WK8: SNA to observe decision making, an article

Identifying Decision Making Patterns
 Primary Health Care Centers

          Hierarchies are increasingly being replaced by flatter structures in industry. This is leading to an organizational focus on social networks within an organization (Cross, Borgatti, & Parker, 2002). These social networks have always existed – those that we trust when we need back-up, those we go to when we need advice, and those we communication with to get work done (Krackhardt & Hanson, 1993) and they are thought to be the real way work actually gets done. As organizations have flattened out, social network analyses (SNA) have evolved to identify the roles of individuals in these social networks. That information can then be translated into big picture diagrams, graphs, and number crunching that can give managers more information about how their organization truly functions (Cross, Borgatti, & Parker, 2002).

           

          I read an article titled Social Network Analysis as an Analytic Tool for Interaction Patterns in Primary Care Practices (Scott, Tallia, Crosson, Stroebel, DiCicco-Bloom, O’Malley, Shaw, & Crabtree, 2005) that applies a social network analysis to quantify decision-making patterns in 2 primary care health centers. The analysis studied how patterns naturally emerge to get work done on a daily basis. Initially the team of analysts observed the practices for two weeks, conducted interviews with key individuals, and collected sample documents. Then they made a matrix to map the consulting relationship by asking questions such as “Who does this person (ABC) consult when decisions need to be made?” They discussed and combined their findings in a matrix of consulting connections.

This is a simplified example I made which is similar to the complex consulting matrices made by the analysts. Matrices are a good source of information because they can be less confusing than graphs, especially when there are several actors involved (Intro. to Social Network Methods).  In an effort to account for directionality, the row represents the person seeking advice and the column represents whom they go to. This is an asymmetric matrix, because it has a source and a receiver (Intro. to Social Network Methods). They used 1s and 0s: 1 means that they go to that person and 0s mean that they do not. Here is an example…

	Taylor	Bill	Leslee
Taylor	-	1	1
Bill	0	-	0
Leslee	1	0	-

So you can see from this example: Taylor and Leslee go to one another for advice; Bill and Leslee go to Taylor for advice; neither Taylor nor Leslee go to Bill for advice; Bill and Leslee do not have an advice network.

similar to those in the Krackhardt & Handson, except in their
article they call it the advice network. In this article it’s the consulting network. 

          Then the team of analysts imported the matrices into software programs UCInet and KrackPlot to compute the qualitative data quantitatively using network structure measures. When the analysts compared the two practices, they saw that in one practice they had only one-direction consulting relationships and in the other they had a lot of reciprocal communication.  The difference in the amount of communication is visually palpable. Without even paying attention to the fine print, you can see in this diagram that practice 1 is has a lot of single direction traffic within minimal consulting relationships, while practice two has a lot of co-reliance for decision-making.

          They use KrackPlot (designed by Dr. Krackhardt) to analyze SNA measures of network density, clustering, centralization, and hierarchy. They hypothesized then how these measures might relate to outcome performance of the organizations. For example, the analysis indicated that practice 1 had strong hierarchy and practice 2 had no unidirectional connections, or in other words, no present hierarchy.  This could then be compared to performance measures to see if the hierarchy model has the better, worse, or the same level of performance and if this is statistically significant. The article did not present their findings as results to questions, but rather as observations that could later be used for future hypotheses.

FUTURE APPLICATIONS

          It would be interesting to do further analysis of these two practices to see how strongly the consulting network is connected to the trust networks. As stated by Levin and Cross (2004) trusting someone leads to more willingness to give him or her useful information. They could look at the type of trust, to see if it’s based on benevolence or competence. This insight might compliment the consulting analysis to see what types of relationships are most useful in the consulting network.

          Ibarra & Hunter (2006) talk about three types of networks every leader should maintain – operational, personal, and strategic. This article on health care practices could be useful to think about on the individual level to consider one’s own role in their with their immediate connections and who supports or blocks you from getting work done effectively. 

Scott, J., Tallia, A., Crosson, J. C., Orzano, A. J., Stroebel, C., DiCicco-Bloom, B., O'Malley, D., Shaw, E., Crabtree, B. (2005). Social network analysis as an analytic tool for interaction patterns in primary care practices. Annals of Family Medicine, 3(5), 443-448. doi: 10.1370/afm.344

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1466914/pdf/0030443.pdf