Spinuzzi network-5

Editor's Notes

• #2: Hello, everyone, this is Clay Spinuzzi again. And we’re up to Chapter 5 in Network: “How are Networks Enacted?” Here’s where we start bringing our previous work to bear on specific cases.In the last slide deck, we examined net work at a high level, a strategic level, a macro level. Now, we’ll move to the tactical level, the meso level. (For much more on these heuristics, see my book Topsight.)You can think of this as the level where most of us live most of the time. This is the level of goal-directed actions. When you ask someone what they’re doing, they probably won’t respond in terms of their organizational mission: they’ll say something like “I’m writing a report” or “I’m updating these records in the database” or “I’m playing Farmville.” That is, they focus on the immediate goal they’re trying to accomplish that day and on the actions that they take to accomplish it. Today, we’ll go over some practical heuristics that will help us make sense of this meso level.
• #3: So here’s the value you’ll get out of today’s session. We’ll see what understanding sociocultural networks can help us bring to a concrete analysis of work coordination and organization. We’ll find out how understanding sociotechnical networks can help us to better understand networked organizations, which we discussed in Slide Deck 2. We’ll talk a little more about texts in three senses: inscriptions, genres, and boundary objects.And most importantly, we’ll model some instances of net work using three heuristics, three evidence-based models that help us examine different aspects of goal-directed actions.
• #4: Some background first. In the first half of my book, activity theory and actor-network theory have been described as antagonists. They’ve been opposed. But here, finally, we see them coming together. We’re going to team them up, despite their differences, and make them work together.Let me give you an analogy.
• #5: If you’ve read comic books, maybe you’ve heard of the Marvel Team-Up. The idea is that one superhero – usually Spider-Man – would meet and often end up fighting another superhero. Usually the superheroes have different, complementary powers that make them evenly matched.But at some point the two heroes have to stop fighting and work together to defeat a more powerful, more evil foe. They have to team up and use their complementary powers. And at the end … they’re friends. http://upload.wikimedia.org/wikipedia/en/7/74/Marvel_Team-Up_Killraven.jpg
• #6: That’s basically what Ch.5 is about. For the first half of the book, we’ve been discussing the differences between these theories. Each has different strengths and weaknesses – different superpowers.But finally, in Chapter 5, they team up: finally we can coordinate them, leveraging their separate superpowers in common cause. It’s the theory team-up.Photo: http://www.flickr.com/photos/maha-online/2163831851/http://www.marxists.org/archive/vygotsky/images/index.htmhttp://www.flickr.com/photos/mrcrash/85539715/
• #7: What exigency causes this team-up? It’s not a supervillain. Rather, it’s the shared metaphor of the network, which is applied to the many changes in how work is being conducted in an increasingly connected, mediated world.As ShoshannaZuboff argued in her book In the Age of the Smart Machine, our work and our lives are becoming “informated,” suffused with information and information technologies. That’s in part what activity theory and actor-network theory have been fighting over: how best to analyze these changes. As we saw in Slide Deck 2, the two theories are coming into contact more and more, converging on the same spaces – spaces that focus on knowledge work.But rather than fighting, they can team up to face this challenge.http://www.flickr.com/photos/respres/5181391026/
• #8: Recall our discussion from Slide Deck 2. As we’ve moved from agricultural societies to industrial work to knowledge work, we have changed how we organize and coordinate work. Particularly with this last move to knowledge work, we have seen the rise of networked organizational structures. These networks don’t do away with the previous structures (tribes, institutions, and markets), but rather, they overlap them.Public domain, Library of Congress, http://www.flickr.com/photos/library_of_congress/2179136302/Public domain, Library of Congress, http://www.flickr.com/photos/library_of_congress/2179077779/in/photostream/CC, Rod McLatchy, http://www.flickr.com/photos/rodbotic/2479178443/
• #9: And in Slide Deck 2, we discussed networked organizations. I outlined several differences between networked organizations and sociotechnical networks – but although they’re very different things, they do interact. As more organizations switch from hierarchical to networked organization structures (or overlap those structures), they need more communication and coordination. These involve more boundary-crossing, more interactions across disciplines and fields, more roles per person, and often, more texts that help to textere, to weave together, these networks.
• #10: In the book, I characterize this shift in work organization as moving from modular work to net work. Modular work is what characterized work during the Industrial Revolution: tasks were decomposed, routinized, regularized, and supported with separate trades, fields, and disciplines. Net work is what characterizes the Information Age: tasks are still separate but must be reintegrated, spliced together and leveraged, and supported by specialists who work across trades, fields, and disciplines. Let’s look at each.
