Spinuzzi network-2
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A slide deck discussing Chapter 2 of my book Network.
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Spinuzzi network-2
- 1. What is a Network? Clay Spinuzzi Clay.spinuzzi@utexas.edu How to improve information flow in 1 organizations (c) 2011 Clay Spinuzzi
- 2. Value • Understand how sociotechnical networks differ from social network analysis and networked organizations. • Understand what a sociotechnical network is and why this sort of analysis is valuable. • Understand conditions that have led to more distributed organizations. • Understand weaving and splicing in sociotechnical networks. • Understand the four characteristics of sociotechnical networks. How to improve information flow in 2 organizations (c) 2011 Clay Spinuzzi
- 3. WE’RE NOT TALKING ABOUT… How to improve information flow in 3 organizations (c) 2011 Clay Spinuzzi
- 4. We’re not talking about Social Network Analysis (SNA) • Looks at connections between people • Connections are explicit • Data collection focuses on quantification (surveys, structured interviews, classifiable communications, most recently email and social networks) • Analyses are typically quantitative • Great for finding hidden connections, structural holes • In popular literature: Gladwell, Barabasi How to improve information flow in 4 organizations (c) 2011 Clay Spinuzzi
- 5. In social network analysis… Person Person Person Person Person Person Person How to improve information flow in 5 organizations (c) 2011 Clay Spinuzzi
- 6. Popular Books on SNA • Barabasi, Linked. • Gladwell, The Tipping Point. How to improve information flow in 6 organizations (c) 2011 Clay Spinuzzi
- 7. But SNA is different from sociotechnical networks… • SNA assumes constant nodes (human beings) • SNA comparatively underdefines links • SNA misses the notion of mediation • SNA therefore takes fitness (competence) to be a property of the node How to improve information flow in 7 organizations (c) 2011 Clay Spinuzzi
- 8. We’re not talking about networked organizations • A form of organization, distinct from tribes, institutional hierarchies, and markets • Focused on the people in the organization, newly enabled to communicate via digital technologies • Described in studies of distributed work, peer production, and warfare • Characterized by distributed leadership, involving pushing discretion to edges of the organization • Involving tactics such as swarming and rapid iteration • … although we will see some of those characteristics in Telecorp. How to improve information flow in 8 organizations (c) 2011 Clay Spinuzzi
- 9. In a networked organization… How to improve information flow in 9 organizations (c) 2011 Clay Spinuzzi
- 10. Popular Books on Networked Organizations • Toffler, The Third Wave. • Brafman and Beckstrom, The Starfish and the Spider. • Robb, Brave New War. How to improve information flow in 10 organizations (c) 2011 Clay Spinuzzi
- 11. But networked organizations are different from sociotechnical networks… • Networked organizations still assume constant nodes (human beings) • Networked organizations still comparatively underdefine links • Networked organizations are phenomena, while sociotechnical networks represent analysis How to improve information flow in 11 organizations (c) 2011 Clay Spinuzzi
- 12. Rather, we’re talking about sociotechnical networks • Analysis that involves both humans and nonhumans • Existing across history • Focusing on sociocultural meaning of linking people, practices, and artifacts • Transforming information and capabilities through different configurations • Examples: Activity theory, actor-network theory How to improve information flow in 12 organizations (c) 2011 Clay Spinuzzi
- 13. DISTRIBUTED WORK How to improve information flow in 13 organizations (c) 2011 Clay Spinuzzi
- 14. How to improve information flow in 14 organizations (c) 2011 Clay Spinuzzi
- 15. How to improve information flow in 15 organizations (c) 2011 Clay Spinuzzi
- 16. How to improve information flow in 16 organizations (c) 2011 Clay Spinuzzi
- 17. How to improve information flow in 17 organizations (c) 2011 Clay Spinuzzi
- 18. How to improve information flow in 18 organizations (c) 2011 Clay Spinuzzi
- 19. Adhocracies • “man will find himself *sic+ liberated, a stranger in a new free-form world of kinetic organizations. In this alien landscape, his position will be constantly changing, fluid, and varied. And his organizational ties, like his ties with things, places, and people, will turn over at a frenetic and ever-accelerating pace.” (Toffler 1970, p.125) • “managers are losing their monopoly on decision- making” (Toffler 1970, p.140) How to improve information flow in 19 organizations (c) 2011 Clay Spinuzzi
- 20. Adhocracies How to improve information flow in 20 organizations (c) 2011 Clay Spinuzzi
- 21. Decentralization • “the new production system relies on a combination of strategic alliances and ad hoc cooperation projects between corporations, decentralized units of each major corporation, and networks of small and medium enterprises connecting among themselves and/or with large corporations or networks of corporations.” (Castells 2000, p.96) How to improve information flow in 21 organizations (c) 2011 Clay Spinuzzi
