A new foundation workshop from Catalynk
Dr Peter Mellalieu
Discover how Organizational Network Analysis and Collaborative Health insights provide a practical, ethical foundation for Knowledge-Centered Success (KCS) and Intelligent Swarming adoption. Explore how you can see real collaboration patterns, select the right coaches and change agents, and grow organisation-wide knowledge capability.
In many organisations, the story of knowledge management is still a familiar one. Years of effort building repositories, introducing new tools, and running ‘lessons learned’ sessions. Yet front-line staff still ask, ‘Who do I go to when I am stuck?’ rather than, ‘Where can I find what we already know?’
At the same time, service and support environments are changing quickly. Intelligent Swarming℠ challenges traditional tiered support models by routing work dynamically to the best available expertise. Knowledge-Centered Success (KCS®) embeds knowledge capture and reuse into every interaction. Both frameworks assume something that is often left implicit: that the underlying collaboration network is healthy enough to carry the change.
Catalynk’s new workshop, ‘Using Collaboration Insights to Accelerate KCS and Intelligent Swarming Adoption’, is designed for organisations that want to make that assumption explicit, and test that assumption with data.
Why collaboration insights now?
Classic strategy writers such as Prahalad and Hamel described core competence as a form of collective learning that competitors find hard to copy. Senge, writing on learning organisations, argued that the only sustainable advantage is the ability to learn faster than competitors. In practice, this ‘learning faster’ depends on how effectively people connect, share, and apply knowledge in the flow of work.
Several trends make the health of those connections more critical than ever:
- Complex products and services generate more knowledge-intensive interactions in sales, onboarding, support and internal enablement.
- Agile and digital operating models shorten feedback cycles and expose knowledge gaps quickly.
- AI and automation reduce routine work, leaving a higher proportion of complex, collaborative problem-solving.
Given these trends, trust, access to expertise and psychological safety matter greatly.
Knowledge management, in this context, is not only about content and tools. It is about networks of interaction and influence. Who gets asked for help, who is trusted, which teams bridge silos, and where is collaboration fragile.
From KCS and Intelligent Swarming to a knowledge management core competence
KCS and Intelligent Swarming provide robust, field-tested frameworks for improving support performance. The KCS v6 Practices and Adoption & Transformation Guides show how embedding knowledge creation and reuse into support interactions can reduce time to resolve, improve self-service and increase customer satisfaction. The Intelligent Swarming Practices Guide describes how connecting people to people for new issues, rather than escalating through tiers, improves resolution speed and skills development in complex environments.
Catalynk’s experience suggests that a narrow and strong competence in service, through KCS and Intelligent Swarming (IS), becomes a stepping stone to an organisation-wide knowledge management competitive core competence, illustrated in Figure 1.
In KCS/IS adoption projects, organisations learn how to:
- Embed knowledge capture and reuse into daily work
- Develop and support coaching capability for knowledge practices
- Align metrics and incentives with learning and collaboration
- Use network-aware analytics to inform change and talent decisions
Once those capabilities are working reliably in service functions, they can be adapted to domains such as product development, risk and compliance, or sales enablement.
Figure 1. How disciplined knowledge in support grows into competitive competence
Our proposition, that KCS / Intelligent Swarming competence is a productive baseline for wider knowledge management capability, is an experience-based proposition drawn from Catalynk’s consulting work. Our proposition is consistent with the patterns reported in the KCS adoption literature and case studies.
What collaboration insights reveal: ONA + Collaborative Health + Qualitative analysis
In practice, KCS and Intelligent Swarming succeed or stall depending on the underlying social system. The Consortium for Service Innovation highlights collaboration, trust, role clarity and team learning as conditions for successful adoption. Those conditions are not visible in an organization chart.
Here is where Organizational Network Analysis (ONA) and Collaborative Health Analysis (CHA) become powerful:
- ONA makes visible who goes to whom for help with processes, policies, technical issues and innovation; who connects teams; and where collaboration bottlenecks or overload points exist.
