Topsight > The publishing process

It seems like forever since I first announced that I was planning to publish Topsight. But I get my final proof from Amazon CreateSpace in the mail tomorrow, and I've viewed a draft of the Kindle Direct Publishing version already. So I'm hoping that I can pull the trigger midweek—and I'll announce it here when I do.

While we wait, here's some observations about the self-publishing process. I've already talked about why I decided to self-publish this book; here, I'll talk about what the process looks like.

The printed book: Amazon CreateSpace
I chose to use Amazon CreateSpace (ACS) because Amazon has a great distribution network, because I already have an author page, and because self-publishing is simple there. ACS is a print-on-demand platform, which means that each book is individually printed. That means higher per-book printing costs, but I don't have to worry about volume; extra copies won't be sitting in warehouses waiting to be pulped.

ACS prints the book, but technically, I'm the publisher. That means that Amazon takes a percentage of each sale for printing and distribution, and I get the rest. In practical terms, I can set my own royalties. (But I'm setting the price fairly low so that everyone can enjoy Topsight.)

In practical terms, I supply ACS with two files:

• A cover PDF
• An interior PDF

ACS supplies Word templates for the interior, and also supplies design services for an extra fee. However, I opted to hire a graphic designer, copyeditor, and production person out of my own pocket to produce the print-ready PDF. I also rented Adobe InDesign (about $99 a month) to implement final changes by hand. These costs added up.

The designer and production person also developed the cover. ACS provides a specific formula for calculating the width of the spine, based on the paper you choose. 

The range of choices and services is impressive here. You can choose book formats as small as 5"x4" (the size I chose) or select a custom size; you can hire Amazon to design the cover and interior or do it yourself; you can use their Word templates. You can even hire them to do copyediting.

Once the PDFs were ready, I uploaded them and ACS automagically identified potential PDF errors. The cover went though fine, but I had to correct several errors involving headers and text that ran slightly into the margins. Each error was highlighted in the online view—I was impressed with how thoroughly error checking was handled and how easy it was to understand the errors.

After a few tries, I generated an error-free PDF and proceeded to the next step: a human being checked the document. It took less than 24 hours. 

At that point, I had the option to order a proof or just launch the thing. Although I was impatient, I ordered the proof (about $5) and paid a premium (about $25) to deliver it as soon as possible (5 days).

While awaiting the proof, I was guided through the pricing process. ACS gives several options here too, each of which might involve extra fees or affect royalties. Despite the extra cost, I opted for expanded distribution channels so that libraries and bookstores could order it ($25) and also opted to allow printing in different countries (a royalty fee). 

Once that was done, I was guided to Kindle Direct Publishing for the option of creating a Kindle book.

The Kindle book: Kindle Direct Publishing

Clicking a button transfers the cover and interior PDFs and metadata to Kindle Direct Publishing (KDP). KDP is a different animal. For one thing, you have different, more simplified formatting options. For another, you can't use the same ISBN (and you don't need an ISBN at all.) Third, distribution channels are more flexible because you're not moving paper around, just bits.

Two of these are headaches.

First, the formatting. Kindle books are modified, simplified HTML. That means that an InDesign file doesn't translate directly to Kindle. The easiest thing is to build a Word file, then convert it. In fact, if you read Kindle publishing guides, they claim that you have to convert the final version to HTML; fortunately this is no longer the case.

To handle the conversion, I did the following:

1. Went into InDesign's Story Editor, copied the body, and pasted it into a Word file.
2. Went into the Story Editor again to copy the front matter, then pasted it into the same Word file.
3. Went through the entire InDesign document, identified all materials outside the main story (tables and figures), copied them into Preview, saved them as JPEGs (per the Kindle publishing guide), then placed them each into the Word file.
4. Reformatted as appropriate, including deleting page numbers from the Table of Contents, List of Tables, and List of Figures.
5. Discovered that the procedure for autogenerating TOC hyperlinks doesn't work on Word for Macintosh.
6. Deleted all but the first level of the TOC, then hyperlinked these by hand.

I then uploaded the Word file to KDP. Within minutes, it gave me a preview on a simulated Kindle Fire screen. (You can switch orientation or simulate a Kindle HD, second-generation Kindle, Kindle Paperwhite, iPad, or iPhone screen.) I also downloaded a Kindle version to view on my Kindle and my Nexus 10. 

I'm glad I did, since I found some conversion errors. For instance, I discovered that I had to save the graphics at a higher resolution and set them to the proper size. On the whole, though, the process was tedious rather than challenging; I probably spent about six hours on the conversion.

It's worth noting that if I had used the ACS Word template, the conversion would have probably been even less painful. If I do this again, I'll probably go that route.

Once I was satisfied with the Kindle version, I was given the option to take 35% royalties (which would allow me to set any price) or 70% royalties (which limited me to charging $9.99 and was available only in some countries.) I tried various configurations, then set a price.

I'm also not entirely happy with how graphics render in the Kindle version, so I've made some of the graphics available from the book's website; I'll likely add more as I go.

Lessons learned

I'm really impressed with how easy it is to publish in both ACS and KDP. It's not for the faint of heart, and it involves more detail work than I like to do, but it has allowed me to turn out a book at relatively low cost, quickly, while retaining creative control. And that's been tremendously exciting.

What would I do differently next time? I would consider developing the PDF using one of the existing Word templates rather than InDesign. That's not because the product would look better—I think it wouldn't—but it would be quicker, easier, and cheaper to produce, as well as being easier to convert.

Overall, though, I'm very happy with the experience. Looking forward to seeing the proof. 

Reading :: Networked

Networked: The New Social Operating System
By Lee Rainie and Barry Wellman

I have been meaning to review this book for a while—I probably finished it in July—but I have been put off by the sheer amount of work it deserves. Let's see if I can do it justice.

In this book, the authors explore how networks among people have transformed how we connect with each other, both personally and electronically.

Chapter 1 summarizes the book's main argument pretty well. People "have become increasingly networked as individuals, rather than being embedded in groups. In the world of networked individuals, it is the person who is the focus: not the family, not the work unit, not the neighborhood, and not the social group" (p.6). They term networked individualism "an 'operating system' because it describes the ways in which people connect, communicate, and share information" (p.7). Its characteristics are

• personal
• multiuser
• multitasking
• multithreaded (p.7).

It requires new strategies and skills for solving problems (p.9). And it involves a "triple revolution":

• We can reach beyond tight groups (p.11)
• We have new communication power and information-gathering capabilities (pp.11-12)
• Information and communication technologies (ICTs) are a "bodily appendage," always accessible (p.12).