• #11: First, we’ll discuss modular work, which characterizes the Industrial Revolution.
• #12: Think in terms of the assembly line: complex tasks are broken down into much simpler, more repetitive and controlled ones. Generalists become specialists. These tasks are connected, but in very predictable and circumscribed ways. They’re modules that can be stacked and connected.
• #13: Remember, activity theory developed in the Industrial era: its beginning corresponded with the beginning of the USSR, and it’s theoretically grounded in Marx’s critique of the early Industrial Revolution. So it’s not surprising that a chained activity system looks quite a bit like an assembly line, with the outputs (objects, outcomes) of one activity becoming the inputs for other activity systems down the line.
• #14: Modular work involves specialization: in modular work, a complex task is decomposed into simpler tasks, and those tasks are tackled by people who don’t necessarily have a broader understanding of the rest of the work. That’s by design: the more narrow and circumscribed the task, the more easily you can replace the worker. We might think about this in terms of weaving, as discussed in Slide Deck 3. Labor is progressively divided across space and time. And because tasks are narrower and more specialized, workers are deskilled: they build up fewer long-term skills and narrower skill sets, and consequently can be replaced more easily by other semiskilled workers – or by automation. Within an organization, modular work tends to be hierarchical: workers don’t communicate across units, but rather, through their supervisors. That’s partially because communication can be expensive. The assumptions of modular work are pretty good ones if you’re running an assembly line. But in a networked organization, they aren’t. For instance, at Telecorp, different specialists must work directly with each other to solve cross-functional problems; border crossing is common, as specialists have to work across functional and organizational boundaries. To explain organizations such as Telecorp, we need a different understanding.
• #15: And that brings us to net work. By the way, I planned to name my book “Net Work” – with a space in between – but according to my editor, Cambridge University Press was “not keen” on the pun. Too bad. Because the book isn’t really about networks so much as about net work. Let me show you what I mean.
• #16: Think in terms of the shift to the knowledge economy. As we saw in Slide Deck 2, to facilitate knowledge work, it helps to establish networked forms of organization: relatively independent workers in fast-changing, recombinant organizations.Work tends to be reorganized from departments to projects, attacked by transient teams of specialists: knowledge workers. In these “adhocracies,” cross-functional teams change in composition, and leadership shifts during different stages and different projects. In these circumstances, organizations must be 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 positions, these organizations tend to be resilient and highly reactive. They tend to be networks.Public domain, Library of Congress, http://www.flickr.com/photos/library_of_congress/2179136302/Public domain, Library of Congress, http://www.flickr.com/photos/library_of_congress/2179077779/in/photostream/CC, Rod McLatchy, http://www.flickr.com/photos/rodbotic/2479178443/
• #17: By net work, I mean the coordinative work that weaves and splices divergent work activities and that enables the standing sets of transformations that characterize such work. That is, net work is what holds together networks.Although it may describe how networked organizations hold together, net work is different from networked organizations: whereas networked organizations describe individuals and their relationships, in net work we’ll look at the coordinative work that holds these organizations together – the coordinative work that allows assemblages to form and coordinate.
• #18: These stable settings of modular work have been destabilized by recent changes in work: downsizing, automation, flattening of work hierarchies, increasing numbers of relationships between companies, continual reorganization, the breaking down of "silos" or "stovepipes" in organizations, and perhaps most importantly, the increase in telecommunications (phones, faxes, Internet connections), which has made it possible to connect any point to any other, within or across organizations. One result, Nardi et al. say, is that "many corporations operate in an increasingly distributed manner, with workers, contractors, consultants, and important contacts such as those in the press located in different parts of the country or across the globe" (p.206; cf. Zuboff & Maxmin 2004).Net work has to hold together these very heterogeneous networks. That’s partially accomplished through standing sets of transformations.
• #19: Net work involves developing and coordinating relatively stable, standing sets of transformations. These form dense interconnections among people, texts, tools, etc. They involve multiplicity and polycontextuality: that is, they help people with different backgrounds and functions to work together despite their very different orientations to a shared problem. They cross functions, trades, disciplines, and even organizations.Here’s an example, a figure from an article I published in 2010. In this case, people at a search engine marketing company are trying to improve their clients’ rankings in Internet search results. To accomplish that, they’ve set up several different transformations, mostly involving representing and rerespresenting data so that they know how to handle the next round of changes.