- Collaborative Health Analysis uses a short survey to assess perceptions of trust, conflict, structure, commitment, accountability, results and psychological safety across teams and regions.
- Qualitative analysis of free-text responses surfaces the perceived drivers and barriers to better knowledge practices, in participants’ own words.
In the Polinode article ‘Using Organizational Network Analysis to Help Drive Knowledge-Centered Service Adoption’, I explain how ONA is used to identify potential KCS coach candidates by analysing who colleagues turn to for help with processes, policies and innovation. Catalynk’s method calculates a candidate merit score based on weighted ONA metrics, then presents managers with a data-informed pool of candidates rather than a single ‘winner’.
The same analytic spine can be extended:
- To find change advocates (influencers) who are central in communication and collaboration networks.
- To diagnose drivers and barriers to improved Knowledge Management. For example, strong willingness to share but low confidence in existing knowledge base quality.
- To establish a baseline collaboration health score against which future change waves can be assessed.
Figure 2 illustrates one aspect of Catalynk’s integrated approach to revealing collaboration insights. The larger nodes in the sociogram reflect survey respondents who regard the organization’s Collaborative Health most highly, a composite index including measures of trust, conflict, structure, commitment and psychological safety.
Secondly, the triangle-shaped nodes signal those respondents identified through ONA as being ‘influencers’. Technically, these people are highly connected directly and near-directly to other members of the organization: they have widespread ‘reach’ (Zak & Zbieg, 2014).
The labelled nodes represent the selection of those people who are BOTH strong influencers AND rate the organization’s Collaboration Health highly. These are strong candidates to undertake the role of change advocates accelerating the knowledge management journey.
Finally, the node color represents informal communities of communication within the organization. These communities do not necessarily match the formal divisions of the organization. Note how two communities are weakly connected with the organization as a whole, top left, and middle left. In contrast, the rest of the organization possesses communities that have highly interconnected communication networks. There are multiple connections both within and between the communities. This phenomenon suggests the likelihood of highly collaborative cross-organizational problem solving. Do you see the community where most members rate their perception of Collaboration Health the weakest in the organisation?
Figure 2. Catalynk’s integrated approach to presenting collaboration insights.
Ethics, privacy and misuse of data
There is also an ethical dimension. Network data can be sensitive. It touches on trust, influence, and sometimes performance perceptions. Recent work on people analytics has highlighted both the opportunities and the risks, including privacy concerns and possible misuse of data. The workshop, therefore, treats ethics and governance as central, not peripheral.
Collaboration insights support each phase of the knowledge journey
Figure 3 extends Figure 1, by illustrating the location and sequence of collaboration insights in support of your knowledge journey. The figure emphasises the importance of a baseline ONA+CHA analysis as the foundation for developing the knowledge management change management plan, and the selection of influencers and KCS / IS coaches.
Figure 3. How collaboration insights accelerate knowledge adoption
Inside the workshop
The workshop is designed as a stand-alone introduction to ONA+CHA for organisations early in their knowledge management or KCS / IS journey, and as a deeper collaboration-insights module for existing Catalynk clients.
Format
- Two live, instructor-led sessions of three hours each
- Sessions separated by one day to one week, with light homework in between
- Delivery via Zoom or in-house, using Polinode, Catalynk templates and anonymised case material
Who it is for
- Knowledge management, KCS and Intelligent Swarming sponsors and program managers
- Support and operations leaders (customer support, success, service desk, internal services)
- Change managers, HR and people analytics professionals
- Internal and external consultants or analysts supporting KCS, IS or broader KM initiatives
What you will do
Participants will:
- Complete a short ONA+CHA survey, experience it as a respondent, and see an aggregated view of the cohort’s collaboration network.
- Explore real sociograms, metrics and candidate merit heatmaps from Catalynk’s KCS coach selection work, using Polinode.
- Draft their own survey and communication plan for a small, realistic ONA+CHA engagement aligned with their KCS, IS or KM goals.
- Work through a Governance Canvas to address privacy, consent, data use, and retention.