Here, the authors italicize their main points; I'll just bullet them:

• "Many meet their social, emotional, and economic needs by tapping into sparsely knit networks of diverse associates rather than relying on tight connections to a relatively small number of core associates." (p.12)
• "Networked individuals have partial membership in multiple networks and rely less on permanent memberships in settled groups" (p.12)
• "A key reason why these kinds of networks function effectively is that social networks are large and diversified thanks to the way people use technology" (p.13)
• "The new media is the new neighborhood" (p.13)
• "Networked individuals have new powers to create media and project their voices to more extended audiences that become part of their social worlds" (p.13)
• "The lines between information, communication, and action have blurred. Networked individuals use the internet, mobile phones, and social networks to get information at their fingertips and act on it, empowering their claims to expertise (whether valid or not)" (p.14)
• "Moving among relationships and milieus, networked individuals can fashion their own complex identities depending on their passions, beliefs, lifestyles, professional associations, work interests, hobbies, or any number of other professional characteristics" (p.15)
• "At work, less formal, fluctuating, and specialized peer-to-peer relationships are more easily sustained now compared with the past, and the benefits of boss/subordinate hierarchical relationships are less obvious" (p.15)
• "The organization of work is more spatially distributed" (p.16)
• "Home and work hae become more intertwined than at any time since hordes of farmers went out into their fields" (p.16)
• "While ICTs have shattered the work-home dividing line, they have also breached the line between the private and public spheres of life" (p.17)
• "New expectations and realities about the transparency, availability, and privacy of people and institutions are emerging" (p.17)
• "In the less hierarchical and less bounded networked environment—where expertise is more in dispute than in the past and where relationships are more tenuous—there is more uncertainty about whom and what information sources to trust (p.18).

With that summary in mind, the authors dive into the rest of the book.

In Chapter 2, "The Social Network Revolution," the authors discuss social networks (in the sociological sense, that of relationships among individuals) (p.21). They identify several major trends:

• Widespread connectivity (pp.22-27), including more ground and air travel, more telecommunications and computing, and more commercial and social interconnectedness due to trade.
• Weaker group boundaries (pp.27-30), due to changes in family composition, roles, and responsibilities; the rise of ad hoc, informal networks over structured and bounded voluntary organizations; and the fragmenting of media markets.
• Increased personal autonomy (pp.31-34), due to increased work flexibility; falling barriers related to ethnicity, gender, religion, and sexual orientation; and the rise of IRAs and the decline of defined benefit pensions.

Although people still think they're in groups, the authors say, they're really in networks (p.35). In networked sociality, boundaries are more permeable, interactions occur with diverse others, hierarchies are flatter and more recursive (p.37). The authors provide a table comparing group-centered society with networked individualism (p.38).

In Chapter 3 and 4, "The Internet Revolution" and "The Mobile Revolution," the authors turn to the rise in Internet and mobile connectivity, discussing how these changes connected us in different ways. In particular, mobile devices make us hyperconnected (p.95) and hypercoordinated (p.99), and norms have not caught up to practice (p.105). For instance, "mobile hyperconnectivity in fuzzily bounded public-private space" can lead to problems such as private conversations overheard in public spaces as well as questions of who should and shouldn't be in the loop.

In the next section, the authors address how networked individualism works. In Chapter 5, "Networked Relationships," they describe communities as fluid personal networks, noting a post-WWII shift from door-to-door to place-to-place communities (p.122). With the triple revolution, we're undergoing another shift, from place-to-place to person-to-person (p.123). "Their networks are sparsely knit, with friends and relatives often loosely linked with each other" (p.124). And the authors suggest thinking in terms of "a networked self: a single self that gets reconfigured in different situations as people reach out, connect, and emphasize different aspects of themselves" (p.126). In their personal networks, communities become sparsely knit—most members aren't directly connected—and specialized—different network members help each other with different types of support (p.135).

In Chapters 6 and 7, "Networked Families" and "Networked Work," the authors note similar changes in the family. Lifelong marriage has gone the way of lifelong employment. Work involves multiple teams and multiple purposes (pp.171-172). Work trends include 

• globalization of work, consumerism, travel (p.172)
• a shift from atom work to bit work (p.172)
• the internet and mobile revolutions (p.173)
• the ability to work at a distance (p.173)
• the resulting trend toward mobile work using primarily laptops and smartphones (p.173)

These trends especially affect workers whose organizations are "permeable"; workers directly connect with each other, and their work structure is "more flexible, laterally coordinated, team based, and boundary spanning" (p.177). Information is the key asset, and its flow is critical for success (p.178). Networked organizations have familiar characteristics:

People often work in multiple projects with different teams. This allows firms to assemble ad hoc teams with diversified talents and perspectives. As workers shift among teams, they can develop cumulatively larger networks of expertise that are "glocal," with both local interactions and global connectivity. Instead of submitting to the traditional hierarchical ode of authority, workers have more discretion about the work they jointly accomplish. Networked organizations have advantages for boundary spanning, as employees work and network between work groups and organizations—and at times, between continents. (p.181)

In these organizations, the structure tends to be flatter, with fewer reporting relationships, and more informal (p.182).

Networked work also involves more work from home (p.186).

Let's leave it there. The authors have plenty more to say: about networked creators (Ch.8), networked information (Ch.9), how to thrive as a networked individual (Ch.10), and the future of networked individualism (Ch.11). But I'm most interested in the analysis above, which is so worthwhile that I regret sitting on this review for so long. If you're interested in networked individualism, certainly take a look at this book.

Reading :: Explorations in Information Space

Explorations in Information Space: Knowledge, Actor, and Firms
Edited by Max H. Boisot, Ian C. MacMillan, and Kyeong Seok Han

I just reviewed Boisot et al.'s Collisions and Collaboration, and in that review I discuss Boisot's I-Space in detail. This collection further discusses and applies I-Space.

The book's purpose is "to provide some theoretical perspective on the nature of organizationally relevant knowledge and to indicate the kind of research that might generate empirically testable hypotheses and hence to further the development of a knowledge-based theory of the firm" (p.6). The I-Space is central to that theorizing, meant to provide insight into "the nature of information and knowledge flows in any system" (p.7). The authors assume that "the speed and extent to which information diffuses within a population of agents is a function of how far that information has been structures" and that "information only becomes knowledge if it gets internalized and becomes part of the recipient's expectational structure—that is, if it affects the recipient's belief structure taken as disposition to act" (p.7).

For me, the interesting stuff started in Chapter 4. The authors start by claiming that "How far knowledge gets articulated determines how speedily and extensively it can be shared" (p.109). Although economics has taken the default assumption that markets underlie all other forms (p.109), Boisot et al. argue that "the heterogeneity of organizations, not their homogeneity, had to be taken as a default assumption when analyzing organizational strategies" (p.110). Since organizations are characterized by heterogeneity, articulation and sharing are thus impeded, and so "transaction costs and benefits remain heavily stacked against the kind of articulation of knowledge that would be required to make the choice of markets either ubiquitous or even symmetric with that of organizations" (p.110). So, they conclude, "in the beginning there was the organization" (p.110).

Given this assumption, the authors outline E-Space (epistemic space), with the axes of codification and abstraction. At the most uncodified, concrete corner, we get embodied knowledge; at the opposite corner, we get abstract symbolic knowledge; and in the middle, we get a band of narrative knowledge (p.123). The authors then add the axis of diffusion in order to produce the familiar I-Space—and we now see that embodied knowledge tends to be the least diffused, while abstract symbolic knowledge tends to be the most diffused (p.131). That is, the more well-compacted and abstract knowledge is, the more mobile and fluid it tends to be. Yet at the same time, codification and abstraction involve data losses (p.131).

Boisot et al. claim implications for economics. For our purposes, the most interesting one is that, below a certain threshold of codification and abstraction, a shared context between sender and receiver favors hierarchies rather than markets (p.136).

Chapter 5 continues exploring the nature of organizations. Here, Boisot discusses the evolution of bureaucracies from Gemeinschaft (local, personalized) to Gesellschaft (large, ubiquitous, impersonal) (p.147). Boisot pegs this shift to the printing press, which provided information storage and diffusion (p.148). Similarly, Boisot argues, modern ICTs might favor options other than bureaucratic hierarchies and competitive markets to other options, such as clan-like networks (p.150).