• #20: In activity theory’s terms, net work activities don’t chain so much as they overlap and interfere with each other. The people who are involved have to take on many functions, talk to people from many different areas, and rely on many different texts and processes to transform their information. To use the terms we discussed in Slide Deck 3, they are less like astronauts and more like collective subjects – cyborgs.
• #21: As I say in this chapter, “we’re faced with collective subjects, composite subjects whose stability is punctuated by changes in the assemblages that constitute them, cyborgs.” Let’s go back to an illustration we discussed in Slide Deck 3. A blind man + a cane + his environment can form a unit (an assemblage). This unit has collective properties, properties that the blind man alone doesn’t have. People and tools exhibit different capabilities; in assemblages, they may exhibit emergent capabilities that are the property of the assemblage rather than attributable to the individual parts. These assemblages can come about through sometimes surprising coordinations and connections.http://www.flickr.com/photos/welcome2bo/4337922625/
• #22: Just a quick example from Slide Deck 4. As we discussed, Universal Service subsidies are calculated in part based on eligibility for subsidized school lunches. This is a very complicated connection across activities and organizations. In fact, Jean, a new hire in Accounts Payable, had no idea how this complex connection worked. But she handled it anyway, via spreadsheets left by the previous worker. The previous worker had set up a standing set of transformations, and Jean just had to learn her part in this scheme. Like the blind man with the cane, Jean felt her way along with the help of the other tools her predecessor had left. Jean didn’t know how to calculate Universal Service, or even what it was. But Jean plus Spreadsheet did.http://www.flickr.com/photos/specialkrb/3019685980/
• #23: Net work involves a lot of coordination and communication within and across organizations. Much of this communication is cross-functional, among specialists who don’t necessarily belong in the same hierarchy and who therefore can’t really issue orders or commands. Instead, they have to build alliances.So in net work, Negotiation becomes an essential skill. You’ve got to be able to find ways to work with these people, ways that may not involve rank.Trust becomes an ongoing project. You have to build trust across and within organizations.Organizations become looser aggregations. People develop personal connections across these boundaries and may work more with their counterparts in other organizations than they do with people in their own.And rhetoric becomes an essential area of expertise. Given the above, people have to inform, instruct, and persuade each other.
• #24: Let’s circle back and talk a little more about one of those points. Since organizations have become looser aggregations, anyone can potentially link up with anyone else inside or outside the organization, and consequently any work activities can be intersected -- or reconstituted. Once you put a phone and an Internet-connected terminal on every worker’s desk, there are no necessary boundaries. I saw this a lot at Telecorp, in a lot of different ways.In this environment, traditional leadership (within functional areas or branches) was supplemented with emergent leadership, in which people with no formal hierarchy (or training) developed project-oriented relations. In the absence of formal hierarchy, in a fast-moving interconnected environment, skills such as time management, informal networking, and persuasion became critical.
• #25: So how are these connections sustained? To find out, first we’ll return to texts. We discussed texts quite a bit in Slide Deck 1. And one thing I mentioned was that the word “text” comes from “textere,” meaning “to weave together.” So how do texts weave networks together?
• #26: They function in at least three senses. (read)
• #27: Let’s start with inscriptions – a term from actor-network theory. These are individual texts, not text types. They’re concrete traces that represent phenomena in stable, circulable ways. They represent a phenomenon, and in doing so, they allow us to dominate it. And they create realities.This language – drawn from Bruno Latour – really sounds far-fetched. We dominate phenomena and create realities? So let’s make sense of it by looking at an example.In Ch1, Darrel thinks Gil is being unreasonable. You may remember this case. Darrel is a sales associate, and he’s very excited about a customer who wants to come back to Telecorp. He’s talked to the customer and judges the customer to be solid and trustworthy. What’s more, the customer is offering to pay in advance. From Darrel’s perspective, the customer is great.But Gil, in Credits & Collections, doesn’t meet the customer, shake his hand, and take his measure as a person. Instead, Gil looks at the customer’s credit report – a piece of paper that represents the customer in terms of specific characteristics. A concrete trace that represents a phenomenon – the customer – in a stable, circulable way. The client may represent himself differently, but the credit report is an immutable mobile: it boils down the information to one number, a credit score. And based on that score, Gil refuses the customer. Darrel, who isn’t privy to the credit report and who has (after all) looked this customer in the eyes, can’t believe this. It’s like they’re not even talking about the same person. In a sense, they aren’t. I mentioned that inscriptions are individual texts. But we understand these texts in part because they form recognizable types. Once you learn to read a credit score, you can interpret a whole stack of them. We’ve talked about text types before, in Slide Deck 1.
