To start let’s consider two distinctions about organizational processes. Following Sig over at Thingamy, two basic types of processes exist: easily repeatable processes (ERPs) and barely repeatable processes (BRPs).
ERPs: Processes that handle resources, from human (hiring, firing, payroll and more) to parts and products through supply chains, distribution and production.
BRPs: Typically exceptions to the ERPs, anything that involves people in non-rigid flows through education, health, support, government, consulting or the daily unplanned issues that happens in every organisation.
As I noted in Social Learning and Exception Handling, BRPs result in business exceptions and take up almost all of the time employees spend at work. Interestingly, much of the writing I see on Big Data is about making ERPs more efficient or making guesses about when to expect occurrences of a BRP. In other words, both goals are really about making coordination of organizational efforts more efficient and/or effective.
How organizations coordinate their activities is essential to the way they function. What makes sense for the organization’s internal processes may not make sense in its ecosystem, and vice versa. These are distinctions that analysts of Big Data sometimes fail to note and consider.
For example, in The Industrial Internet the Future is Healthy, Brian Courtney notes the following about the use of sensors in industrial equipment and the benefits derived from storing at big data scale.
Data science is the study of data. It brings together math, statistics, data engineering, machine learning, analytics and pattern matching to help us derive insights from data. Today, industrial data is used to help us determine the health of our assets and to understand if they are running optimally or if they are in an early stage of decay. We use analytics to predict future problems and we train machine learning algorithms to help us identify complex anomalies in large data sets that no human could interpret or understand on their own [my emphasis].
The rationale behind using data science to interpret equipment health is so we can avoid unplanned downtime. Reducing down time increases uptime, and increased uptime leads to increases in production, power, flight and transportation. It ensures higher return on assets, allowing companies to derive more value from investment, lowering total cost of ownership and maximizing longevity.
In other words, Courtney’s analysis of the big data generated from sensors that constantly measure key indicators about a piece of equipment assumes the data ensures a decrease in downtime and an increase in uptime resulting in increases in production, power, flight and transportation. Yet, the implied causal relationship doesn’t translate to all cases, especially those involving barely repeatable processes (BRPs) that produce business exceptions. It is in BRPs that the real usefulness of big data manifests itself, but not on its own. As Dana Boyd and Kate Crawford note in Critical Questions for Big Data, “Managing context in light of Big Data will be an ongoing challenge.”
Podular Design — From Dave Gray’s Connected Company
In “Institutional Innovation and Podular Design“ I noted a number of insights from the Aspen Institute’s report, Institutional Innovation: Oxymoron or Imperative?, especially that “the most important innovation challenges are now in fact institutional in nature.” As an aside, let me just note that institutions typically change in dramatic ways only over long periods of time. Think of institutions such as religion, government, the economy, and then consider the various organizational forms in which these institutions took shape across cultures over time.
One insight I have not discussed in previous posts is relevant to understanding the changing way teams work together in organizations and, by implication, in a Connected Company — as outlined by Dave Gray. Richard Adler the Rapporteur for the Aspen sessions, noted that,
“New findings about the power of collective intelligence and about the most effective ways of organizing teams are providing practical insights about how to accelerate innovation.”
To start, let’s consider many companies organize teams and then turn to the “power of collective intelligence” mentioned by Adler to see how the two relate to podular organization. Several research projects in recent years noted the fuzzy boundaries of teams in large organizations. Skilful Minds first noted this phenomena in Who’s on Your Team? Enterprise 2.0 and Team Boundaries , and then a couple of years later in Social Learning, Collaboration, and Team Identity.
In fact, the phenomena of transitory team membership is so pervasive that some people propose we analyze “teaming” rather than teams when talking about how groups organize for cross-functional purposes within, or between, companies. Consider, for example the way, Mark Mortensen summarizes this trend in team dynamics,
First, organizations increasingly require collaborations to be fluid in their organization and composition, able to adapt to the rapid changes of the external environment. Second, collaborations increasingly overlap with one another, sharing resources — including people — as those resources become more limited due to increased competition. Third, collaborations must increasingly take into consideration the different contexts within which collaborators are embedded, including locations, time zones, cultures, and languages, structures, or organizations.
The liminality of such transitory teams results from several institutional challenges including the high degree of misunderstandings that initially occur due to team members rarely having the time to translate the different ways of thinking that people bring from their professional specializations into a mutual understanding of their shared business purpose. Developing mutual understanding requires shared experiences, getting to know who you are collaborating with, not just what they do or their skills profile. In addition, conflicting functional priorities, and often a lack of clear accountability, make it difficult for such teams to remain focused on the business purpose of their collaboration.
Teams were not always organized this way. As Mortensen notes, teams in multi-divisional companies were, at one time, defined by bounded and stable team membership and common goals that interdependent work was required to meet. Cross-functional teams in such companies today are not typically defined by bounded and stable membership, and common goals are still too often related to divisional performance driven by scalable efficiency rather than a connection to the purpose of the business the team is serving.