- Produce a one-page project plan for their first collaboration-insights initiative, using an eight-phase ONA cycle aligned to the KCS v6 Adoption & Transformation Guide and the Intelligent Swarming Practices Guide.
Some participants will leave ready to run small-scale ONA+CHA projects with light support. Others may choose a more deliberate capacity-building pathway, partnering with Catalynk for additional coaching or action-learning engagements.
Why Catalynk?
Several elements distinguish Catalynk’s approach:
- Deep alignment with KCS and Intelligent Swarming
The workshop is grounded in the KCS v6 Practices and Adoption & Transformation Guides and the Intelligent Swarming Practices Guide. It is designed to complement – not duplicate – KCS and IS training, by adding the collaboration-insights layer underneath. - Integrated ONA+CHA+qualitative methodology
Catalynk’s baseline survey combines ONA, collaborative health and qualitative questions in a single instrument, with a well-tested analysis and reporting workflow. - Polinode expertise
Catalynk has developed and demonstrated this approach using the Polinode platform for ONA, as documented in the Polinode blog and associated case materials. - Attention to ethics and governance
The design draws on emerging guidance about the ethics of network and people analytics – an area where the literature warns against naive deployment.
Getting started
This workshop is intentionally practical. It does not attempt to turn leaders into network scientists. Instead, it aims to:
- Give decision-makers confidence to ask the right questions of ONA+CHA projects
- Help teams align collaboration insights with their KCS and Intelligent Swarming roadmaps
- Lay a data-informed baseline for growing an organisation-wide knowledge management core competence
For organisations that sense their collaboration patterns are both an asset and a constraint and that want to progress beyond tool-focused Knowledge Management, Catalynk’s approach to identifying collaboration insights may be a timely next step.
To explore how this workshop could support your KCS, Intelligent Swarming or broader Knowledge Management journey, Catalynk can discuss public virtual cohorts or dedicated in-house sessions.
Get started now – talk one of our Catalynk KCS specialists
About the Author
Peter is a Knowledge Engineer at Catalynk. He works with clients to drive their knowledge management and collaborative problem-solving programs using tools from network science, organization development, and operations research. Prior to joining Catalynk, Peter held roles in biosystems engineering, software development, and innovation strategy, including scientific and academic positions in the USA, United Kingdom, Botswana, Belgium and New Zealand.
References
Consortium for Service Innovation. (2016–2023). KCS v6 Practices Guide and KCS v6 Adoption & Transformation Guide. Consortium for Service Innovation.
Consortium for Service Innovation. (2022). Intelligent Swarming Practices Guide and related web resources. Consortium for Service Innovation.
Cronin, B., Ryan, P., & Coughlan, J. (2020). Ethical implications of network data in business and management settings. Social Networks, 62, 104–112.
Mellalieu, P. J. (2024, November 12). Using Organizational Network Analysis to Help Drive Knowledge-Centered Service Adoption. Polinode.
Mellalieu, P. J. (2025). Using Collaboration Insights to Accelerate KCS and Intelligent Swarming Adoption: Workshop syllabus (Version 4.0). Catalynk Ltd.
Prahalad, C. K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79–91.
Senge, P. M. (1990). The fifth discipline: The art and practice of the learning organization. Doubleday.
Serrat, O. (2017). Knowledge solutions: Tools, methods, and approaches to drive organizational performance. Springer / Asian Development Bank.
Tursunbayeva, A., Pagliari, C., Di Lauro, S., & Antonelli, G. (2021). The ethics of people analytics: Risks, opportunities and recommendations. Personnel Review, 51(3), 900–923.
Zak, B., & Zbieg, A. (2014). Heuristic for Network Coverage Optimization Applied in Finding Organizational Change Agents. 2014 European Network Intelligence Conference, 1–8. https://doi.org/10.1109/ENIC.2014.22
Knowledge-Centered Service (KCS®) and Intelligent Swarming℠ are registered trademarks of the Consortium for Service Innovation™.
CATALYNK gratefully appreciates the assistance of Polinode in supporting its conduct of Organizational Network Analysis.
Data selected for illustrative purposes.