- 22. 1996: GIS-ALAS How to improve information flow in 22 organizations (c) 2011 Clay Spinuzzi
- 23. TELECORP’S NETWORKS How to improve information flow in 23 organizations (c) 2011 Clay Spinuzzi
- 24. Telecorp’s challenges • Complexity. The competitive and regulatory landscape changed rapidly, leading to increasingly specialized units. • Interconnectivity. Telecorp had to create seamless links with its “coopetition” - rapidly • Speed. Every call is an emergency, leading Telecorp’s workers to find shortcuts and to process multiple calls at once. • Volume. Telecorp was growing rapidly, as was the entire telecommunications sector. • Turnover. At this point, unemployment was low and Telecorp had a hard time keeping employees. How to improve information flow in 24 organizations (c) 2011 Clay Spinuzzi
- 25. Telecorp as a Sociotechnical Network From the perspectives of • Activity theory • Actor-network theory “A dialogue, not a dialectic.” How to improve information flow in 25 organizations (c) 2011 Clay Spinuzzi
- 26. One Dog’s Death • “Rex” escaped his yard and was struck by a car. • Who’s to blame? Someone didn’t effectively circulate the message “dog in yard.” • ANT: political-rhetorical aspect • AT: developmental aspect How to improve information flow in 26 organizations (c) 2011 Clay Spinuzzi
- 27. Aside: I received an email… • “I'm currently taking a Qualitative Research Methods with [professor] at [university]. In our last class, we read your article "Who Killed Rex?" During our discussion, it was suggested that you fabricated your qualitative investigation of Telecorp in an effort to educate your readers …” How to improve information flow in 27 organizations (c) 2011 Clay Spinuzzi
- 28. Two Ways to Build a Network 1. Weaving (developmental) – Starts at a point and diverges – The longer the network, the more attenuated it is – Example: Different kinds of fishing nets – “Weaving” analyses emphasize human cognition and expertise. They’re asymmetrical. Activity theory provides a weaving analysis How to improve information flow in 28 organizations (c) 2011 Clay Spinuzzi
- 29. Development (Weaving) in ALAS Development How to improve information flow in 29 organizations (c) 2011 Clay Spinuzzi
- 30. Two Ways to Build a Network 2. Splicing (political-rhetorical) – Different preexisting elements converge – The longer the network, the stronger it is – Example: The Bell network – “Splicing” analyses examine humans and nonhumans on the same footing. They’re symmetrical. Actor-network theory provides a splicing analysis. How to improve information flow in 30 organizations (c) 2011 Clay Spinuzzi
- 31. Alliances (Splicing) in ALAS How to improve information flow in 31 organizations (c) 2011 Clay Spinuzzi
- 32. Three Aspects of Telecorp’s Network • The physical network: sprawling, delicate. • The actor-network: spliced, symmetrically treated actants (human and nonhuman) that provide the illusion of unified service. • The activity network: woven, interlinked activities that are asymmetrically treated; developing; and structured. How to improve information flow in 32 organizations (c) 2011 Clay Spinuzzi
- 33. Four Characteristics of Sociotechnical Networks • Heterogeneous • Multiply linked • Transformative • Black-boxed How to improve information flow in 33 organizations (c) 2011 Clay Spinuzzi
- 34. Five Events 1. Rex’s owner notices interrupted service. 2. He calls Telecorp and asks them to fix it. 3. The message finds its way to the NCC. 4. An NCC worker calls a BigTel technician and orders the repair. 5. BigTel’s technician visits the residence, accidentally letting Rex escape. How to improve information flow in 34 organizations (c) 2011 Clay Spinuzzi
- 35. How to improve information flow in 35 organizations (c) 2011 Clay Spinuzzi
- 36. How to improve information flow in 36 organizations (c) 2011 Clay Spinuzzi
- 37. Opening All the Black Boxes • “The workers’ jobs were complex because their relations to other departments, other activity systems, were complex and getting more complex all the time.” (p.57) How to improve information flow in 37 organizations (c) 2011 Clay Spinuzzi
- 38. Opening All the Black Boxes • “Without relative stability on which sustainable practices could be founded and formalized, workers could only learn by encountering contingencies and tailoring responses to each one of them.” (p.57) How to improve information flow in 38 organizations (c) 2011 Clay Spinuzzi
- 39. Who’s Responsible? • Not the person who brought the information into Telecorp, but … • The last line of defense: The NCC • But that person can plead mitigating circumstances! How to improve information flow in 39 organizations (c) 2011 Clay Spinuzzi
- 40. Exercise: Examine Social Media Use • What’s the team (functional boundaries)? • What are they trying to accomplish (multiple objectives)? • What are their assumptions? • What tools, texts, practices, people do they enlist, and how do those drag in other assumptions? • What information fails to circulate? How to improve information flow in 40 organizations (c) 2011 Clay Spinuzzi