To make this argument, Boisot discusses bureaucracies, markets, fiefs, and clans in the same terms that he discussed them in Collisions and Collaboration. He adds that we can think of three types of complexity:

• Codification: Descriptive complexity
• Abstraction: Computational complexity
• Diffusion: Relational complexity (p.155)

"We hypothesize that building effective institutional structures in market and clan regions widens the complexity region and helps to stabilize it while simultaneously reducing the size of the region in the I-Space from which they chaotic regime can 'attract' transactions—that is, its basin of attraction" (p.159). Furthermore, modern ICTs shift the diffusion curve because of two effects:

• The diffusion effect: "at any given level of codification and abstraction, more information will reach more people per unit along the diffusion scale than hitherto" (p.160)
• The bandwidth effect: "any given proportion of the population located at some point along the diffusion scale can be reached at a lower level of codification and abstraction—that is, at a higher bandwidth—than hitherto" (p.160). 

In fact, "the rightward shift in the diffusion curve appears to privilege both market institutions over bureaucratic ones and clan-like institutions over fiefs" (p.161). Evidence for markets-over-bureaucracies: "the average size of firm in the United States has actually been falling over the past thirty years" due to outsourcing (p.161). Evidence for clans-over-fiefs: "the emergence of interpersonal networks and relational contracting between firms" (p.161). 

I don't think I've sufficiently assimilated Boisot's work to relate it well to other frameworks I've examined. But I am really intrigued by this line of reasoning, particularly Boisot's consideration of how ICTs change the landscape of organizations. If you're similarly intrigued, take a look. 

Reading :: Collisions and Collaboration

Collisions and Collaboration: The Organization of Learning in the ATLAS Experiment at the LHC
Edited by Max Boisot, Markus Nordberg, Said Yami, and Bertrand Nicquevert

I picked this book up primarily because it was one of the few recent books out there to use the term "adhocracy"—a term that I'm currently researching for a project. But it turns out that Boisot is quite well known for his writings on information and strategy (though not so well known in the circles where I typically read and publish, alas). After reading this book, I can understand why: his I-Space framework is useful for thinking through the relationships between organizational characteristics and the circulation of information.

Let's talk about I-Space first, then get back to the book project.

I-Space is depicted as a three-dimensional space, a cube with three axes:

• Codification: from very uncodified to very codified information. "Codification is indexed by the amount of data-processing required to distinguish between categories and to assign events to these" (p.33).
• Abstraction: from very concrete to very abstract information. "Abstraction is indexed by the number of categories required to perform a given categorical assignment." (p.33)
• Diffusion: from very concentrated to very diffuse. Here, we're talking about the degree to which information can be diffused over time. "The greater the degree of codification and abstraction achieved for a given message, the larger the population of agents that can be reached by diffusion  per unit of time." (p.34)

Within this three-dimensional space, Boisot et al. say, we can map a social learning cycle. This cycle follows six phases:

1. Scanning
2. Codification
3. Abstraction
4. Diffusion
5. Absorption
6. Impacting (p.39)

Mapped in I-Space, the social learning cycle typically looks like an S-curve. But it looks different for each organization, since each organization's I-Space tends to be different—that is, different organizations have different characteristics of codification, abstraction, and diffusion. Indeed, "to the extent that individual agents can each belong to several groups, each locatable in its own I-Space, they will participate in several SLCs that interact to form eddies and currents" (p.38).  

In fact, if we map parts of the I-Space to cultures and institutional structures, we find that different structures have different "homes" in the I-Space:

Fiefs. These thrive in situations with concrete, undiffused, uncodified information. Characteristics:

• "Information diffusion limited by lack of codification to face-to-face relationship." 
• "Relationships personal and hierarchical"
• "Submission to superordinate goals"
• "Hierarchical coordination"
• "Necessity to share values and beliefs"

Bureaucracies. These thrive in situations with abstract, undiffused, codified information. Characteristics:

• "Information diffusion limited and under central control"
• "Relationships impersonal and hierarchical"
• "Submission to superordinate goals"
• "Hierarchical coordination"
• "No necessity to share values and beliefs"

Markets. These thrive in situations with abstract, diffused, codified information. Characteristics:

• "Information widely diffused, no control"
• "Relationships impersonal and competitive"
• "No superordinate goals—each one for himself"
• "Horizontal coordination through self-regulation"
• "No necessity to share values and beliefs"

Clans. These thrive in situations with concrete, diffused, uncodified information. Characteristics:

• "Information is diffused but still limited by lack of codification to face-to-face relationship." 
• "Relationships personal but non-hierarchical"
• "Goals are shared through a process of negotiation"
• "Horizontal coordination through negotiation"
• "Necessity to share values and beliefs" (p.49)

These different institutional types are similar to those of Ronfeldt's TIMN, Cameron and Quinn's Competing Values Framework, and Mintzberg's categories of structures, but they're defined via the three axes in the I-Space. Essentially, Boisot et al. are arguing that certain institutional structures thrive because they best adapt to specific conditions in a given I-Space. 

Yet they also posit that modern information and communication technologies (ICTs) are shifting the curve, making it easier to diffuse messages and thus to reach more people at a lower level of codification and abstraction (pp.50-51). This shift is a big deal. Up to this point, to be widely diffused, knowledge had to be highly codified and abstracted—something that naturally favored bureaucracies and markets, which are set up for those conditions. But due to ICTs, the shift in the curve might favor clans as well as markets, to the comparative detriment of bureaucracies (p.51). "Over time, this is likely to favor clan-like network cultures that have a tendency to closure ... rather than the more open market processes" (p.51).

So there's the I-Space framework. In this collection, Boisot (who is listed as an author on every chapter) and his coauthors apply this framework to the ATLAS collaboration, a complex multunational scientific organization that uses ATLAS, a high-energy physics detector at CERN; it forms part of the Large Hadrion Collider (LHC) (p.8). This organization coordinates without central managerial authority (p.55). 

In Chapter 3, the authors examine the ATLAS collaboration as an adhocracy, drawing from Mintzberg to identify the structure and then locating it "to the right of the region in the I-Space labeled 'clans'" (pp.74-75)—that is, further diffused than clans are. "As a geographically dispersed, loosely coupled adhocracy, the ATLAS Collaboration extends beyond the bounds of clan cultures as conventionally understood. Yet ... it remains driven in large part by clan values and practices" (p.74). Later, in Chapter 4, the authors add: 

As a loosely coupled adhocracy, ATLAS operates to the right of clans along the diffusion scale of the I-Space, in the region where, on account of the lack of structure of the knowledge being exchanged and the large number of interacting players, things could quickly become chaotic. The collaboration remains culturally cohesive, however, held together by shared commitments, norms, and a common focus on an infrastructure of boundary objects that over time deliver a clan totem: the detector itself. (p.114).

Boisot et al. credit modern ICTs for the success of ATLAS' adhocracy: "It is mainly the bandwidth effect [in which more people can be reached per unit of time] that makes giant adhocracies like the ATLAS Collaboration possible, and that is likely to give birth to a new scientific culture" (p.257). For instance, such adhocracies can involve "a re-personalization of science, a move away from the impersonality of anonymous peer reviewing and journal publications as the only way to get on and towards the building-up and exploitation of personal networks" (p.263). Via ICTs, "the culture of clans can be extended to more loosely coupled and geographically scattered adhocracies" (p.264).