• #28: There, we called them genres. I won’t belabor them here, butI’ll remind you that they are not just texts, they’re ways of seeing, understanding, and processing information. Coordinating genres involves coordinating perspectives. Connecting them in assemblages involves linking up these different ways of understanding the world. As we’ve discussed, genres provide relative stability: we know how to interpret them. But they also provide flexibility: they evolve in response to evolving problems, and we can also splice in genres from other domains if we need to adapt to local conditions and intersecting activities. When we look at standing sets of transformations, we’re usually looking at how genres have been sequentially linked.
• #29: Finally, these genres or text types can act as boundary objects: objects that function differently across different sites, although they maintain a constant identity. For instance, a service order might be understood and processed in very different ways by a customer, a customer service representative, a CLEC provisioner, and a service tech. But they all call it an “order.” It’s a boundary object, crossing different boundaries, maintaining more or less the same identity.Boundary objects are often texts – or text assemblages.
• #30: So: as circulatingrerepresentations, texts help to define the groups that they weave and splice together. (read)
• #31: With that under our belt, let’s get to the four concrete cases we’ll be discussing. These cases illustrate different heuristics – different models, in which we can coordinate activity theory and actor-network theory.
• #32: Case 1: Following an order. I just mentioned how an order might serve as a boundary object; now let’s look at how it does this.
• #33: This figure is based on a flow diagram as defined in Beyer and Holtzblatt’s book Contextual Design. The order starts in the top left corner, where a customer calls Telecorp and reaches a customer care worker. From there, we can see how information flows to different parts of Telecorp, and even beyond its borders to the BigTel database used by the entire telecommunications industry. This diagram illustrate a standing set of representations: a whole lot of different texts that represent different aspects of the order, going to different people, instantiated in different media. Three things are striking here.First: There was no order. At least, there was no single text or representation that we could say was the “order.” The parts of the customer’s request were represented in different genres and media, traveling along different pathways to different specialists. Second: There was no transportation without transformation. Every time the information flowed, it flowed by being rerepresented in a different inscription. For instance, when the customer called the customer care worker, she or he would type up the information into an application form; then upload it to the intranet; then generate a text file that was then printed for a file and emailed to the postmaster. The information moved by being rerepresented.Third: There was no single genre. In fact, we see a whole set of genres here, each one connected to others in specific ways. We could dive more deeply and see how these relationships involved mediation, but here, we can see definite sequential relationships among these genres.
• #34: Yet the genres were stable – stable enough that they could weave together different functional groups. The application form could be transformed into a text file and sent to the postmaster, for instance, and the postmaster knew how to redirect it to the right place.These texts had to codevelop because they had to circulate as a whole. For instance, the application had to ask for the same information required by the AS/400 database. If the database had changed, so would the application.As stable genres, these texts could be reviewed and used by different people in the organization. For instance, once the order is rerepresented in the AS/400, other workers – such as CLEC Provisioning and the switch techs – could read and understand the parts that were relevant to their own duties. And they could scrutinize these details years later.
• #35: My colleague Bill Hart-Davidson has been experimenting with similar, but simpler ways to represent how people string together such communicative events into sequences. In fact, between now and next time you’ll be working through a model such as this one. (You’ll recognize this one from the reading.)Such communicative events are events in which one actor "hands off" a communication to another; emails, phone calls, document handoffs, and "do not disturb" signs on doors could all be considered communicative events. Usually these "handoffs" are instantiated in texts or speech. Communicative events tend to follow patterns, and these patterns tend to cycle within the larger activity in an organization. For instance, - a telecommunications worker receives a list of past due notices from his manager, then calls a customer, then makes a note in the database for his fellow workers.Since these communicative events involve identifiable transactions, we can detect them (especially if we ask the participants to help interpret them). And in most cases, these events follow regular and recurrent patterns: people tend to develop or learn a sequence for communicating, and they tend to stick to that sequence unless other circumstances intervene. So examining communicative events tells us a lot about how people understand their work and how they handle disruptions.CEMs provide a simplified, easily comparable description of event sequences, a description that can help us detect patterns in people’s work, compare patterns, and see sequential divergences. Any given action is a contingent choice made in response to situational constraints. In the CEM, these contingent choices are essentially portrayed as strings of verbs and nouns. If we were to apply CEMs to longer segments of work, we should be able to formally detect consistent patterns, identify larger units of interaction, and consistently explore places where sequences diverge across workers or conditions.