- 41. THE FOUR CHARACTERISTICS OF SOCIOTECHNICAL NETWORKS How to improve information flow in 41 organizations (c) 2011 Clay Spinuzzi
- 42. 1. Heterogeneous • ANT: actants • AT: activities • Both: Qualitative, not quantitative How to improve information flow in 42 organizations (c) 2011 Clay Spinuzzi
- 43. 2. Multiply Linked • Links are heterogeneous too. • Links must be observed and analyzed empirically and/or discussed in interviews. • Formal or informal. • Active or passive. How to improve information flow in 43 organizations (c) 2011 Clay Spinuzzi
- 44. 3. Transformative • Standing sets of transformations. • Here: information and services. • Transformations often include genres. • Often qualitative and categorical. • How homogeneous assemblages of humans and nonhumans regularly effect transformations. How to improve information flow in 44 organizations (c) 2011 Clay Spinuzzi
- 45. 4. Black-Boxed • When we lift the limiting assumption of heterogeneity… • … we find that nodes are themselves networks… • … and we can potentially follow their links forever. • But in practice, the customer calls “the phone company.” How to improve information flow in 45 organizations (c) 2011 Clay Spinuzzi
- 46. Exercise: Apply the Four Characteristics • Heterogeneous. What different types of nodes (activities, actants) do you see in your case? • Multiply linked. What different types of connections (direct and indirect communication, influences, assumptions) do you see? • Transformative. What sorts of transformations (especially of information and services) do you see? • Black-boxed. How are parts of your case black- boxed – that is, how do people reduce complexity when talking about it? How to improve information flow in 46 organizations (c) 2011 Clay Spinuzzi
- 47. Twitter as Ambient Status Update How to improve information flow in 47 organizations (c) 2011 Clay Spinuzzi
- 48. Case Study: World of Warcraft • Sherlock, L. (2009). Genre, Activity, and Collaborative Work and Play in World of Warcraft: Places and Problems of Open Systems in Online Gaming. Journal Of Business And Technical Communication, 23(3), 263-293. • Grouping (team performance) enabled and enhanced through out-of-game genres. • Division of labor, strategies, tactics. How to improve information flow in 48 organizations (c) 2011 Clay Spinuzzi
- 49. Example: LinkedIn How to improve information flow in 49 organizations (c) 2011 Clay Spinuzzi
- 50. Exercise: Examine Weaving and Splicing • Weaving. In your case, how have things developed and diverged? Think especially of genres, functional groups, and practices. • Splicing. In your case, how have different things converged? Think especially of genres, functional groups, and practices. • “Text” comes from “textere,” to weave together. How are texts helping to weave – and splice – the organization? How to improve information flow in 50 organizations (c) 2011 Clay Spinuzzi
- 51. Takeaways • How sociotechnical networks differ from social network analysis and networked organizations. • What a sociotechnical network is. • Conditions that have led to more distributed organizations. • Weaving and splicing in sociotechnical networks. • The four characteristics of sociotechnical networks. How to improve information flow in 51 organizations (c) 2011 Clay Spinuzzi
- 52. Applications • Examining sociotechnical networks - qualitatively. • Determining how an organization has become woven together via development. • Determining how an organization has become spliced together via alliances. • Examining how they’re used at different levels. • Examining how they connect, especially in unsanctioned or unforeseen ways. How to improve information flow in 52 organizations (c) 2011 Clay Spinuzzi
- 53. We Still Haven’t Discussed… • The details of activity theory • The details of actor-network theory We’ll get to these in the next chapter How to improve information flow in 53 organizations (c) 2011 Clay Spinuzzi
Editor's Notes
- Hi, everyone. I’m Clay Spinuzzi from the University of Texas at Austin. In this slide deck, I’ll discuss Network Chapter 2.Just an aside here. When I wrote Network, I seriously considered putting the theory chapter, Chapter 3, before this one. That’s how academic books are typically structured. In fact, some of the reviewers thought I should have structured it that way. But I chose to put this concrete case first. Here’s why.First, activity theory and actor-network theory are both very dense and, to some degree, counterintuitive. I believed, and still believe, that a warm-up case like this one can help prepare the ground for that dense discussion.Second, I wanted to keep people interested in the book. I wanted people to see the stakes and the promise of learning these two theories before they did the hard work of absorbing them. And what better way than to read a true story of death and recrimination? Even when the death is that of a dog.Third, I wanted to emphasize that these organizational difficulties do have consequences.I hope this arrangement worked well for you too.
