I’ve been thinking a lot about my recent work experience while studying culture, engagement, organizational change, and social network analysis in one of my classes at Northwestern. I was part of a small (~60 people) creative company that was acquired by a large matrixed global technology company (~30,000 people). It’s been really interesting unpacking how these concepts compare and contrast in the two different work environments, and even in other organizational units such as my family network and my Northwestern network.
Culture, engagement, and social networks are certainly connected in various ways. Culture can be casually defined as “the way things work around here” (2016, Bersin, Geller, Wakefield, Walsh) and as Schein famously points out, there are physical manifestations of culture (artifacts, environment), espoused values (innovation, philosophy), and unconscious underlying assumptions (thoughts, perceptions, feelings) (1992). Further, there are ways to look at culture at a micro level (subcultures, cliques) and a macro level (geographical, demographical). Whereas culture guides and constrains our work and integration in an organization, engagement is how we interact with the culture: how we feel about the work (“trait”), how we identify with the organization (“state”), and how we commit to the work (“behavior”) (Schein, 2010; Schaufeli, 2014; Kumar & Pansari 2015; Macey & Schneider 2008). As Schaufeli (2014) notes Shuck’s 2011 work, with engagement, one may not only feel connected and dedicated to the work at hand, but also to the organization at large. In short, engagement is our evolving and oftentimes personal relationship to both organization and to the job we have.
One way Social Network Analysis (SNA) connects to the concepts of culture and engagement is the notion that culture and engagement are not fixed - they are constantly evolving (2016, Lorsch & McTague) and, as mentioned above, composed of evolving relationships. Explicit in the name, SNA looks at engagement and culture as a network concept – not a pre-defined concept. SNA can help us understand culture and engagement in new ways with its relationship-orientation. SNA strives to bring data related to our physical relationships (who we are near and far from), emotional relationships (who we trust, who drives enthusiasm), and cognitive relationships (who do we go to for answers). The analysis of SNA data can not only help create a story of culture and engagement, but also help understand gaps and be a valuable input to strategic decision making.
“SNA offers an opportunity to examine human capital from a social and relational perspective and offer new insights into how information and energy flow ”
There is an old saying “it’s not what you know; it’s who you know”. I believe that with SNA, who you know IS what you know. SNA offers an opportunity to examine human capital from a social and relational perspective and offer new insights into how information and energy flow (2015, Hollenback & Jamieson). SNA and other traditional HR-centered business analysis methods agree that “the effectiveness and power of an individual… depends not just on his or her position in the hierarchy, but on the person’s place in a variety of intertwined networks” (2002, Kleiner). Using SNA can help create maps of influence, networks, reach, and other social attributes, often referred to as social capital ((2015, Hollenback & Jamieson). Social capital, in short, is powerful. It can take on many forms of power: positional power (highly networked and/or networked to key stakeholders or stakeholder groups), expertise power (knowledge), or personality power (charisma, trust, reputation) (2016, Cawsey, Deszca, & Ingols). If one can assert that (a) social capital comes from strong (or many) relationships, and (b) participation in the myriad of relationships drives engagement, and (c) that engagement is related to job performance, we can deduce that (c) networks and their inter-relationships drives performance in an organization (2010, Rich, Lepine, & Crawford).
My reflection about these concepts kept coming back to the concept of trust. Trust is an important common thread that links engagement, culture, and learning. A typical hierarchical organizational map shows reporting and departmental relationships, but it definitely does not show how trust is shared among employees and groups. With social network analysis, we can begin to see how trust is built and sustained (and perhaps lost) through our study of seeing how information flows through networks. Perhaps best said by Art Kleiner, referring to Karen Stephenson’s Quantum Theory of Trust, he posits:
[There is a] direct cognitive connection between the amount of trust in an organization and its members’ ability to develop and deploy tacit knowledge together. Because networks of trust release so much cognitive capability, they can (and often do) have far more influence over the fortunes and failures of companies from day to day and year to year than the official hierarchy. (2002, para. 2)
Simply put, “trust is the utility through which this knowledge flows” (2002, Stephenson, quoted by Kleiner). One way I was thinking about it was like a metaphor of the circulatory system in the human body. The veins and arteries show the network – all of the possible connections between nodes. Culture, knowledge, and information will flow through that network, just like blood will flow through those veins and arteries. However, to get the blood actually to move, the heart needs to pump the blood. The heart pumping and actually getting the blood to move around the network like the concept of trust. It gets information moving.
“Simply put, “trust is the utility through which this knowledge flows” ”
Of course, not all connections between nodes/actors exhibit trust. Some connections in networks are mandatory, some are superficial, and yet others are environmental. However, organizations must consider building a culture of trust in order to create the groundwork, the potential, for trustworthy relationships. Trust as part of an organization’s set of values will elicit both the espoused and subconscious layers of culture, thus enabling stronger engagement in peer relationship-building, and thus flow of information and learning. While trust may be a difficult concept to immediately instill in a troubled organization, with a continuous cultivation it should be part of a movement towards “humanization of the organization” (2016, Ng). With the growth and evolution of trust, a social network map will change over time – I believe we’d be able to see not only more connections but stronger and more multi-directional ties. Further, as trust can be correlated to learning and information flow in an organization, businesses can effectively consider it a part of their culture that provides a unique competitive advantage.
Despite the many connections and similar threads between these concepts of trust, culture, engagement, and analyzing social networks, there are some gaps we must consider. Biases are inherent with any analysis, and social network analysis is no different. The analyst must be aware of the self-confirmation bias in particular, insofar as the data may confirm a thought you subconsciously already believe to be true. Other biases may be related to priming, or drawing a conclusion from the data that may have been exposed to you before your own analysis. Another gap may be related to overall subjectivity when the actors (people) are interviewed for data collection. For example, if I am having a particularly troublesome time with a connected employee, there is a potential for a different, in this case more negative, response to my overall relationship with that person. Similarly, if I am having trust issues in my non-work personal life, that overall mental state of non-trust may influence how I perceive trust in my professional life. Further, and this is one point I am particularly puzzled by, subjectivity can be raised when considering the typical Likert scale of strength – for example what is “very strong” versus “strong” – the actor’s interpretation can be considered subjective. This is a consideration to make when looking at the actual measurements of SNA (2013, Schaufeli).
Another related effect to consider in SNA is how much of a relationship or structural hole is within an employee’s control. Oftentimes, seating arrangements, reporting lines, and access to people (due to schedules or gatekeepers such as administrative assistants) are not within an employee’s control, so the network map will need to take that into consideration. A specific example is a seating chart. The proximity bias may influence relationships that may not have been there under other circumstances. For example, I may share more information more frequently with the person sitting across from me solely because he is within proximity to me. If s/he moved to another location, that relationship tie may diminish, weaken, or altogether stop, creating a structural hole (2014, Hanneman & Riddle) even though it is out of my control and not related to trust or engagement with the person. Whereas some theories, namely Burt’s, posit that structural holes can produce positive outcomes like creativity, we can also conclude that structural holes create gaps of information flow that can be, as mentioned above, out of the employee’s control no matter how much effort they make to close the gap (2014).
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REFERENCES & SOURCES
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