Let's inject a bit of caution here. Many of the authors are involved in ATLAS or other aspects of CERN; this collection is not (exclusively) an outsider's account and shouldn't be considered a set of studies per se. In tone, the contributions are often a bit congratulatory.

But on the other hand, the collection does a great job of explaining and illustrating I-Space. If you're interested in how organizations work, or how I-Space works, this book is a good solid introduction with some intriguing analysis.

Reading :: Writing Ethnographic Fieldnotes

Writing Ethnographic Fieldnotes, Second Edition
By Robert M. Emerson, Rachel I. Fretz, and Linda L. Shaw

I've been meaning to read this book for a while. It didn't disappoint—although it's not a perfect book.

First the plusses.

Field notes are an essential part of ethnography, the main way of collecting data and beginning the analysis. And like any essential tool, field notes have developed into several variations, with different strengths and applications. Yet in many ethnographic textbooks, the discussion of field notes is relatively underdeveloped. Yes, we're told to write things down. But what things? When? How? How do we process field notes? How do we turn them into an analysis? Ethnographers and other qualitative researchers can generate an enormous amount of text, but may not be consistent enough to examine the same thing over time, or may not be organized enough to extract consistent insights from that writing.

That is, field notes don't simply involve writing down what the ethnographer sees, hears, and experiences. There's enough in a minute of observation to fill a book if one were meticulous enough. Field notes have to interpret and record what the ethnographer believes is the most important information, and they have to do this consistently in order to generate comparable data over time. That's tough.

In this book, the authors systematically address various aspects of field notes—from jotting to creating scenes, from stylistic considerations to member meanings, from coding to memoing, and finally to inserting fieldnotes into an ethnography. At each point, the authors provide plentiful examples and discuss the different sorts of choices ethnographers make as they write.

And that brings us to the minus—the drawback to the book. Field notes tend to be detailed, and the book similarly dives into the details of producing and processing them—often too quickly, without doing enough to surface and signal the overall structure of each chapter. I had to read each chapter with one finger on the first paragraph, flipping back periodically to remind myself what these particular details were meant to address.

But that's a relatively small issue. If you are interested in learning more about field notes, put Post-Its on the appropriate pages and dive into this book.

Topsight > Triangulation tables

In previous posts in this series, I've discussed two meso-level analytical constructs, two constructs for making sense of what we see minute-by-minute in people's work. Handoff chains help us to envision regular sequences, while resource maps let us see the connections among the information resources that people use.


Think of your research site as a football game. In handoff chains, the camera follows the ball, tracing through the series of handoffs and tosses that move it downfield. In resource maps, the camera follows the game, watching systemic dynamics and tactical changes as players and artifacts all over the field continuously reconfigure themselves.

Can we follow the ball and the game? Can we find a way to coordinate these two models? Sure: That's what we use triangulation tables to do. They allow us to triangulate data: to compare the stories that we get from different sets of data in order to make sure they agree.

Triangulation tables are based on Bruno Latour's sociotechnical graphs, but they've been adapted to mesh together what we learn from handoff chains and resource maps. For the messy details, see the paper that Zachry, Hart-Davidson and I put together a few years ago:

Spinuzzi, C., Hart-Davidson, W., & Zachry, M. (2006). Chains and ecologies: Methodological notes toward a communicative-mediational model of technologically mediated writing. SIGDOC  ’06: Proceedings of the 24th annual international conference on Design of communication (pp. 43–50). New York, NY, USA: ACM Press.

You can also see it at work in my book Network.

The basic idea is pretty simple: we put together a series of tables or matrixes that relate the chain of sequences to the resources used at each point in the sequence. We start with the individual visit, then expand to the group, then to larger units.

In our implementation, triangulation tables are tables in which 

• columns represent communicative events from the handoff chain
• rows represent different points of comparison - different data sources, different participants, or different groups
• cells contain information resources that are used for a given communicative event within a given point of comparison

For instance, here's a triangulation table in which the researcher examines a single participant's work, using two different data sources (field notes from the observation and the post-observation interview). Notice that this table helps us relate communicative events from the handoff chain to the resources from the resource map. 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.

Table 1. A triangulation table for a single participant.

	Communicative events
	Prepare for call	Contact customer and discuss bill	Record notes on call
Arnold - Field notes	collections list, annotations on collections list, database screen for customer, database screen for customer's collections information	Phone call to customer, collections list,database screen for customer's collections information	database screen for customer's collections information, fax cover sheet, sticky note, collections list
Arnold - Interview	collections list, annotations on collections list, bankruptcy notices, spiral notebook,phone calls from coworkers	Bills, phone call to customer	collections list, annotations to collections list, database notes, database screen for customer

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't

For instance, in Table 2, 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 triangulation table 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 table helps us to catch innovations and workarounds, showing how these substitute for other texts.

Table 2. A triangulation table for multiple participants.

	Communicative events
	Prepare for call	Contact customer and discuss bill	Record notes on call
Arnold	collections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy notices, spiral notebook, phone calls from coworkers	Phone call to customer, collections list, database screen for customer's collections information, bills	database screen for customer's collections information, fax cover sheet, sticky note, collections list, annotations to collections list, database notes, database screen for customer
Bill	collections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy notices	Phone call to customer, collections list, database screen for customer's collections information, bills, spiral notebook of call log	database screen for customer's collections information, collections list, annotations to collections list, phone call to supervisor
Clara	collections list, annotations on collections list, database screen for customer, database screen for customer's collections information,log of previous customer interactions	Phone call to customer, collections list, database screen for customer's collections information, log of previous customer interactions	database screen for customer's collections information, collections list, annotations to collections list, log of previous customer interactions

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)

For instance, if a company has two offices, it's common for the offices to develop different ways of doing things due to different technologies,  training, backgrounds, expectations, or innovations. A group-level triangulation table can help you spot those differences as well. Table 3 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.

Table 3. A triangulation table for different groups.

	Communicative events
	Prepare for call	Contact customer and discuss bill	Record notes on call
Group A	collections list, annotations on collections list, database screen for customer, database screen for customer's collections information, bankruptcy notices, spiral notebook, phone calls from coworkers	Phone call to customer, collections list, database screen for customer's collections information, bills	database screen for customer's collections information, fax cover sheet, sticky note, collections list, annotations to collections list, database notes, database screen for customer
Group B	collections list, customer folder with contact information and last bill	Phone call to customer, customer folder with contact information and last bill, calendar	customer folder with contact information and last bill, Word template, email

The triangulation table helps you to easily relate information from the other two analytical constructs and spot differences. It's a way to manage complexity so you can get a handle on the meso level. Which is great, because we're almost ready to move to the micro level—the level of habits and reactions. More on that soon.

Topsight > Advance praise for Topsight

As I work my way through the final revisions for Topsight, I wanted to share some of the advance praise I received from two readers—one from industry and one from academia. Like me, they're excited about the potential for this book.

Topsight is a proven, structured way to uncover and analyze the information flow in a process, department or organization. In contrast to many user-centered methods, it goes beyond the user and the screen to expose the work itself, identifying the parts that are broken and the connections between the users, their tools and their tasks. Topsight is ideal for large-scale, strategic design work and this book is required reading for anyone wanting to build a successful social platform, intranet or collaboration tools.