- Now, our talk today should deliver the following value. [read]
- Before we get to the chapter, let’s distinguish between sociotechnical networks and two other sorts of networks with which you may be familiar: social network analysis and networked organizations. As you can tell, “network” has become a very popular term. Let’s disentangle some of its uses so that we can better understand how sociotechnical networks can be useful.
- The sort of analysis in Network is an analysis of sociocultural networks. That’s very different from social network analysis. Let’s take a few moments to discuss what SNA involves and how sociocultural networks differ.(Read slide)
- In network analysis, we select a kind of node. Nodes can be anything – texts, atoms, bits, servers, genes. But in any case, you examine how these nodes connect.In social network analysis, the nodes are people. And by examining the connections among them, you can detect how networks scale, how they move information around, and how they are likely to operate. For instance, in the simple network on this slide, the person in the middle is the only one connected to other people. If that person gets hit by a bus, the network will be severely compromised.SNA also allows you to identify things such as strong vs. weak ties, structural holes, and brokers. It does a great job of inspecting overall resilience, and since SNA tends to be mathematical, it provides nicely verified models.
- SNA has become very popular, and you may have read these books as well as other, more technical ones.
- But SNA is not the same as sociotechnical networks. There are a few key differences.One, SNA assumes constant nodes. A node is a human being, period. In contrast, sociotechnical networks allow that people can act in qualitatively (not just quantitatively) different ways depending on their network. And some sociotechnical theory – specifically actor-network theory – assumes that nonhumans as well as humans can be nodes. ANT in particular delves into ontology, the question of being, and suggests that each node is itself a network. That is, we might see a telephone as a node. But we might also see it as a network consisting of other nodes, including components and service. Because of this multiplicity, sociotechnical analysis generates insights that are based on provisional frames. That makes it less precise than SNA, but much more flexible.Two, and this is a related point, SNA tends to underdefine links. For instance, SNA studies tend to try to discover “connections” (links) between people by looking at explicit communication among them: conversations, phone calls, email. Sometimes the question is more vaguely asked: Do you “know” X? How well do you know them? In contrast, sociotechnical networks can take other forms, such as mediation and translation. For instance, in our case, Rex the dog didn’t know the scripts that the Network Operations Center used to handle their calls, but these two nonhumans were still interconnected.These bring us to point three: SNA doesn’t have a concept of mediation. That is, as we saw last time and as we see in Network Chapter 2, people gain different capabilities when they mediate their work with artifacts and practices. For instance, someone who begins working at Telecorp initially has low expertise and won’t know what questions to ask. But they gain expertise quickly, not just through training (which is not well structured or applied) but by looking at products of previous work, by learning scripts, by borrowing or generating texts, or by assembling many genres (as we saw in the last slide deck). Mediation changes the capability of the “nodes” and leads people to learn different behaviors and gain different interpretations of the activity. Crucially, this leads us to a really crucial difference between SNA and sociotechnical networks. In SNA, fitness (or competence) is a property of a node (see Barabasi p.95). But in sociotechnical networks, fitness (or competence) can be the result of mediation. For instance, in our last slide, we saw that people consistently had trouble relating different genres, but some people adopted workarounds that allowed them to relate them much more effectively. A single innovation – a sticky note or photocopied map - could increase the worker’s effectiveness dramatically.
- So we’re not talking about SNA in Chapter 2, but we’re also not talking about networked organizations. By the way, lots of people confuse SNA and networked organizations. Barabasi goes down this path a bit in his book Linked. SNA simply takes people as nodes and maps out their links. These people could be related in a number of configurations, such as a kinship system in a tribe, a top-down hierarchical organization such as a large modern army, or an arm’s-length marketplace in which people come together temporarily to bargain. But networked organizations are a distinct form of organization, contrasted with tribes, institutional hierarchies, and markets. They represent a different way for people to organize themselves and establish lines of authority.
- For instance, in a study I published recently, I found that an Internet startup had set up at least groups that functioned as overlapping networks. These included teams of specialists that came together to work on a specific project; service groups; field-related groups; and social groups. These networks were generally quite small, some as small as two people, but together they ensured that everyone was connected to everyone else.In networked organizations, leadership tends to rotate within a network, and someone who leads in one network may not in an overlapping network. Leadership tends to be awarded based on specialization. Command and doctrine may be centralized, but control and discretion tend to be pushed to the edges, resulting in more decentralized decision-making. In contrast to SNA, networked organizations are distinct phenomena, not a method of analysis.