Over the last 40 years, the emergence of new digital infrastructures and a global liberalization of economic policy have increased the pace of change exponentially. Many companies that were extremely successful in earlier times of relative stability are now finding that their relationship architectures are fundamentally misaligned with the needs of their business today. As the pace of change increases, many executives focus on product and service innovations to stay afloat. However, there is a deeper and more fundamental opportunity for institutional innovation—redefining the rationale for institutions and developing new relationship architectures within and across institutions to break existing performance trade-offs and expand the realm of what is possible.
Institutional innovation requires embracing a new rationale of “scalable learning” with the goal of creating smarter institutions that can thrive in a world of exponential change.
The challenge then remains how to enable organizations to adapt to their ecosystems by enhancing access to flows of knowledge that are likely to result in learning. Leinwand and Mainardi recently observed that permanent cross-functional teams tend to fare better than transitory teams in engaging organizational ecosystems. As they note:
We’ve recently seen a more robust cross-functional construct emerge, one with an overarching organizational structure, based on building and maintaining a distinctive capability. Members of these capabilities teams are assigned permanently to them, reporting there rather than through a functional hierarchy.
Permanent cross-functional teams provide an institutional basis for what Hagel and Brown refer to as edge businessesthat develop within large-scale enterprises, noting that such companies “should resist the temptation to confront the core, and instead focus on opportunities on the periphery or at the ‘edge’ of their businesses that can scale rapidly.” I suggest below that Dave Gray’s conception of podular organization affords an important insight regarding how the institutional innovation of edge case businesses can develop and organize. Read the rest of this entry »
Podular Design — From Dave Gray’s Connected Company
In Social is the plural of personal JP Rangaswami contends that institutional innovationis required to achieve the potential that social software offers organizations in general, and for-profit companies in particular. JP’s voice is one of several important contributions to current thinking about innovation. For another example consider the Aspen Institute’s Communications and Society Program. It produced a series of roundtables with the Deloitte Center for the Edge over the past few years. Until the 2011 session the focus was largely on talent development. However, in the most recent session, Institutional Innovation: Oxymoron or Imperative?, the focus was on institutional innovation. It is an interesting change in terminology largely because much of the attention in the learning and development world today is on talent management along with employee engagement as cutting edge concerns. However, as Richard Adler the Rapporteur for the Aspen sessions, explains,
If institutions developed in and optimized for the previous generation of infrastructure are no longer working, then where innovation is most urgently needed is not in product development but in the design of institutions themselves.
My point is that the most important innovation challenges are now in fact institutional in nature. Many companies employ senior executives and managers who use social networks in their personal lives but are either reluctant or stymied about how to integrate similar patterns of communication into their work. This point is reinforced by the recent finding of Stanford University and the Conference Board from a survey of 180 senior executives and corporate directors of North American public and private companies. The lead researcher concluded that, “We know that executives and board members are using social media. However, familiarity with social media is just not translating into systemic use at their companies.”
We continue to see organizational ambivalence over how social relationships contribute to business outcomes. For instance, a recent IBM study reported that only 22% of CIOs surveyed think managers are prepared to incorporate social media into their work. Managers generally fail to acknowledge that social networks contribute to business outcomes and that enabling human connections between stakeholders (employees, business partners, customers) adds value to the company when employees share a substantive understanding of the business purposes served by the enterprise’s organization. How to facilitate that substantive understanding is the biggest question facing anyone considering collaboration and innovation in today’s companies.
As my recent post, Revisiting the Great Innovation Debate contended, it is essential for people working in distant places, whether down the block, across the state, or on the other side of the world, to have a sense of a shared office to develop adaptive capabilities. Indeed, recent research on distributed work by Hinds and Cramton contends that knowing whoone is collaborating with is a crucial part of the know how, the practical, institutional knowledge, that enables the adaptive capability organizations widely recognize they need to innovate, as well as deal with exceptions to process through informal and social learning.
The point isn’t totally new, nor is it passe’. As many social software vendors acknowledge, it is important to integrate collaboration tools into the flow of work for them to succeed as useful tools. However, as a previous post noted, Social Software, Community, and Organization, that doesn’t mean the social communication afforded by particular tools is more effective if it supports only formal workplace, i.e. functional, goals. Social software must afford the capability for those using it to develop shared experiences of one another as people, not just corporate role players.
I recently received an invitation from Mads Soegaard, Editor-in-Chief at Interaction-Design.org to offer those who read this blog an early view of a new chapter on Social Computing in their encyclopedia. I’m a little late on this writing for you to get a pre-publication view of the chapter but I wanted to make sure and point it out for those who take topics like social computing seriously. Thomas Erickson wrote the chapter. To be candid, I didn’t really know much about Thomas until I read it. He seems like a very interesting person. Thomas’ chapter takes seriously the point of an early comment I made in a post here in 2008 on Social Software, Community, and Organization: Where Practice Meets Process, specifically my point that not enough of the influential discussion on the topic took seriously the roots of what it means to do social computing.