—Fredrik Matheson, Manager, Social Computing & Collaboration Group, Bekk Consulting AS

You may think you don't need to know much about doing fieldwork to manage change in your organization, but Clay Spinuzzi shows you why it just might be in your interest to learn about it! If you use the methods in this book, you'll learn where your communication strategy is working, where it could improve, and where you need additional information to make effective changes. In Topsight, Clay Spinuzzi presents a series of inquiry moves that anyone interested in organizational change can use. The methods are powerful, and they have been honed in over a decade of research experience and many peer-reviewed publications. But Spinuzzi presents them here for the first time as a straightforward and clear process for learning where your organization—and your people—can communicate more effectively. I believe those who think about communication practices in groups and organizations—as researchers or managers or practitioners—will find valuable insights and helpful tools in Topsight.

—William Hart-Davidson, Associate Professor of Rhetoric & Writing and Director of the Rhetoric & Writing Graduate Program, Michigan State University

Topsight > Using Topsight to teach a class

I developed Topsight for several audiences: consultants, people who want to change their organizations, people who need a gentle introduction to field research in organizations, graduate students. But in particular, I was thinking of my own undergraduate students in the course I often teach, Designing Text Ecologies.

The link goes to the spring 2013 version of the course. And I'm excited that I'll be using Topsight for that course. You can follow the link for the particulars, including the projects and the pacing. But if you're thinking about using Topsight for your own graduate or undergraduate course, here's a template for a 13-week course that might be helpful:

Week 1: Field studies and topsight (Preface, Ch.1)
Week 2: Developing a study design; building in protections (Ch.2-3)
Week 3: Gaining permission; preparing to study (Ch.4-5)
Week 4: Introducing yourself to participants (Ch.6)
Week 5: Observing; interviewing (Ch.7-8)
Week 6: Collecting artifacts and other sorts of data (Ch.9-10)
Week 7: Navigating data: triangulating and coding (Ch.11-12)
Week 8: Reporting progress: The interim report (Ch.13)
Week 9: Introduction to the analytical models; resource maps; handoff chains (Ch.14-16)
Week 10:Triangulation tables; breakdown tables (Ch.17-18)
Week 10: Activity systems and activity networks (Ch.19-20)
Week 11: Topsight tables; describing systemic issues (Ch.21-22)
Week 12: Turning findings into recommendations; writing the recommendation report (Ch.23-24)
Week 13: Turning recommendations into new solutions (Ch.25)

Topsight > I just looked at the proofs for the book...

... and I got excited all over again. I'm really thrilled that this book is coming together. Part of what I'll be doing over Christmas break is to go through the proofs and identify the final tweaks so that this book will be professional-grade.

Some of you have also contacted me in various ways—on Twitter, Facebook, Google Plus, email, and even face-to-face—to express interest. Thank you.

Although I hoped to get Topsight uploaded to Amazon CreateSpace by the end of 2012, it looks like it'll happen in early 2013 instead, due to some tweaks that still need to happen. It's this last mile—making sure the footers are right, watching out for widows and orphans, adjusting page breaks—that slows things down, but that also gives the book that finished, professional look.

In the meantime, I'll keep blogging and uploading content to the Topsight page. If you're interested in Topsight, please do keep watching this space—and if you know others who are interested, point them this way.

Topsight > Resource maps

One analytical construct that I discuss quite a lot in Topsight is something I call "resource maps." The name might be unfamiliar, but I've been discussing resource maps since 1997 under another name: "genre ecologies."

Why the name switch? "Genre ecologies" gets at the theoretical aspects that are important to academics. But they take a lot of explanation for non-academics. The concept of genre itself takes a lot of unpacking. But I've found that when I talk about mapping information resources, people can more easily grasp what's going on—and are sometimes more open to seeing unconventional or idiosyncratic resources as part of a system.

Let's take the classic example I use in my first book. Various people, in various locations, working in various organizations, all struggle when trying to use a text-based information system in conjunction with a street map. That's a classic usability problem, right? But a subset of people find ways to route around those problems. One copies down information onto a sticky note and keeps it in a folder. Another photocopies parts of his map. And so on. For these people, the information system doesn't have a usability problem, because they've successfully added an information resource that shores up the weaknesses of the current set of resources.

In some cases, these systems tend to standardize. For instance, in my second book, I describe how collections workers for a telecommunications company take a printout of people who are late on their payments, annotating it to turn it into both a checklist (who do I call next?) and a record (when I called this person, did I talk to them, leave voice mail, or what?). Even though these people all told me that they didn't learn this annotation system from anyone else, they were able to read and understand each others' checklists when necessary.

At the same time, these systems tend to have components that can be borrowed from anywhere—previous jobs, personal lives, other organizations, other domains—piled, sometimes haphazardly, in a heap of information resources. Since they come from different places, these information resources sometimes assume very different things and follow very different logics. And those mismatched resources sometimes develop disruptions.

Tracking these resources—again, not abstractly, but in the minute-by-minute, meso-level ways that they're used by actual people—can help you gain a detailed understanding of how complex the work is, how information flows around the organization, and where things go wrong. And it's a lot easier to track them if you map them out like this:

Here, each box represents an information resource that was actually observed during a field visit. The lines indicate points at which two or more information resources were observed being connected. For instance, if you see someone looking at his notebook when filling out a dialog box, you can connect them with a line. But if you never see him using the dialog box in conjunction with a folder, you don't.

Observation is crucial here. People connect information resources in a lot of different ways, including:

• juxtaposition (two information resources attached to or overlapping each other)
• placing (two information resources placed side by side, in a stack, or in regular places)
• annotation (writing or altering an information resource)
• transfer (using one information resource as source for filling in another)
• modeling (using one information resource as a model for another)
• reference (using one information resource to interpret or operate another)

And they don't always tell you about these connections. Some are too habitual, others seem too obvious (to them), and still others can seem petty or even embarrassing to them (few people will say that a sticky note is the linchpin of their work). But you need to be able to map them if you're going to gain topsight.

Resource maps and handoff chains are two important ways to analyze the minute-by-minute, meso-level interactions you'll observe in organizations, and I discuss them extensively in Topsight. They're two ways of looking at the same information resources. But they need to be connected. Soon, I'll discuss how to connect them.

Topsight > Handoff chains

As I wait for the production to finish on my new book Topsight, I've been discussing some of the analytical constructs that we can use to better understand aspects of work. Until now, I've been looking at macro-level constructs: activity systems and activity networks. These give us a "big picture" view of an organization and how it does what it does.

But a "big picture" view isn't topsight.

That point might seem counterintuitive. Isn't topsight an overall understanding of how the system works? Well, yes. But topsight is like insight: it takes a while to develop, and it develops inductively, over time, as you understand how the details interrelate. You have to actually get into the details—to understand how specific routines happen, over and over, and where they go wrong. You have to see these not just at the macro level of activity, but also at the meso level of action—the minute-by-minute interactions, the ways that people use tools and communicate information as they go about their daily work.

Topsight discusses three different analytical constructs to explore meso-level aspects of an organization. Today, we'll talk about handoff chains.

Think about handoff chains in this way. When we circulate information around an organization, we don't do it via telepathy. We have to hand it off. Sometimes that's a literal handoff: I physically hand you a memo, report, sticky note, or hard drive. Sometimes it's more metaphorical: I speak to you, post a message to the internal message board, or tweet about something. But in any case, we can usually identify a specific genre, cast in a specific material medium, that allows us to hand information from one person to another.