- Networked organizations are very popular, particularly in literature on business, open source software, and warfare.
- But like SNA, networked organizations are not the same as sociotechnical networks. There are a few key differences.Like SNA, networked organizations assume constant nodes – people. This perspective has the same contrasts and constraints as SNA’s.Similarly, analyses of networked organizations tend to underdefine links. People who analyze networked organizations do recognize how important communication technologies are, and particularly how digital technologies and telecommunications have lowered the cost of transactions, allowing networked organizations to scale much better than they had in the past. But beyond that, networked organizations tend not to examine links thoroughly or in ways beyond communication.For instance, an analysis grounded in networked organizations would pick up on some of the issues in the Rex case. It would identify and differentiate different networks in play at Telecorp, especially the connections that go across organizations (for instance, the fact that Telecorp workers often work more closely with their counterparts at other companies than other people in their own company). But a NWO analysis would tend not to look at the issues we discussed last time: issues such as the history of genres and practices, the levels of activity at which people work, or the way that genres (or artifacts or people or practices) form different capabilities through their assemblages.
- Rather, in Network Ch.2, we’re talking about sociotechnical networks. That is, we’ll deploy an analysis that examines how humans and nonhumans link together. Sociotechnical networks are heavy on history, interpretation, and transformation. (Read from slide.)In Network, I specifically examine two understandings of sociotechnical networks: activity theory and actor-network theory. We’ll get into their differences in a moment, lightly, and then in much greater detail in the next slide deck. But before we do, let’s take a detour and discuss a key notion that will help us understand why Telecorp functions the way it does.
- To get a handle on howTelecorp functions, we’ll discuss distributed work. What we see throughout the Telecorp example, and realistically what we will see in most organizations that focus on producing or transforming information, is a trend toward distributing work across heterogeneous units. And although I said we’re not talking about networked organizations per se, I’ll draw from some of the networked org literature to help describe what’s going on here. In particular, I’m going to pull from Alvin Toffler’s 1980 book The Third Wave. This book has plenty of problems, as does any wave theory of history, but it can provide us with a shorthand account of how work has become so distributed.
- Let’s bring up this diagram again. As I mentioned earlier, in an Internet startup, I saw people forming different, overlapping networks. These networks tended to be formed by specialists, they were often cross-functional, and leadership differed in different networks. Importantly, these networks were very fluid, able to absorb new people – and lose others. Since expertise is pushed to the edges, and since people get leadership experience in different networks, these networks tend to be resilient and highly reactive.
- If that sounds familiar, it’s because we talked about one example in the previous slide deck. We saw how very disparate fields such as business computing, geographic location, and accident analysis were brought together in the ALAS system. Often the results were not optimal. But that’s the challenge that Telecorp faced. And it faced that challenge at different levels.
- So let’s get to the question of Telecorp’s networks – specifically, its sociotechnical networks. And the challenges Telecorp faced as it tried to manage them.
- Here’s at least a few of these challenges. [read]
- So we could easily examine Telecorp as a networked organization. But remember, networked organizations focus on people and leadership. I was also interested in how Telecorp’s texts and technologies, its logics and assumptions, its development and its alliances. Studying Telecorp as a networked organization was not going to get me there, because a networked organization analysis has no place for examining them.This leads us to the two variants of sociotechnical networks discussed in the book: activity theory and actor-network theory. These are both sociocultural approaches, but they have very different assumptions and lead to different accounts. As I say in the book, I wasn’t interested in a dialectic in which I could reconcile them or declare a winner. I was interested in a dialogue in which I could use each account to gain insights – just as SNA and networked organizations give us different insights.So what kind of insights can we get from this sort of perspective?
- Let’s start with the case. On a hot August day in 2000, a customer called Telecorp to report interrupted local telephone service. A few days later, a telephone service technician opened the backyard gate to investigate the problem. Unknown to him, in the backyard lived a dog. Startled by the intruder, this dog fled the yard and ran into the street. He was promptly struck by a car. Let’s call this dog “Rex.”Who’s to blame for Rex’s death? More to the point, what can this instance teach us about how Telecorp worked and what contributions AT and ANT can make? We know that someone didn’t effectively circulate a message: “dog in yard.” But who? An aside here: when I was conducting this study, I thought that I would simply apply an activity theory analysis to it and be done with it. But in many instances, including this one, AT didn’t seem to tell the whole story. So I looked to actor-network theory to provide an alternate account. As I did, I realized that ANT is very good at examining political and rhetorical aspects: how humans and nonhumans are persuaded to work in the service of some goal. AT doesn’t do that so well – but it does examine cognitive and developmental aspects much better, showing how practices evolved over time.