The distinctions involved are as old as the study of social interaction in organizations, especially the characteristics of routine work. However, we don’t need to go back to the 1950s when the distinction first emerged in the study of industrial organization to understand the significance of Ross’ point. Indeed, the early 1980s will do. Rob Kling discussed computing as social organization as early as 1982 in Marshall Yovits’ edited series on Advances In Computers. Drawing from the symbolic interactionist tradition, Rob distinguished between a line of work which, he contended, indicates what people actually do in computing work, compared to formal descriptions of that work, or what we might today refer to as business processes. Kling’s work was one precursor to the focus on computer supported collaborative work (CSCW) in studies of group collaboration, most notably developed at Xerox PARC.
The social roots of social computing are important for influentials to keep in mind as they discuss current developments in Web 2.0 technologies, especially their use in the enterprise. The point is not a simple academic exercise of giving credit to what came before. Rather, it is to take note that the distinctions made explicit…regarding practice/process are as old as the modern, hierarchical organization and seem to survive regardless of the way communication technology is applied in it. Those who discuss tensions between social software and Enterprise 2.0, or learning management systems and eLearning 2.0, are pointing to persistent challenges in how organizations work.
Thomas’ chapter provides an excellent overview of the roots, history, and development of the concept of social computing as a concept that promises to stand the test of time regardless of the labels used to describe it, e.g. Web 2.0, Social Media, Social Business, Enterprise 2.0, etc. I recommend anyone involved in current discussions related to compound nouns like social media, social business, social “this” or “that” take a look at Thomas’ chapter as well as the Interaction-Design.org encyclopedia which offers in-depth analysis of such topics.
Harold Jarche recently offered a framework for social learning in the enterprise in which he draws from a range of colleagues (Jay Cross, Jane Hart, George Siemens, Charles Jennings, and Jon Husband, all members of the Internet Time Alliance) to outline how the concept of social learning relates to the large-scale changes facing organizations as they struggle to manage how people share and use knowledge.
Harold’s overall framework comes down to the following insight,
Individual learning in organizations is basically irrelevant because work is almost never done by one person. All organizational value is created by teams and networks. Furthermore, learning may be generated in teams but even this type of knowledge comes and goes. Learning really spreads through social networks. Social networks are the primary conduit for effective organizational performance…Social learning is how groups work and share knowledge to become better practitioners. Organizations should focus on enabling practitioners to produce results by supporting learning through social networks.
Indeed, Jay Cross suggests that the whole discussion needs framing in terms of collaboration, and I tend to agree. Yet, saying social learning occurs largely through collaboration means delving into the subtleties of how social networks relate to the organizing work of project teams as well as to their performance. After all, much of the work done in Enterprises involves multidisciplinary teams, often spread across departments, operating units, and locations.
One of my earlier posts posed the question Who’s on Your Team? to highlight the importance of social networking to establishing team identity and enhancing knowledge sharing across distributed, multidisciplinary teams. Its focus was on the importance of social software applications in the Enterprise to the ability of distributed project team members to recognize who is on their team at any point in time, and who isn’t. Organizational analysts refer to the challenge of establishing team identity as a boundary definition problem for teams, when members are spread across large distances whether geographic or cultural in nature.
As I noted in a post on Peter Morville’s Findability several years ago,
“Interfaces are not what they used to be. The computer-human interface is both more and less than it was a few years ago. Interfaces are not only, or even primarily, a screen anymore. Yet, screens remain important to most design efforts, even though interfaces are increasingly part of the environment itself. As John Thackara and Malcolm McCullough both recently pointed out, entire cities are developing into user interfaces as ubiquitous computing environments expand.”
Caleb, over at MobileBehavior, recently observed that mobile phones do not yet provide users with a graphic language for touch interactions. Caleb’s post points to an early visualization of a standard graphic language offered by Timo Arnall of the Touch project, which researches near field communication. Caleb makes his point by talking about the confusion that consumers experience when faced with a visual tag (v-Tag), or 2D Barcode, and does so with the following Weather Channel forecast that offers viewers an opportunity to interact with a visual tag using their mobile phones (wait until about 45 seconds into the video). The forecast fails to indicate to viewers what the v-tag does.
The user experience team that developed the v-tag for that particular forecast must have assumed viewers would know it represented an invitation to interact. A search on the Weather Channel website fails to return any information on the use of v-tags in their media programming though.