These handoffs happen so often, and sometimes seem so trivial, that we don't pay much attention to them. But watch them closely as they happen, examine the specific handoffs, and ask people about them afterwards, and you'll see patterns emerging. Patterns that might look like this:

Each arrow represents a handoff: a point at which one person materially provides information to another. Some of these handoffs seem trivial, others seem major. But each represents—or should represent—an actual, identifiable incident. That is, this isn't an idealized process; it's an actual set of instances that we can reconstruct directly from an actual observation.

That's really important. If you ask someone what their process is, they will generalize it, forgetting what they think are trivial steps, minimizing others, maximizing still others. They don't necessarily know what to pick out for you. If you see it, and especially if you see it over and over, you can build up a more concrete picture of the chain of handoffs that are necessary to make something happen. Maybe, for instance, that instant messaging is a critical part of the process but no one realizes it.

And maybe there's a pattern of disruptions. Maybe, as you look at handoff chain after handoff chain, you realize that certain parts of the chain are repeated over and over because they have to be reset. Structural miscommunications, lossy media, failure to get buy-in from all stakeholders, and who knows what else might be disrupting this communicative chain. When you put together a chain like this based on specific instances, not on generalizations and recollections, you start to see patterns that no one else might have spotted. And those patterns are also part of topsight.

If you've been reading my academic work or those of my collaborators, you may recognize that handoff chains are based on William Hart-Davidson's work with communicative event models. I've been very fortunate to work with Bill and with Mark Zachry to develop and extend the concept, and I'm excited that it's now in the conceptual toolkit of Topsight.

Now, I mentioned that handoff chains are one way to get at a meso-level understanding of an organization. There are two more, which I'll plan to discuss soon.

Topsight > How to cite Topsight

I'm behind on my blogging due to a big project I'm trying to wrap up this week (unrelated to Topsight). But I thought I'd address a question: How do you cite a self-published book?

It turns out that others have also wrestled with this question. It's complicated, because the book is self-published, but printed by CreateSpace. According to one thread from the Amazon CreateSpace message board, one cannot put down CreateSpace in the publisher spot, like this:

Hocking, Amanda. Fate: My Blood Approves. Charleston: CreateSpace, 2010.

At least, you can't in the book itself.

The citation above turns out to be the proper MLA format for citing a self-published book, more or less, so someone who wants to cite this book could actually use this format in their Works Cited page. In this version, the printer goes where the publisher would normally go. Chicago handles things similarly. (A quick Google search turns up no analogue for APA.)

But if you use it in the book itself, CreateSpace will insist that you turn it into one of these possible forms:

Hocking, Amanda. Fate: My Blood Approves. Charleston: Amanda Hocking, 2010.
Hocking, Amanda. Fate: My Blood Approves. n.p. Amanda Hocking, 2010.
Hocking, Amanda. Fate: My Blood Approves. n.p: n.p, 2010.
Hocking, Amanda. Fate: My Blood Approves. n.p: n.p., printed by CreateSpace,  2010.

So: How will you cite Topsight when it comes out? You might consider something like this:

Spinuzzi, C. (2012). Topsight: A guide to studying, diagnosing, and fixing information flow in organizations. Austin: CreateSpace.

Check your style guide for details.

Network > New slide decks for each chapter

I've been posting a lot about my new book Topsight and pointing to the downloadable content I've been adding to the page as I count down the days until the book is available. But I have other books too—books that lay down the theoretical and empirical background behind Topsight. And I'll be adding downloadable content to their pages as well.

In fact, I put together a set of slide decks last year that discuss my 2008 book Network chapter by chapter, reviewing and amplifying on each chapter's content and adding examples to make the book more relevant to social media and information design. Today I uploaded them.

If you're interested, go to the page for Network and take a look—they're in the Download section. And let me know what you think in the comments!

Topsight > Activity networks

In the last post in this series, I discussed how my book Topsight handles activity systems, which are essentially ways to sketch out the cyclical activities in which people are engaged, as well as the systemic tensions or contradictions that inevitably develop. And at the end of the post I said, "Activity systems don't just float around by themselves, like beach balls in the ocean. They constantly connect and overlap. And those connections and overlaps create contradictions too."

So let's talk about how activity systems connect and overlap.

They do, of course. Let's take a simple example. Suppose that you're working in a restaurant. In fact, it's a fast food restaurant. And there's something that seems absolutely normal, but is actually quite extraordinary: everyone seems to know what they're doing. And I don't just mean the cashiers and the cooks: customers who have never set foot in the restaurant also seem to know what to do. They walk in, go to a point just behind the current line, read the board, queue up, and read their order to the cashier. They then pay, move to the correct place, and receive their food. Then they sit, eat, (hopefully) bus their tables, and exit.

How on earth does this happen?

Largely it's because they are familiar with how fast food places are set up in general. They borrow from the same sources. For instance:

• Objectives and outcomes are largely common to most fast food places.
• Tools tend to involve similar genres (menus, graphics, even signs on the trash cans).
• People vary in education and experience, but the fast food restaurant is set up to accommodate and train a broad range of people.
• Rules tend to come from a range of places, most importantly health regulations.
• Division of labor tends to be rigid in order to modularize the workforce—to ensure that if someone quits, another person can easily take her or his place.

So, for instance, every restroom of every fast food restaurant in the US (theoretically) has a sign telling employees that they must wash their hands before returning to work; that's not because restaurant owners all think alike, it's because the sign is required by the health code. Most of these restaurants also have cash registers that work similarly and spit out similar-looking receipts, and that standardization—though not required, I think—comes from outside the activity, from the suppliers that furnish the cash registers. Each activity is impacted in multiple ways by multiple other activities. 

To put it another way, although some things happen that are unique to a given activity, many things are either inherited from other activities or shared by them. In cases like these, we can consider the interlinked activities activity networks. Here's what they look like in Topsight.

In this figure, the circles represent different activities. Sometimes they're interlinked, with one activity's output becoming another's input—for instance, perhaps Company XYZ makes cash registers (their objective), which then become tools for the fast food restaurant. Sometimes they share some of the same  components: for instance, maybe the franchisee (an actor) also sits on the Chamber of Commerce (where he also serves as an actor). 

And sometimes two activity systems overlap. For instance, suppose that the franchisee has gone into business with his son-in-law, and various family members work at the franchise. So the actors and objective are shared between the fast food restaurant and the family; to some extent, the division of labor might be as well. But families and franchises are very different entities, and when they overlap in the same space, it's very easy for contradictions to develop. 

So how do we detect links to other activities? Here's a worksheet that I provide in Topsight.

In the worksheet, I provide guiding questions to help you discover these other links and describe them. Topsight provides more extended instructions as well. And after discovering these links, you can draw an activity network similar to the one in the previous figure.

Activity systems and activity networks are key to understanding how activities develop, interlink, and develop long-term systemic contradictions. But we also need to understand how organizations work at other levels and timescales. In a few days, I'll introduce some ways to do that.

Writing :: How Can Technical Communicators Study Work Contexts?

Spinuzzi, C. (2012). How can technical communicators study work contexts? Solving Problems in Technical Communication, Eds. Stuart Selber and Johndan Johnson-Eilola. Chicago: University of Chicago Press.