- By the way, a couple of years ago I received the email above from a graduate student at another institution, asking about this particular case. He actually wondered if I made up this story. The answer, of course, is no. I told the grad student that the story of Rex was true, that I had the data to prove it, and that each claim had at least 2-3 different data points supporting it, data points coming from different data collection methods.Just wanted to make sure we were all on the same page here.
- Back to the case. As I argue in the book, there are two ways to build a network. The first is weaving, and this is the sort of building that activity theory excels at examining. Think in terms of examining how a pattern is repeated and developed over time. As one activity's labor is divided, it grows into several interwoven activities, and perhaps the interstices among the activities become wider. But genetically and historically, the activities interrelate.“Weaving” analyses tend to be asymmetrical. In other words, human beings take center stage here. They’re the agents who drive things and get things done through their cognition and expertise. They develop, and accordingly, their activities develop. In a weaving analysis, humans take center stage, although they are affected and enabled by their tools, texts, practices, and so forth.The book gives the example of weaving a fishing net. But we’ve seen this sort of development in another context…
- … from our previous slide deck on genre. As I discussed there, we could trace development in these basic patterns – these genres – across generations of the ALAS software. We saw last time that genre provides a good explanation of how text types develop over time; in this chapter, we see how activity theory is focused on the same sort of action, weaving networks together by incrementally developing tools, techniques, and other parts of an ongoing activity.
- But there’s a second way to build a sociotechnical network: splicing, in which you make connections between previously unrelated elements to form new uses. These might include historically separate technologies, practices, fields, trades, and disciplines. Spliced networks grow through opportunistic alliances among historically separate elements.In actor-network theory, splicing is treated as a political and rhetorical endeavor, one in which actors have to negotiate and compromise. The wider the alliance, the longer the network, and thus the stronger it is.“Splicing” analyses tend to be asymmetrical. In other words, human beings don’t take center stage here: they are not necessarily the most important actant. In fact, ANT doesn’t really have an account of cognition or expertise. Rather, it focuses on how different elements come together to make alliances with different qualities, and it uses the same terms to describe humans and nonhumans. In a splicing analysis, the connections and concatenations are more important than the qualities of the individual actants.In this chapter, I give the example of the Bell network, which allowed multiple operators’ networks to interoperate. But we can also look at another example from the last slide deck:
- The hybrid genres that we saw as ALAS developed. At each stage of development, ALAS developers combined traditional ALAS genres with genres from another domain. For instance, when the ALAS node map was spliced together with the GIS map, the hybrid genre represented two distinct technologies, activities, and representation systems that had converged. This convergence added functionality – but at a cost.
- So we can see three different aspects of Telecorp’s network.The first is the physical network, which is complex enough: lines, fiber, switches, repeaters, etc. This network is extraordinarily fragile and continuously breaks down.The second is the actor-network. And in the actor-network, we take a symmetrical viewpoint: that is, we treat humans and nonhumans alike as actants. These actants “persuade” each other to work together – that is, these different parts have to constrain each other so that the network holds together. When it does, we can forget that it’s a network of different actants and see it as a “black box,” a unified thing.The third is the activity network. In the activity network, which comes from activity theory, we take an asymmetrical viewpoint. The only actors are human beings; nonhumans are mediational means at best. Activity networks are woven together: individual systems of activity have developed over time, and when they come into contact, they develop stable associations over time. Finally, they’re structured. As we’ll see in the next chapter, each activity has developed a very definite structure over time.
- We’ll get to more differences between AT and ANT in the next slide deck. But in this one, let’s focus on their common characteristics – characteristics that set sociotechnical networks apart from social network analysis and networked organizations. Heterogeneous: They are material assemblages of dissimilar humans and nonhumans. They interrelate in relatively stable ways.Multiply linked: Networks are easy to disrupt, difficult to destroy because their components are interlinked along many lines. At Telecorp, many of these links were textual: customer orders, scripts, instructions.Transformative: Sociotechnical networks represent standing sets of translations. These standing sets are what get things done. For instance, when a customer calls to complain about interrupted phone service, that complaint is written on a notepad, typed into a database, conveyed over the phone to other workers, and turned into a work order sent to a technician employed by another company. It moved from one place to another, from one part of the network (one position, social language, genre, activity) to another – and it moved by being rerepresented and rearticulated (again, in all senses of the word). In this case, the message “dog in backyard” would ideally be extracted from the customer during a phone conversation, transformed into F1 notes in a database, made a part of the vital information, and orally presented to the tech.Black-boxed: Finally, these networks are black-boxed: although they are complex, we reduce that complexity. When you start your car, you don’t need to think about the many elements that make up your engine; you just drive. When you pick up a phone, you don’t need to think about lines, switches, or technicians; you just dial the number. When you “call Telecorp,” you may not know the job title of the person who picks up the phone and you probably won’t understand how their different departments interrelate. Most of the time, that complexity stays hidden, giving the illusion of a unified service.