• #36: CEMs can do something else too. Often, work suffers from action-level disturbances called discoordinations: points at which two or more texts just don't "fit." At these points, the sequence is interrupted, and the participant has to find a way to repair the coordination before she can continue the sequence. You can map these discoordinations on the sequence. If you’re finding that a large number of people are encountering discoordinations at the same place, you may have found a part in the system that you can improve.For next time, you’ll be reading instructions on how to develop your own CEMs.
• #37: Let’s get to the second case: Following the money.
• #38: In this section, I used a familiar heuristic: Genre Ecology Models. We discussed these in Slide Deck 1, so I won’t spend too much time on them here.Just a note – These are a little more complex than the genre ecologies we discussed in Slide Deck 1: you’ll notice that they have arrows to show how one genre acts on another, as well as thicker lines for more frequent connections. Don’t worry about these. We’re going to try something a bit simpler in our exercises for next time. Anyway, these models are based on several observations of several people working in Cash Posting.Just a glance and you’ll see the central organizing principle that people in Cash Posting use to coordinate texts: the stack. They stack to signal several things:- Sequence- Stage in processing: completed vs. pending- Place in processing- Progress- Separate genres
• #39: But when they move to transferring information across texts, the stacks disappear. We see them transferring information from the form to a variety of other genres. And from many genres to the AS/400 screen. They activated different relationships among the genres, depending on what they were trying to do.
• #40: In contrast, downstairs at Credits & Collections, their chief coordinating text was a list. They would print a report of past due notices, then turn it into a checklist. The combination of a printout of customers plus a checklist plus a spreadsheet yields a system for tracking overdue accounts. And what was extraordinary was that all of them used a very similar system – but they also claimed that their system was idiosyncratic. They didn’t learn it, they just made it up themselves.
• #41: About two thirds of their work, however, involved transferring information from one genre to another. They copied texts from one genre to another constantly. Consequently, these genres were closely tied together. As Latour likes to say, there is no transportation without transformation.
• #42: We can scale out just a little more to discover that the different functional areas had specialized languages. I talked with one person in Accounts Receivable who had difficulty understanding an AS/400 note from a colleague in Credits and Collections. After trying to understand the note, she confessed to me that “everybody interprets things differently.” Her solution was to wait until the author came back from lunch, then give her a call.But that’s a common problem at Telecorp. People ended up summarizing all conversations with customers in the AS/400 database. But since they always had other work to do, they would have to summarize drastically. “Trying to shorten your 20-minute conversation into 10 words is kind of difficult,” one told me with considerable understatement.
• #43: We’ve discussed GEMs in Slide Deck 1, but here they are: Another powerful heuristic as you look for patterns in how people coordinate work. What textual resources are out there? How do they connect with each other?Again, you’ll recognize this one from the reading.
• #44: And like Communicative Event Models, Genre Ecology Models can help you to detect discoordinations between texts. Often, genre ecologies suffer from action-level disturbances called discoordinations: points at which two or more different genres just don't "fit.” The Genre Ecology Model allows you to map these discoordinations in a systematic fashion.
• #45: Let’s get to Case 3: Following the Substitutions.
• #46: Sociotechnical graphs come straight from actor-network theory.Latour uses sociotechnical graphs to examine statements. Sociotechnical graphs are an attempt to empirically model assemblages of humans and nonhumans as they associate themselves with each other and intermediate each other. Borrowing from linguistics, Latour, Mauguin, & Teil (1992) describes these associations as having paradigmatic and syntagmatic dimensions. By syntagm, the authors mean the associative dimension, the AND dimension: the human and nonhuman elements that must be associated in order to make a statement true. By paradigm, they mean the substitutive dimension, the OR dimension: the human and nonhuman elements that can be substituted for each other while keeping the statement true.
• #47: One example: The Network Operations Center, discussed in the case “Who Killed Rex?” from Slide Deck 2. In the NOC, as you’ll recall, workers sat at long desks arranged as if in a theater, all facing the same large screen. Each place at each desk had a terminal and a phone, which the workers used to coordinate repairs. All day long, workers would receive calls: calls from customers with phone service problems, calls from service techs in their own and other companies, calls from network operators reporting damage to the network. To coordinate this work, they entered new issues into a trouble ticket system; worked trouble tickets; and placed calls as appropriate. And as the Rex case shows, they had to remember a complex set of scripts and steps. Typically, an NOC worker would have four trouble tickets on the screen at the same time and would be entering data into any of these screens – while taking a call for a fifth ticket! This was complex work. As I watched them do this work, over and over, I noticed that they tended to use a basic set of resources.http://www.flickr.com/photos/maxwellgs/4267297275/
• #48: Here it is. Without this string of associated heterogeneous genres (or appropriate substitutes), the work wouldn’t get done. F1 notes provided a detailed history of the ticket; “winpops” provided a way to broadcast messages to the entire room; phone lists provided contact information within and without the company; and the list of active tickets let the worker know what to work on and how long it had been active. All five genres interconnected: workers could use any of these in combination with any of the others, not sequentially but jointly.Without all of these resources, workers couldn’t do their jobs.So what happens when one of the resources failed? Or when one of them was judged less useful or less portable than it should be?
