Core Topics …

Social Networks, Network Visualisation & Analysis (NVA), NVA Mapping,  Influence Patterns, Communities of Influence, Advisory Committees, UCINETTM, KNETMAPTM


Key Issue …

NVA Mapping as a means to identify influential informal and formal organisational players such as leaders & innovators; also as a means to visualise the informal communications links and relationship patters across an organisation.


CASE 2: Network Visualisation & Analysis (NVA) Leads to Improved Customer Support


Copyright © 2008 The Leadership Alliance Inc. All rights Reserved


The Canadian manufacturing firm S.A. Armstrong Limited undertook to identify its subject matter experts (SMEs) by querying the organisation. Once lists of top and up-and-coming SMEs were made available to the Customer Support department, Armstrong customers received faster responses to complex questions about Armstrong fluid-engineered products.


Innovative and globally competitive firms, including manufacturers such as S.A. Armstrong Limited, function mostly on the basis of the know-how of their people, yet this knowledge is difficult to codify. Network Visualisation & Analysis can identify those individuals deemed by their peers to be subject matter experts on important products, processes and services.


Issues Addressed


The manufacturer S. A. Armstrong Limited produces a wide array of products for a company of its size. There are more than twenty product lines, and each line contains differently configured products. As each product is manufactured according to custom configured order, there are thousands of permutations of size, power, options and features. Additionally, each product must conform to the HVAC standards of the destination country and the intended industry.


The Customer Support department is responsible for addressing questions on these products. It prides itself on providing a response within two hours of receiving the call, either by telephone or email. The questions are generally complex, and frequently require an opinion or recommendation from a subject matter expert. Frequently these SMEs are not available (they may be out of the office or otherwise not reachable). When the top SME is not around, who is the next in line who can answer a customer support question? And when the next in line is not available, what is the pool of up-and-coming SMEs that can be accessed to provide a timely response to a customer question?




·         Identification of critical skills and expertise required to support the nineteen main product lines;

·         Identification of the source of the skills and expertise;

·         Analyse the dependence on these people for expert advice, and assess the risk to the organisation if this resource were lost;

·         Determine whether knowledge network maps provide useful decision support for continuity planning.



·         A query about expertise is sent by email:


Example Query:. To whom do you go for technical support regarding Vertical In-Line Pumps?


·         Employees respond to each query by selecting individuals from a pick list of names;

·         New names (including external contacts) are added to the list;

·         The data is displayed in a dynamic knowledge network map that updates after each submission.


We used the data-gathering tool KNETMAPTM for this pilot. This application generates dynamic Web-based knowledge network maps in real-time after each submission by a participant.

Figure 1: Sample  of an NVA map for Case 2


With the cooperation of 258 participants who were requested to provide data in response to twenty email queries over a period of two weeks, a series of “knowledge network maps” of people whose expertise was sought were generated for each of the following domains: Vertical In-Line Pumps, Horizontal Split-Case Pumps, End-Suction Pumps, Circulators, Vertical Multi-Stage Pumps, Sump and Sewage Submersible Pumps, Integrated Pumping Systems, Booster Pumps, Fire Pumps, Heat Exchangers, Circuit Balancing Valves, Flo-Trex Valves, Suction Guides, Hydronic Specialties, Motors, Variable Frequency Drives, Diesel Engines, On-Line Order Tracking, Heat Exchanger Software, ACE Product Selection Software.


Maps were made available for viewing by participants after each submission and were archived for retrieval, either for decision support, for location of expertise, or for monitoring changes in the knowledge networks. Specific attributes designating location (Canada, UK or USA) were assigned to all participants; these attributes were included in this sample ranked list generated by network analysis software.



Nodes are color coded by the following location attributes. All names are pseudonyms. This is sample data only.

n  Canada                                            n  UK

n  USA                                                n    X -- all others, including external contacts   

Node              Attribute

Don Topper            n                 # of incoming links (10); # outgoing links (0)

Alan Rockford        n                 # of incoming links (15); # outgoing links (0)

Rick Laing             n                 # of incoming links (12); # outgoing links (0)

Cindy Chelsea       n                 # of incoming links (11); # outgoing links (1)

Rand Mercer          n                 # of incoming links (4); # outgoing links (0)

Glen Chester         n                 # of incoming links (14); # outgoing links (1)

Dale Hart               n                 # of incoming links (6); # outgoing links (0)

Sally Bingam         n                 # of incoming links (6); # outgoing links (0)

Lewis Miller           n                 # of incoming links (9); # outgoing links (0)

Don Belisle            n                 # of incoming links (5); # outgoing links (0)


*Definition of REACH: Reach-In measures how influential a node is. The metric looks at both direct and indirect ties. By calculating how many unique nodes seek the advice/expertise/opinion of node X, the influence of node X can be determined. The influence of node X goes up if other influential nodes seek its advice/expertise/opinion. The sphere of influence for node X can be determined by viewing both direct and indirect in/out links surrounding node X -- incoming links show who seeks out node X, while outgoing links reveal who, if anyone, node X seeks for advice/expertise/opinion.

Node Specific Data

Don Topper: incoming link is Cindy Chelsea

Cindy Chelsea: outgoing link is Don Topper

Glen Chester: outgoing link is Rand Mercer

Figure 2: :Analysed Data



·         Lists of known subject matter experts;

·         Lists of up-and-coming subject matter experts.



·         Reduced subjectivity in identifying SMEs due to the peer evaluation approach

·         Identification of individuals with deep corporate knowledge

·         Exposure of vulnerabilities related to critical skills assets

·         Decision support for targeted training


Future Considerations

·         Generating and archiving knowledge network maps of subject matter experts and making such maps and/or lists available to all staff;

·         Using subject matter expert network maps as orientation tools for new staff;

·         Launching communities of practice led by retiring SMEs as part of a programme of continuous learning leading to capabilities development for a new wave of managers, thereby mitigating loss of expertise.

·         Updating the Yellow Pages system and creating links to the network maps;

·         Making such maps and/or lists available to customers and suppliers.




The data gathered in this pilot revealed many of the 'lynchpins' in the flows of knowledge instrumental to getting answers to complex technical questions. Such individuals are generally only manifest in informal networks because information flows do not follow managerial lines. These informal links help circulate information and are responsible for significant activity that sustains the effective functioning of the organisation, including better customer support.


Feedback from the participants was increasingly enthusiastic as this initiative progressed; several significant cultural issues were raised. Once the first few maps were generated, product managers became extremely interested in seeing results of their product lines and made an effort to better understand the emerging patterns through discussions with the KNETMAPTM project leader. Of particular interest to them were the “surprise” SMEs who surfaced as key resources.


Network maps show the relationships based on information exchange between colleagues. They are also reliable snapshots of how work gets done in an organisation. These maps have significant potential for decision support related to HR planning.