- So with that background in mind, here’s the five events that led to Rex’s death. [read]Who killed Rex? The question is hard to answer because…
- … although the customer imagines that it works this way – they make a call to Telecorp – in reality
- … it works this way, with a number of different entities potentially receiving the call. Each entity might have different experiences and expectations. For instance, the NCC, Customer Service, and Sales all receive very different training and potentially would handle such a call in very different ways.In other words, the customer is encouraged to see Telecorp as a black box. But it’s not. It turns out that Telecorp is almost all border – specialists from various areas might receive the call. We can’t actually tell who took the call. It was likely someone in the NCC. But it could have been someone in customer service, sales, or elsewhere in the company. Nearly every worker at Telecorp could be contacted at any time by a customer, a vendor, a collaborator or a competitor, and thus nearly every worker could be pulled into different activities and asked to function in novel ways. This is typical in knowledge work, in which business-to-customer and business-to-business contacts proliferate (Zuboff and Maxmin 2004). Since these activities represented different points or functions in the call’s transformation, they did not receive that initial call in the same way; members of different groups asked different things, recorded different things, and routed the information in somewhat different ways. This posed a real problem in terms of tracking, routing, and maintaining quality. By the way, notice that this network stretches beyond organizational boundaries - not a formal organization, but who is really collaborating/contributing.
- Telecorp’s management wanted to deal with this issue by providing comprehensive training for managers. But Telecorp was changing so rapidly that it added new departments, divided labor, and acquired new processes rapidly. A combined weaving and splicing analysis helps us to see a more complete picture here. The weaving analysis lets us see how these departments are developing over time. We can detect their differing practices, expectations, and assumptions, especially as they extend and diverge over time. And in particular, what I saw was that because the telecommunications landscape was changing so rapidly, departments were developing and splitting at a rapid rate. For instance, in the first week I was there, a group split off from Customer Service to form a data entry unit. Over the 10 months I was there, I saw other functional groups emerge, as well as high turnover that brought in people from other telecommunications organizations, people who brought in their own ideas about how to work.That brings us to a splicing analysis. These departments didn’t just develop, they borrowed tools, people, and practices from other organizations and even other sectors and domains. Just as we saw with the ALAS cases last week, that meant bringing in other worldviews, assumptions, and representational systems. Individually, these could be spliced in to increase a department’s capabilities. In the aggregate, these tended to cause crises as each department’s composition had to be renegotiated. That is, most areas of Telecorp were continually in the process of being remade. This sort of splicing is characteristic of knowledge work.
- Whenever these changes occurred, workers had to figure out how to relate to the other parts of the organization. So it’s no surprise that workers became very focused on contingencies and emphasized “learning on the job” as the way to handle these contingencies. In fact, workers across the organization described training as “sink or swim.” And they usually followed up by saying “That’s the best way to learn.” And as long as jobs involved responding to contingencies, of course they were correct. We’ll return to this point in Chapter 6. But for now, I want to emphasize the continual changes in the organization due to continual development and addition – continual weaving and splicing.
- So let’s get back to our mystery: Who killed Rex? Who’s responsible? Nearly any Telecorp worker could have received the phone call. Once they received it, they could move it along one of several paths to get it to the NCC. But there was only one way leading from Telecorp to BigTel’s technician: the NCC. The last NCC worker to have touched the order must take the blame.But that person can plead mitigating circumstances. He’s typing four trouble tickets at a time while talking to a fifth customer! (Literally.) That worker has a convincing argument: the system needed to be more robust so that everything doesn’t hang on the overtaxed individual worker. But a system that evolves as rapidly as Telecorp’s will have a hard time building in this sort of robustness.
- Now let’s examine your case. what’s the team (what’s the functional boundaries?) and what are they trying to do (perhaps multiple objectives)? How else are they sharing information? What information fails to circulate?
- Let’s circle back and look at the lessons we can gain from sociotechnical networks. We discussed four characteristics of such networks that distinguish them from SNA and networked organizations.
- First, they’re heterogeneous. This factor makes them very different from SNA and networked organizations, both of which deal with relatively homogeneous nodes. ANT’s nodes are actants while AT’s nodes are activities, but both represent heterogeneous sociotechnical units. And these units are qualitative analytical units, so the quantitative tools that SNA applies don’t apply here.