• #49: Simple: They substituted.For instance, as you can see here, workers sent what they called “winpops,” or short text messages broadcast to all terminals in the NOC, with a program called “winpopup.” All workers could receive “winpops,” but only those at Windows 98 terminals could send them; those at the newer Windows NT terminals couldn't. So, for instance, when Jack was seated at a Windows 98 terminal, he would send “winpops”; but when he was at an NT terminal, he would instead shout to the entire room: “Ticket 17, CLEC!” How do I know that shouting at the room was an explicit substitution? Simple. At one point, Jack yelled: “26 is CLEC. Nathaniel? You gettin' my winpops?”Other people found substitutes too. For instance, Fred didn’t use winpops or yell at the room: he left handwritten notes at people’s desks while they were on the phone. You can also see other substitutions going on here too. So as you read across, you see the syntagmic dimension, the associations (AND) – the minimal set of resources that the NOC workers needed to get their work done. But as you read down, you see the paradigmatic dimension, the substitutions (OR) – the substitutes for those necessary resources. Sometimes those substitutes work differently from the originals, and sometimes they lead to innovations. For instance, Fred replaced a printed phone list with one that he worked up in a spreadsheet; Nathaniel liked this innovation and copied it. One other thing here. An STG allows you to detect substitutions, but also relative stability. And that lets us stop what could become an endless, recursive process of unpacking black boxes, that is, endlessly examining the components of each element. For instance, we can note that workers seemed to treat F1 notes in the same way, without substituting for parts of them, and thus we don't have to examine the narrative and categorical genres that make them up; we don't have to examine F1 notes themselves as an ecology. Instead, we can focus on the substitutions, which tell us about how workers had componentized their work and how innovations might change those components.Notice that regular work is an extraordinary achievement: with minimal training, the workers at the NOC were able to lean on this essential set of genres to perform good work. This essential set is fascinating because it has achieved a level of stability, and that’s a real achievement. But the unstable parts, the substitutions, are where the innovations tend to occur. That’s where the action is at.
• #50: These substitutions are worker innovations – like Jack yelling at the room or Fred reproducing a phone list in a spreadsheet. Often, these substitutions come in from other activities: people recognize a problem because they have solved a similar one elsewhere, so they import that solution, often in genre form, into the current activity. That is, the “homework economy” boomerangs, with people taking genres they learned at home or in other activities, substitute them for those in the current activity, and splice them in.
• #51: We can expand an STG further. Here’s an example. And in this example, we generate the STG from the Genre Ecology Model and the Communicative Event Model. The Communicative Event Model gives us a sequence of communicative events – and you can see that sequence in the columns of this expanded STG. The Genre Ecology Models for each step in the sequence gives us a minimal list of resources, displayed in each cell. And the rows represent the individuals or groups who are trying to execute the sequence, substituting resources as they go.You lose a bit of resolution from the other two models when you combine them into an STG like this one. But what you gain is a dashboard that allows you to see patterns of associations and substitutions. In the online reading, these associations and substitutions corresponded with different groups: you can see at a glance that people are approaching their work in different ways.So the STG is a third powerful heuristic, one that ties together the other two heuristics we’ve discussed. We begin to see patterns. But we can also coordinate perspectives with it.
• #52: We can use STGs at different levels.For instance, here's an STG based on Credits and Collections. I’m examininga single participant's work, using two different data sources (field notes from the observation and the post-observation interview). Notice that this STG helps us relate communicative events from the Communicative Events Modelto the genres from the Genre Ecology Model. And it helps us to see how our field notes differ from the participant's account. It helps us to triangulate the two data sources: we can see how closely they line up and where they disagree or are partial. See the italics in each cell: these are texts that are mentioned in just one account.
