A Review of the Event Analysis of Systemic Teamwork Methodology

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HFIDTC/WP1.1.3/10 Version 2/ 31 October 2005 C4i networks within the emergency services, rail, military, aviation, nuclear reprocessing, air traffic control, civil energy distribution, and naval domains. Step 2: Define scenarios Typically, networks are analysed over a number of different scenarios. Once the type of network under analysis has been defined, the scenario(s) within which they will be analysed should be defined. For a thorough analysis, a number of different scenarios should be analysed. The scenarios used should be representative of all C4i activity within the network under analysis. In the analysis of naval warfare C4i (Stewart et al 2004), the following scenarios were analysed: • Air threat scenario • Surface threat scenario • Subsurface threat scenario Step 3: Data collection Once the network and scenario(s) under analysis are defined clearly, the data collection phase can begin. The data collection phase involves the collection of specific data on the relationship (e.g. communications and activity) between the agents during the scenario. Typical HF data collection techniques should be used in this process, such as observational analysis, interviews and questionnaires. Typically agent activity and the frequency, direction and content of any communications between agents in the network are recorded. Step 4: Construct agent association matrix Once sufficient data regarding the scenario under analysis is collected, an agent association matrix should be constructed. The matrix represents the frequency of associations between each agent in the network. Step 5: Construct social network diagram Once the matrix of association is completed, the social network diagram should be created. The social network depicts each agent in the network and the communications between them. The communications are represented by directional arrows, and the frequency of communications is also presented. An example social network diagram is presented in Figure 3-14. Step 6: Calculate agent centrality Agent centrality is calculated in order to determine the central or key agent(s) within the network. There are a number of different centrality calculations that can be made. For example, agent centrality can be calculated using Bavelas-Leavitt’s index. The mean centrality + standard deviation can then be used to define key agents within the network. Those agents who posses a centrality figure that exceeds the mean + standard deviation figure are defined as the key agents within the network. 53
HFIDTC/WP1.1.3/10 Version 2/ 31 October 2005 Step 7: Calculate sociometric status The sociometric status of each agent refers to the number of communications received and emitted, relative to the number of nodes in the network. The mean sociometric status + standard deviation can also be used to define key agents within the network. Those agents who posses a sociometric status figure that exceeds the mean + standard deviation figure can be defined as the key agents within the network. Step 8: Calculate network density Network density is equal to the total number of links between the agents in the network divided by the total number of possible links. Low network density figures are indicative of a well distributed network of agents. High density figures indicate a network that is not well distributed. Advantages • SNA can be used to determine the importance of different agents within a social network and also to classify the network type. • The SNA offers a comprehensive analysis of the network in question. The key agents within the network are specified, as are the frequency and direction of communications within the network. Further classifications include network type and network density. There are also additional analyses that can be calculated, such as betweenness, closeness and distance calculations. • Networks can be classified according to their structure. This is particularly useful when analysing networks across different domains. • SNA is particularly suited to the analysis of C4i scenarios. • The technique has been used extensively in the past for the analysis of various social networks. • The technique is simple to learn and easy to use. • SNA is a very quick technique to apply. The provision of the Agna SNA software package also reduces application time further. • SNA is a generic technique that could potentially be applied in any domain. Disadvantages 54
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A Review of the Event Analysis of Systemic Teamwork Methodology

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