during the audit. The current effectiveness of the organisation in achieving its business process objectives. Potential knowledge gaps or threats. Opportunities and recommendations for improving the organisation's use of knowledge assets. The final knowledge report forms a basis for implementing KM initiatives going forward. Stage 10: Continuous Knowledge Re-auditing Once the core processes with the highest priority have been audited, the process is repeated on the remaining core processes until all knowledge assets and flows are identified and captured. The organisation should also periodically re-audit its knowledge assets and update any relevant changes to the knowledge inventory, knowledge flows, and knowledge map. In this way, the organisation can measure the performance of its KM initiatives over time and make adjustments to facilitate continuous improvement. 1. Perez-Soltero, A. et al., 2007. A Model and Methodology to Knowledge Auditing Considering Core Processes. The ICFAI Journal of Knowledge Management, 5(1), pp. 7-23.

The terms knowledge audit and knowledge management audit (KM‐audit) are often used interchangeably. However, the two processes are distinct and serve entirely different purposes. The goal of a KM-audit is to evaluate the impact and effectiveness of ongoing KM practices and processes within an organisation, while a knowledge audit refers to a systematic process of identifying knowledge assets and their relationship across an organisation. Knowledge audits help organisations determine what knowledge they currently have, how they utilise knowledge, and what knowledge they will need in the future. The knowledge audit process consists of the following steps [1]: 1. Identify what knowledge currently exists in the organisation or department: (a) Determine existing and potential knowledge sinks, sources, flows, and constraints, including environmental factors. (b) Identify and locate explicit and tacit knowledge within the organisation or department. (c) Build a knowledge map of the taxonomy and flow of knowledge in the organisation or department. The knowledge map relates topics, people documents, ideas, and links to external resources, in respective densities, in ways that allow individuals to find the knowledge they need quickly. 2. Identify what knowledge is missing in the organisation or department: (a) Perform a gap analysis to determine what knowledge is absent to achieve business objectives. (b) Determine who needs the absent knowledge. 3. Provide recommendations from the knowledge audit to management, regarding possible improvements to the knowledge management activities in the organisation or department. Questions to extract the information needed to identify what knowledge currently exists in a targeted area include [1]: 1. List specifically the categories of knowledge you need to do your job. 2. Which categories of knowledge listed in question 1 are currently available to you? For each category of knowledge you specified in question 1 . . . 3. How do you use this knowledge? Please list specific examples. 4. From how many sources can you obtain the knowledge? Which sources do you use? Why? 5. Besides yourself, who else might need this knowledge? 6. How often would you and others cited in question 5 use this knowledge? 7. Who are potential users of this knowledge who may not be getting the knowledge now? 8. What are the key processes that you use to obtain this knowledge? 9. How do you use this knowledge to produce a value added benefit to your organisation? 10. What are the environmental/external influences impacting this knowledge? 11. What would help you identify, use or transform this knowledge more effectively? 12. Which parts of this knowledge do you consider to be (a) in excess/abundance, (b) sparse and (c) ancient/old/outlived its useful life? 13. How is knowledge currently being delivered? What would be a more effective method for delivering knowledge? 14. Who are the ‘experts’ in your organisation housing the types of knowledge that you need? 15. In what form is the knowledge that you have gained from the experts? 16. What are the key documents and external resources that you use or would need to make your job easier? 17. What are the types of knowledge that you will need as a daily part of your job (a) in the short term (1–2 years) and (b) in the long term (3–5 years)? By identifying the knowledge assets that contribute to core processes, an organisation can focus its KM efforts on knowledge assets at various levels of criticality rather than managing everything regardless of its significance. 1. Liebowitz, J. et al., 2000. The Knowledge Audit. Knowledge and Process Management, 7(1), pp. 3-10.

Knowledge production and management are inherently human-centered. Therefore, the most effective roles assigned to generative AI in KM will mostly augment humans rather than replace them. Generative AI cannot make something from nothing – it is trained on existing data and information. Thereby achieving collaborative intelligence, in which generative AI and humans enhance the complementary strengths. Generative artificial intelligence (AI) is artificial intelligence capable of generating text, images, or other media, using generative models e.g. OpenAI’s DALL-E 2 (text-to-image model). We know already that: AI will impact knowledge work, knowledge management and streamlining work, however the pace of the change has critical implications Fast-paced creation of content (in our already information-overloaded workplaces) Generative AI is trained on large corpuses of information, which encode the biases of that material Impact our skills, from generating text to being a good editor, deciding what to keep and what needs to change (e.g. fact-checking AI generated text and spotting visual flaws) Knowledge is at the core of innovation, and enhancing KM practices help accelerate the flow of ideas and collaboration. However, organisations struggle with the time and effort required to capture and maintain knowledge to create a thriving KM practice, drive employee productivity and ensure people can find organisational knowledge. Therefore, moving KM toward agility helps driving its success! Agile in the KM context means rapid implementation and results, being adaptive to culture, context, and the business environment, and focused on changing knowledge sharing mindsets and behaviours.