This is the fifth in my ongoing series on writing publications. But that doesn't mean that the chapter I'm describing was written recently. In this case, I finished the chapter quite a while ago—I submitted a substantial draft in September 2009—and did some light fine-tuning in the years after that, freshening citations and so forth.

The chapter is for Selber and Johnson-Eilola's Solving Problems in Technical Communication, which is meant for technical writing undergrads and early grad students. In this particular case, the editors asked me to describe how to study work contexts, based on my workplace studies.

The topic was really timely for me. In the previous year (2008), I had teamed with Mark Zachry and Bill Hart-Davidson to present a workshop on field methods and analytical constructs at the RSA Summer Institute, so the materials were fresh. And I had been using the analytical constructs in various papers as well as in my undergraduate field methods class. In fact, I had been thinking about bundling some of these materials into a book (which I eventually did).

For this particular chapter, I focused on the meso-level analytical constructs that I thought would be most useful and accessible, the ones that Bill, Mark and I discuss in "Chains and Ecologies": genre ecology models, communicative event models, and sociotechnical graphs. In fact, you can think of the chapter as a popularization of that piece, one that uses an extended scenario to illustrate them.

Popularization is the key word. Since the chapter was meant to be read by undergrads, it required a different mode of writing, one that relied more on conversational language and less on dense citations—and, at least in 2009, it was a mode that I had a hard time entering. The editors patiently sent back my first draft (and, I believe, my second) with a lot of helpful comments on how to make the chapter more accessible. Comments such as "Fixing this may require creating a new scenario and a new extended example"—a comment that led me to completely rewrite and restructure the chapter!

Lessons? For this chapter, the big lessons are:

(a) Often a writer has to adjust for the audience. And those adjustments aren't always easy—in this case, they entailed a complete rewrite. At a couple of points, I became frustrated enough that I wondered whether this chapter was worth it. PS, it was: this exercise paid real dividends in terms of clearer writing and also in terms of doing a better job of teaching my own students.

(b) The chapter isn't the point. Speaking of, I want to emphasize something here that I tell my grad students. It's not about the publication. The publication is not the product of your scholarship, it's the exhaust or the condensate that comes as a byproduct of the scholarship. We measure progress in scholarship by publications, yes, but that's like measuring industry by measuring CO2 emissions or tracking a jet plane by looking for the contrail. Once you think of publications like these as the condensate that results from solving interlinked problems (e.g., How do we study context? How do I communicate my results to an undergraduate audience?), it becomes a lot easier to push them out, to invest less in them emotionally, and to see them as a trailing-edge measure of progress.

(c) Sometimes you have to be patient. In this case, "trailing edge" is a good description, since the chapter took a while to come out. In fact, seeing this chapter come out now almost feels like time travel, since that work from 2009 was an important step toward my new book, which will actually come out just weeks after this one!

No matter. Strategically, these publications link together, with each publication helping me to think through the next step in my scholarship. Tactically, they provide coverage: publications come to press at different rates, just as investments mature at different rates, so having several out there can pay dividends at different points. In this case, the chapter is coming out at a very good time in terms of my annual merit case and in terms of promoting my new book. (Did I mention my new book?)

Topsight > Activity systems

I've been using activity theory ever since David R. Russell introduced me to it in—was it 1995? And one of the most useful tools that activity theory gives to us is the notion of the activity system.

The activity system is the analytical unit of activity theory: it's what we have to study in order to understand what people are trying to do in an organization or other social unit. Roughly speaking, the activity system allows us to study the material and social context that surrounds a repeated activity.

For instance, suppose we want to examine how people work in an organization. We wouldn't focus (exclusively) on their tools, their education, or the posted rules that they have to follow. We wouldn't (exclusively) isolate each one and give them IQ or perception tests. Sure, we might do any of these things as part of a larger study, but in isolation, they don't tell us much about the shared activity.

So what would we do?

Activity theory would suggest that we first figure out: (1) What's the objective that they're trying to accomplish over and over again? And (2) why—What's the outcome they want to produce?

Once we figure those out, then we can go to other components that make up the activity. First the easy part, easy because these components are generally visible: (3) What tools do they use as they try to accomplish their objective? (4) Who is directly using these tools to achieve the outcome?

Then the harder part, harder because these components are generally invisible: (5) What formal and informal rules do people follow in this activity? (6) What community stakeholders are indirectly involved? And (7) What's the division of labor at the site—how do people formally and informally divide their roles?

By dissecting context in this way, we can start to understand how all these components fit together.

Okay, so this description gives us a conceptual overview. But to do this sort of analysis ourselves, it really helps to have step-by-step directions. And maybe a worksheet to fill out.

For step-by-step directions, you'll have to wait to read my book Topsight, where I show how to use field research to construct activity systems. But you can see the Topsight worksheet for activity systems now. Here it is.

As you can see, each component is numbered; these numbers correspond to the instructions in the book. I'll make the PDF available soon on my book site so that people can download it and write in the blanks.

Of course, part of what makes activity systems useful is that once you describe the activity, you can start to detect systemic tensions. Activity theorists call these tensions contradictions. They're sources of disruptions—but also, as Yrjo Engestrom tells us, engines of innovation. Naturally: When a system isn't working, people try to fix it. So detecting those contradictions, and the innovations that cluster around them, becomes extremely valuable.

Detecting these contradictions takes a new set of questions, a new set of instructions—and a new worksheet.

In this worksheet, you can use the same field data to begin identifying contradictions: contradictions within each point (say, two incompatible tools) and contradictions between points (say, a mismatch between a tool and a rule). You write a description, indicate the contradiction with a dashed line, and then you have a depiction of the underlying tensions in an organization.

This brief description makes activity systems sound easy to produce. They're not, of course. Like topsight itself, an understanding of an activity system takes a while to develop. But you'll find the tools for developing it in Topsight.

One more thing. Activity systems don't just float around by themselves, like beach balls in the ocean. They constantly connect and overlap. And those connections and overlaps create contradictions too. Soon I'll talk about how to model those contradictions as well.

Topsight > What's in Topsight?

So my new book Topsight is written for a general audience—people in organizations, consultants, undergraduates, and others who want to better understand information flow in organizations. What does that cover?

Let's just take a quick look at the table of contents. The book is organized around four phases.

It starts with an introduction, of course:

• Chapter 1. Why We Need Topsight–And How We'll Achieve It

Then the four phases. 

Phase I: Planning a Study

• Chapter 2: Developing a Research Design
• Chapter 3. Building in Protections
• Chapter 4. Gaining Permission
• Chapter 5. Preparing for Data Collection

In this phase, people learn how to design a study to achieve topsight. This phase is a bit different from those you'll see in most field methods books, though, for a few reasons.

First, topsight requires an integrated-scope approach. So the research design has to gather data from three different levels (macro, meso, and micro) as well as etic and emic data (your perspective, their perspective). 

Second, topsight involves examining an organization, not a culture or a set of individuals. So the design has to be responsive to the stakeholders in the organization, including gatekeepers at different levels as well as participants. So the design has to be responsive to those dynamics. 

Third, any one of these stakeholders can say no at any time. So I discuss how to get them to say yes.

Phase II. Conducting the Study

• Chapter 6. Introducing Yourself to Participants
• Chapter 7. Observing
• Chapter 8. Interviewing
• Chapter 9. Artifacts
• Chapter 10. Collecting Other Sorts of Data

In this phase, I discuss how to collect the data that you'll need in order to achieve topsight. Again, due to the methodological and analytical requirements of topsight, these chapters will be a bit more specific than you'll see in many field methods books. For instance, you'll need to take field notes openly and in real time during observations—not the norm in ethnographic research. Similarly, interviews involve a certain rhythm and touch on different levels of scope.