- Next, they’re multiply linked. And just as the nodes are heterogeneous, so are the links. Such links must be observed and analyzed, and preferably the investigator should interview participants about those links too. Think in terms of formal communication, but also informal communication, infrastructure, or even training.
- They’re also transformative, another factor that sets them apart from SNA and networked organizations. Sociotechnical networks exist to transform things. In knowledge organizations such as Telecorp, those things are typically information and services, and important moments of transformation include the genres in which information is recast. (We’ll explore this more in Chapter 5.) Such transformations are often qualitative, such as the summaries that NCC workers type as they talk to customers. Much of it is also categorical, as in the database fields that customer service personnel fill out. Whereas SNA focuses on how homogeneous nodes are homogeneously interlinked, and networked organizations describe how people follow lines of command and control, sociotechnical networks describe how homogeneous assemblages of humans and nonhumans regularly effect transformations.
- This brings us to the last characteristic. Sociotechnical networks are black-boxed. This is a necessary move. SNA and networked organizations assume heterogeneity of nodes and links as limiting assumptions to reduce complexity. When sociotechnical networks let go of those limiting assumptions, we suddenly find that we can break down any node into its own network and follow multiple heterogeneous links – forever. That makes analysis quite difficult to close. But like the customer who thought he was just calling “the phone company,” we can black-box phenomena and treat them as nodes – until they break down, at which point we can open the black box and examine its components.
- Exercise: Discuss networks in your own case. Discuss examples of weaving and splicing. Bring it back to genres: How do they help to weave or splice together the organization?
- Okay, so let’s tie this discussion to social media.Example. We have a game in the US in which people throw balls with their hands, catch balls with their hands, and tackle each other with their hands. It’s called football. I didn’t play that game. Growing up,I played actual football:European Futbol (soccer). And my coach emphasized that we should communicate constantly. So in our games, we would constantly be calling things out. Often this was encouragement (“good work!”); sometimes it constituted alerts (“man on!”); and sometimes it was just status (“I’m behind you”). But in aggregation, this chatter constituted what we might call ambient status: when the whole team does this, any given player has a pretty good idea of where the other players are, without looking. If I have the ball, and I hear my team's voices, I know where they are without having to scan the field.PHOTO: ElvertBarnes http://www.flickr.com/photos/perspective/18057298/sizes/o/in/photostream/For me, the bulk of my Twitter usage is in assessing ambient status. I get a sense of the trends in the fields in which I work, but also the well-being of my contacts. I see when they're engaging in activities similar to mine. I can tell when they're struggling with particular issues. I can get a sense of what they're reading, writing, and studying. I know when they're sick and when they're enthusiastic and when they're uncertain. And sometimes I push out encouragement, alerts, and status myself, not necessarily directed to a specific person, but to the whole ad hoc "team.”Or should I say “teams”? Because my Twitter feed is a massive splicing of people from different domains: colleagues in my field, professors in other fields, friends, acquaintances, family, etc. Notice how different this is from the links in SNA or networked organizations. Such communications are not directional, nor do they stand alone. They help to maintain relationships and give clues about what’s happening in different areas. Each is a little transformation of status. More information: http://confusedofcalcutta.com/2011/04/22/thinking-about-twitter-and-chatter-the-knowledge-workers-pheromones/
- Here’s another, very different but better-focused example. Lee Sherlock examined how World of Warcraft players communicated with each other outside the game, and found that they developed far more sophisticated in-game team performance (grouping) because they spent time out-of-game developing documentation in wikis and forums. In other words, they connected World of Warcraft with genres from different domains; they borrowed and developed assumptions from very different activities; and the result was a qualitative change in how they played and perceived the game. They networked differently.
- One more example. LinkedIn is on the surface a straightforward application of social network analysis. Here, the profile pages are nodes, and the connections or contacts are the links. It’s quite easy to perform a social network analysis based on these data.But how do people use these in practice? If you actually observe people using LinkedIn and interview them about their purposes, you may find that they bend this service to quite different uses. Personally, I mostly use LinkedIn to gather information on my research participants. I’m not particularly interested in who they know or what their educational background is, because I’m not looking for a job or interested in hiring them. Instead, I’m interested in how they present themselves to a third party – specifically, their current job descriptions and sectors. So when I use LinkedIn, the links that concern me are not the profiles but the statements they make here – vs. statements they make on their websites and in their research interviews with me.I’m not unique. People bend and break the intentions of social networks all the time.
- So here are some takeaways from this chapter.[read]
- And here are some specific applications. [read]
- So. We still haven’t discussed the details of AT or ANT. We’ll get to these in the next chapter, which is theoretically somewhat dense. But for now, I was concerned about making sure you got the gist of sociotechnical networks and what they are meant to do.