EVENTS KMSA Event Schedule 2024 Upcoming Events In 2024 we will be hosting: Monthly Webinars which will be open to members and non-members of the Association Monthly Practitioner Development Masterclasses will be open to KMSA members only. Past Events 16 - 21 October - KM Week 19 September - Panel Discussion - Panel Discussion: Collaboration: Applying and adapting a KM practitioner’s toolkit in a hybrid KM future 21 & 22 August - Imbizo - "The future of Knowledge Management is hybrid " 11 July - Webinar - "Data rich, but knowledge poor” - Speaker: Charl Theron June - Webinar - AI, ML, cloud are not traditionally part of the KM practitioners toolkit – key considerations. 30 May - Panel Discussion - Reporting line of a KM function for optimal success: cases and use cases, different models. March - Webinar - The metaverse and implications for KM and practitioner Need more details? Contact us We are here to assist. Contact us by phone, email or via our social media channels. Contact Us

CALL FOR ACADEMIC PAPERS AND PRACTITIONER / INDUSTRY PRESENTATIONS KMSA Imbizo 2024: 21 – 23 August Theme: Championing a knowledge-sharing culture Submit your Proposal Championing a knowledge-sharing culture involves creating an environment where individuals and teams actively share information, expertise, and insights to drive learning and innovation. A knowledge-sharing culture is paramount in today's dynamic business landscape, aligning closely with several pivotal themes. The growing role of social collaboration is amplified when organisations prioritise a culture that encourages open dialogue and the exchange of insights. By fostering an environment where team members freely share their expertise and experiences, companies elevate their human experience (HX) management. Employees feel empowered and engaged, contributing to a positive workplace environment. Furthermore, a knowledge-sharing culture not only improves knowledge management metrics and measurement capabilities, and showcases the tangible value of knowledge sharing, but it also seamlessly integrates with business processes, enhancing overall efficiency and effectiveness. Moreover, a knowledge-sharing culture facilitates personalisation, tailoring solutions and approaches to individual needs and preferences, ultimately driving innovation and growth within the organisation. We look forward to receiving your proposals and your shared insights on the exciting future of knowledge management. We would like to ensure that as many people as possible are able to take part in the conference in 2024. Therefore, you will be able to engage in: · The practice track : where you can present, or learn about, practical experience and case studies. · The research track : where we will uncover completed but not yet published research papers based on the potential topic areas. POTENTIAL TOPIC AREAS Championing a knowledge-sharing culture in: Culture Building a knowledge-sharing culture - strategies and best practices. The power of collective wisdom: fostering knowledge sharing in teams. Embedding knowledge sharing in organisational culture - case studies and success stories . Instilling a mindset that values knowledge as an asset to be shared, for mutual benefit. Knowledge exchange Integrating knowledge sharing as a fundamental component of day-to-day business operations. Cultivating a learning organisation by encouraging continuous knowledge exchange. Supporting initiatives that encourage cross-functional collaboration and information flow. Enabling a structured approach to capturing, organising, and distributing organisational knowledge. Overcoming barriers to knowledge sharing and collaboration. Nurturing a sense of community and interconnectedness by promoting knowledge sharing. Technology Leveraging technology for effective knowledge sharing within your organisation. Emphasising the ethical and responsible sharing of information for the greater good. Generative AI - merging human and artificial intelligence. Strategy Incentivising knowledge sharing - rewards, recognition, and motivation strategies. Creating platforms and spaces that facilitate easy access to shared knowledge resources. Measurement Aligning organisational values with the importance of sharing knowledge for collective success. Measuring the impact of knowledge sharing on organisational performance. Workforce Creating a knowledge-sharing ecosystem - from leadership to frontline employees. Engaging remote and hybrid teams in knowledge sharing - virtual strategies. Fostering a collaborative environment that thrives on shared insights and expertise. Establishing mentorship programs that promote the transfer of knowledge and skills within the organisation. Note: this is not an exhaustive list. SUBMIT YOUR PROPOSAL Presentations: Please submit your presentation proposal title and abstract (about 400 words) by clicking here . If you have any enquiries or want to discuss and scope your proposal, kindly email Eileen Bayley eileen@vdw.co.za . Research: All submissions must be unpublished and not be under review elsewhere. All research submissions will go through a double-blind review process. Your submission will be assessed anonymously by at least two reviewers and managed by the academic program committee. Full paper submissions must be at most 15 pages. Proceedings with all accepted full papers will be available online on the KMSA website. A selection of accepted full papers will appear in a special issue of the South African Computer Journal (SACJ ). Please ensure that your full paper adheres to the required SACJ format and submit the pdf version for review in EasyChair. Important Dates · Deadline for full research paper submissions: 18 April 2024 · Notification of full research paper acceptances: 31 May 2024 · Camera-ready paper submissions: 16 June 2024 · KMSA Imbizo 2024: 21 – 23 August 2024 If you have any enquiries or want to discuss and scope your proposal, kindly email Hanlie Smuts hanlie.smuts@up.ac.za

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