Phase III: Navigating Data

• Chapter 11. Triangulating Data
• Chapter 12. Coding
• Chapter 13. Reporting Progress: The Interim Report

Topsight is not just oriented to organizations, it involves being responsive to organizations. So in this phase, the book focuses on how to navigate the data you've collected and how to relate the different parts of the data together. In the end, topsight requires building solid arguments for change, so Phase III is argument-oriented: it involves building claims from triangulated data, figuring out how to put "street signs" on your data via coding, and keeping your host organization in the loop.

Phase IV. Analyzing the Data

• Chapter 14. Introduction to the Analytical Models
• Chapter 15. Resource Maps
• Chapter 16. Handoff Chains
• Chapter 17. Triangulation Tables
• Chapter 18. Breakdown Tables
• Chapter 19. Developing Activity Systems
• Chapter 20. Developing Activity Networks
• Chapter 21. Developing Topsight Tables

This phase is where the unique aspects of the approach really kick in. Each model provides a different view of the data you've collected. Together, they provide integrated views at the macro, meso, and micro levels, allowing you to examine how the three interact—and to diagnose the systemic issues at play in the organization.

Phase V. Reporting the Results

• Chapter 22. Describing Systemic Issues
• Chapter 23. Turning Findings into Recommendations
• Chapter 24. Writing the Recommendation Report
• Chapter 25. Beyond Field Studies

I mentioned that topsight is really about making arguments for change, right? And these arguments aren't simply academic: we're talking about concrete changes that may cost the organization (in terms of money, time, reorganization) but that should pay dividends (in terms of addressing systemic issues that are holding the organization back). In this phase, I'll discuss how to turn the analysis into a solid argument for change, one that provides findings but goes beyond them to furnish concrete recommendations. 

The book can't take you to the next step, which is testing and refining these recommendations. But the last chapter gives you some pointers to the next steps.

Finally, two appendixes:

• Appendix A: Resources
• Appendix B: Rolling Your Own Free, Customized, Free, Multiplatform, and Free Qualitative Data Analysis Tool. For Free.

The first is a set of resources you can read for more information; the second is based on a blog post I wrote a while back, discussing how to manage qualitative data.

Can I be candid? I get more enthusiastic each time I read through this table of contents. I hope you're interested too. 

Keep your eyes on this space for more about Topsight. 

Topsight > How do I get Topsight?

Yesterday I said that I had been working on a project meant to pull my topsight-related work together and make it more broadly accessible. That project is still underway, but let me introduce it to you.

It's a book. I'm calling it Topsight: A Guide to Studying, Diagnosing, and Fixing Information Flow in Organizations.

And it's both similar to and different from my previous books and articles. Here's how.

How to study the organization
My previous books and articles describe field studies I conducted in complex knowledge work organizations, studies that helped me achieve an overall understanding of how these organizations circulate information.

Topsight doesn't describe a field study—it tells people how to conduct and analyze their own field studies, including lots of tips and tricks that I've had to learn the hard way. That includes designing a study, putting together a research kit, and convincing stakeholders that the study is a good idea.

How to diagnose the organization
In my previous books and articles, I developed or adapted analytical constructs such as activity systems and activity networks, genre ecologies, sociotechnical graphs, operations tables, and contradiction-discoordination-breakdown tables. These helped me to diagnose problems with information flow in these organizations.

Topsight includes these constructs and more—but it gives them better, more self-explanatory names; explains them lucidly, so anyone can put them together from the data; and provides professionally designed figures to better convey what these constructs are supposed to do. Which is: to diagnose problems with information flow in organizations.

How to fix information flow
My previous books and articles basically stopped at diagnosis. They were about analysis.

Topsight doesn't. It walks readers through developing claims, turning them into recommendations, justifying those recommendations, and integrating them into solid recommendation reports. Readers won't just analyze the organization, they'll have the tools to argue for changing it.

And that brings us to...

Organizations
My previous books and articles were written for professors and graduate students. They talked about organizations, but not necessarily to people in organizations.

Topsight is written for people in and out of academics who want to achieve topsight: undergraduates, consultants, people who want to change their own organizations.

Published by...
My previous books were published by MIT Press and Cambridge University Press. I'm very proud of these books, and I'm very grateful to these publishers for accepting them.

Topsight will be published by ... me. I'll be working through Amazon's CreateSpace publish-on-demand platform to produce the book in both printed and Kindle versions. This approach means that I can turn the book around quickly, retain control, keep costs down, and reach a global market. It's an exciting experiment.

Topsight won't quite be out in time for Christmas, but it should come out soon afterwards. Watch this space for an announcement. In the meantime, I'll be blogging about different aspects of the book—and adding more content at clayspinuzzi.com.

Topsight > What is topsight?

A while ago, I posted my review of David Gelernter's book Mirror Worlds, an influential book that is about developing software to help us better understand complex systems. Published in 1991, this book was influential in a number of ways. Specifically, it introduced the notion of topsight.

As I wrote in my review of the book,

Gelernter argues that we often have trouble getting to the big picture, understanding the entire system. Instead, he says, we get mired in the details, something that he calls ant-vision. “Ant-vision is humanity’s usual fate; but seeing the whole is every thinking person’s aspiration. If you accomplish it, you have acquired something I call topsight.” Topsight—the overall understanding of the big picture—is something that we must "pursue avidly and continuously, and achieve gradually." It's a systemic understanding, a way of seeing the whole (see p.11; 30; 42; 51).

And I added:

topsight, like insight, comes gradually; don't confuse it with the model itself, understand it as something that the model make it possible to achieve.

As our systems become more complex, topsight becomes more critical to achieve. But it also becomes harder to achieve. That's certainly true in the complex systems that Gelernter wants to model, such as cities and nuclear power plants. But it's also true in the complex, overlapping, polysemous sociotechnical systems in which we work. How do we make sense of an organization in which several specialties overlap, an organization that uses off-the-shelf software and texts from different domains, an organization that has to work with multiple sets of rules? How do we tie together second-by-second operations, minute-by-minute tasks, and year-by-year activities, using them to yield a more complete understanding of the organization? How do we figure out how information flows through organizations, where it gets stuck, and how it becomes unstuck? How do we gain topsight—which, as Gelernter says, must be achieved gradually, like insight—when even a simple organization can develop unwritten rules, hold contrasting objectives, and be enmeshed with other stakeholders?

The term topsight, in fact, points to something that I've been studying since 1997 and teaching since 2000: how to investigate, analyze, diagnose, and model the ways that organizations circulate information. I've discussed parts of this work in my two books, in my many publications, and in seminars.


But Gelernter says something else about topsight. It shouldn't just be for a few people. If you want to drive smart, informed changes, you have to make sure that everyone has at least a chance to develop topsight.  He imagined this happening via broadly accessible models of complex systems. I imagine it happening by bringing methods out of academia—out of books, publications, and seminars—and making them accessible to the people in these systems, to consultants, and to undergraduates.


So for the last several months, I've been working on a project meant to pull my topsight-related work together and make it more broadly accessible. In the next few days, I'll be discussing that project—and topsight—on this blog. Stay tuned.