• #53: Now suppose we do the same thing for multiple participants. We can collapse the list of texts from both data sources into one list for each participant, then compare the participants -- and we begin to turn up similarities and differences in how individual participants work. Triangulating at this level helps us to do the following:- figure out which texts are "core" texts, the bare minimum for executing each communicative event- spot innovations that one participant uses and others don'tFor instance, in this table, Clara uses a text that the others don't use: a log of previous customer interactions. Does this log function as a substitute for some of the texts that others use, such as Arnold's spiral notebook? The STG helps us to spot differences and reexamine our data - including our copies of the spiral notebook and the log - to answer questions about how participants work differently. Through this triangulation, the STG helps us to catch innovations and workarounds, showing how these substitute for other texts.Again, it’s like a dashboard, but this time it helps us examine sets of resources across multiple participants.
• #54: If the organization is large enough, you may triangulate to spot differences in how groups do their work. Groups can be- participants doing the same work at different locations- participants taking on the same role at the same location and in the same workflow- participants at the same location, working in the same role, but with different characteristics (training, experience, access to technology)In this speculative example, a company has two offices, and as often happens, the offices have developed different ways of doing things due to different technologies, training, backgrounds, expectations, and innovations. A group-level STG can help you spot those differences as well. This table shows how two offices might handle the same communicative events differently - and how the second office has managed to use one text to substitute for many.
• #55: Remember that with the Genre Ecology Model and the Communicative Event Model, you can detect discoordinations, places where two different genres don’t seem to fit or where a sequence is often interrupted. As you map those models together in the STG, you can also map the discoordinations (in red), and these might lead you to see some interesting patterns. In particular, if you see that some associations are characterized by discoordinations, and some substitutions seem to eliminate those discoordinations, that’s a big deal.
• #56: This last case isn’t associated with a model, but it can give us insight into how the other models work. In particular, it let’s us examine where these workers come from, where they go, and where they might be picking up and moving around innovations in the form of genres, as well as how they circulate and interpret boundary objects.
• #57: The key word here is “quickly.” At this point in time, the telecommunications industry was expanding rapidly. So workers were being hired right and left, often with only a high school degree. As we’ll see in the next chapter, workers were not given much training, partly because they were being absorbed so rapidly. In addition, since Telecorp was expanding rapidly, it also acquired smaller telecomms and had to absorb their workers as well as their infrastructure.But they also circulated through quickly. Partly that’s because departments sometimes split into smaller, more specialized departments as the division of labor developed. Often it was because workers became bored with their job and made lateral transfers into other departments. As they did, they retained their knowledge of the previous department – and often they found that their former colleagues would still call on their expertise.Because telecommunications was expanding so rapidly, there were plenty of jobs available, and because Telecorp’s workers had to work closely with their counterparts in other telecommunications companies, they had plenty of contacts. So it’s not too surprising that workers also circulated out quickly, sometimes staying only a few months. Many of these worker would circulate among telecommunications companies. Turnover was high at Telecorp and “unreal” at the major regional telecommunications company, and workers would hop from one to the other, bringing the tools and practices they had learned at one worksite to the next. Furthermore, some workers (such as those in Long Distance Provisioning) went to seminars held by the long-distance telecomms. As these workers circulated in, our, through, and among telecomms, they brought, picked up, and modified texts, tools, practices, and innovations. Telecorp’s borders were fairly permeable.
• #58: Here’s an example from early in my research. I was observing people work in Customer Care Data Entry: a new functional group that had been formed to take on the data entry work that Customer Care didn’t have time to do. At Customer Care, phones rang constantly, and workers had to take down orders as quickly as possible. Only a few weeks earlier, they were also responsible for putting those orders into the database; now they emailed the orders to Customer Care Data Entry.The phones at Customer Care Data Entry were almost never used. Until one day Susan received an email, read it, fumed “She must have been on crack yesterday!” and called someone back. I was so intrigued that I went straight to her desk and listened to her side of the conversation. I couldn’t hear the caller speaking, but it was clear that Susan was instructing her. In fact, Susan was instructing her about accounting. That’s strange, I thought. Is there a connection between this new department and accounting? Then I realized that Susan was actually instructing her on how to use accounting software. But, I thought, isn’t Susan new to the company? What’s the connection between these two departments? I began imagining some hidden tangle of connections among different departments. Then, as she closed the phone conversation, Susan told the other person: Look, I quit that job two weeks ago. You have to stop asking me questions.Susan was still answering questions from her old employer, two weeks later! That’s when I realized that when you give everyone a phone and a terminal connected to the Internet, you can reconstitute previous networks. And once I realized that, I noticed the same thing happening within Telecorp: Workers would move from Customer Care to Sales or Long Distance Provisioning, but would still receive calls from their colleagues six months later!
• #59: Here’s another example. Ricardo was a supervisor at the CLEC switch. During our interview, he explained that workers in different functional groups tended to bring in specialized social languages and genres to help them enact that work. Of course, he didn’t use those terms. He said:“the other groups really don't understand how our part of it works. And I'm pretty sure that, you know, we don't understand how some of their stuff works. I mean, they start talking about the ASRs, the provisioners, and FOCs … I have no idea what they're talking about. Now, when I go out in the field and we work on something and we're seeing like an, you know, an AIS condition for a circuit and what have you, they don't understand what we're talking about. So sometimes we can actually word it a different way so they can understand what we're talking about. I would say the lingo is the main thing, main problem as far as why we get the communications wrong.”So Ricardo found it easier to talk to his counterparts at other companies than he did people in his own company. As a supervisor, though, he had to cross the borders in his own company, and he did that by learning at least bits and pieces of the functional groups with whom he had to communicate.
• #60: People like Ricardo are boundary crossers: people who can learn enough of another group’s social language to use their terms and concepts, and therefore can hook up with their expertise, activities, and kinds of work.
• #61: So at this point we have three different heuristics to apply to different cases. These are all based in aspects of genre theory, activity theory, and actor-network theory. They represent the theory team-up that I mentioned earlier in the presentation. How do we apply these to social media?
• #62: We already touched on this question in our first slide deck. As you may remember, we discussed the case of LinkedIn, which has been called “the old person’s social network.” And as I argued, we might find that we can’t understand social media use by looking at the genre by itself. We need to see how it connects with other genres.For instance, when I conducted a recent study on how freelancers work, the freelancers told me that they saw LinkedIn as part of a larger media strategy that included their business’ websites and other social media such as Facebook and Twitter, and connected with their use of email, conference calls, and the products of their work. That is, for them, LinkedIn was part of a larger ecology of genres that they had to deploy in order to carry out their activities. Without understanding these linkages, we don’t really understand the genre as a tool-in-use. With those linkages, we do. But we need to be able to examine how these genres actually connect – drawing on hard evidence, including observations of people’s use, interviews with those people, analytics, or examinations of artifacts these people used (such as marked-up printouts).
• #63: Turning to the Communicative Event Model, we may find some sequential relationships that aren’t evident by examining LinkedIn itself. For instance, this CEM shows a negotiation for an endorsement (which is similar to a letter of recommendation). Yes, LinkedIn supplies a mechanism for soliciting endorsements, but in this speculative case, we may find that high-stakes endorsements tend to follow a specific pattern: a couple of initial conversations, then an emailed first draft of the endorsement, which the applicant marks up and turns into an attachment; then two subsequent drafts before they settle on the text of the endorsement. Finally, the endorser posts the endorsement.Again, this is a speculative example. But suppose we examine the backstage work of developing a LinkedIn endorsement and we find a fairly consistent pattern – a sequence - across at least some users in high-stakes endorsements.
• #64: Once we complete the Genre Ecology Models and Communicate Event models, we can identify the minimum resources (genres) that people use to complete this sequence. We can see some local differences and some substitutions, but we can also see an overall structure. Let me emphasize that these have to be based on actual data on how people actually work: observations, interviews, analytics, artifact analysis, etc. These aren’t design aids that describe how people should work; they’re analytical tools that describe how people actually do work. Here, I’ve just compared three users’ sequences and resources. But if you compare, say, 20 or 30 of these, you may see some commonalities within the STG, and these may help you to identify emergent groups – just as you might identify emergent groups through the process of translation.
• #65: For instance, you might find that students who are just coming onto the job market are more likely to have face-to-face meetings with their endorsers – because those endorsers tend to be professors on campus. And they might work on paper more because their elderly professors are less likely to work electronically. But people who have been out in the workforce for several years might seek endorsements from former employers in various locations, and of various ages, leading them to substitute different genres.Again, this case is speculative, but it shows how you might use this heuristic to generate better understandings of your own social media cases. You should be able to detect differences that make a difference.
• #66: Now, let’s map discoordinations. Again, these are illustrative rather than based on an actual case, but suppose you’ve detected discoordinations at various points. Once we map these to the STG, we begin to see patterns, and those patterns help us to better understand where the sequences and resources are breaking down.
• #67: For more detailed instructions, see my book Topsight.
• #68: For more detailed instructions, see my book Topsight.
• #69: For more detailed instructions, see my book Topsight.