In a previous discussion of Dan Saffer’s book, Designing Gestural Interfaces, I made a similar point about mundane gestural interfaces in public bathrooms, a setting with fairly established graphic language conventions. Yet, even such mundane gestural interfaces can pose difficulty for users. As I noted,
I remember the first time, a few years ago, when I tried to get water flowing through a faucet in a public restroom that used sensor detection. Initially, it was not obvious to me how the faucet worked, and I suspect others continue to experience the same problem based on the photo I took during a recent visit to a physician’s office.
Among other observations, it is important here to note that these examples provide clear instruction for why experience design encompasses user experience. Specifically, people only experience a user interaction if the interactive capability of an artifact is intelligible, if they recognize the artifact as an instance of that kind of thing, i.e. an invitation to interact with media or machinery. Who knows how many people noticed the Adidas logo embedded in a v-Tag on their running shorts, or shoes, and failed to see it as an invitation to a user experience?
People can’t use an interface if it is not recognizable as such or, as the Palcom team coined it, palpable to their use. Otherwise, the invitation to experience, what Dan Saffer calls the attraction affordance, fails. Consider the more telling example of the symbol at the top of this post. It represents an RFID signal environment for devices using the Near Field Communication (NFC) standard. Indeed, Timo Arnall and Jack Schulze’s recent work for the Touch project demonstrates the spatial qualities of an RFID device’s signal, the shape of its readable volume.
Dan Saffer, in Designing Gestural Interfaces, touches on the fact that we are currently missing common symbols for indicating when an interactive system “is present in a space when it would otherwise be invisible,” or when we just wouldn’t recognize it as such. Adam Greenfield’s Everyware made a similar point a half decade ago.
People who discuss the importance of social media, and actually social computing in general (Enterprise 2.0 included), continue to insist that the innovations involved will become as much a part of the tacit knowledge and expertise of ordinary people as email. I think that assessment is in fact correct. However, I want to add an insight that no one yet, to my knowledge, has offered.
Social media is not a noun (media) accompanied by an adjective (social). In fact, as long as we think of it that way social media can only fail to achieve what the thought leaders who advocate its use believe it capable of doing. Social media is, in fact, a compound noun, a noun made up of two or more words. Neither term is sufficient to describe what is done by those using it unless we consider it as part of the other.
My first corporate position carried the title Methods Analyst,working for a large billing center serving a telephone company.One of my main tasks in that role involved learning how other employees performed their work and documenting it. On each project I typically spent several hours observing people work (what some today call rapid ethnographyor guerilla ethnography) and then did in-depth interviews of the people I observed. Usually, at the end of my observation, I took responsibility for doing the work for a brief time under their watchful eye. In some sense you could say my work required me to continuously cross trainin other people’s work, analyze the process, and write it up in a technical document. The main insight I took away from that experience was an appreciation for the importance played by empathy in effective collaboration.
First off, collaboration isn’t just about people sharing information to achieve common goals. Collaboration is about people working with other people to achieve common goals and create value. Advocates of Enterprise 2.0 sometimes make the fundamental mistake of arguing that collaboration is really only about achieving business goals, leaving the implication that incorporating social software into the work flow of organizations is sufficient. Even though goal-orientation is a big part of collaborating, collaboration requires more to achieve goals effectively. It requires shared experience. As Dev Patnaik and Evan Rosen recently noted, empathy and collaboration go hand in hand.
The emergence of social media provides people inside and outside organizations with a way to actively speak about, speak to, and engagethe product and service offerings of enterprises. Currently, 25% of search results for the World’s Top 20 largest brands are links to user-generated content and 34% of bloggers post opinions about products & brands. Enterprises, on the other hand, listen to, engage, and act on insights gained from social media.
A recent study of social media engagement by Ben Elowitz and Charlene Li covered the 100 largest brands and, among other conclusions, noted that,
One recurring theme throughout these case studies is that engagement cannot remain the sole province of a few social media experts, but instead must be embraced by the entire organization.
Channels, policies, processes, touch points and transactions are increasingly viewed as parts of the social experience organizations use to encourage employees in collaboration (also known as — Enterprise 2.0), and engage customers in conversation (also known as — social media) for the purposes of innovation and transformation of the business. The common goal of the ongoing discussion involves transforming business practices to incorporate social relationships into the value proposition to customers and other stakeholders.
Integrating engagement into enterprises is crucial to strategic efforts to use social software throughout an ecosystem, inside and outside the formal organizational hierarchy, as social business design. My contention is that such integration is most likely to succeed with a focused approach to informal learning. In my last post, Scalable Learning and Learnscapes in Social Business Design, I offered the following point.
The concept of learnscape is a useful framework for thinking about the strategic challenge to the range of learning activities occurring as companies attempt to create feedback loops between their brand experience and the functional areas of their enterprise, especially in regard to the multidisciplinary collaborationneeded to make these efforts successful.
The concept of a learnscape, initially outlined by Jay Cross, focuses our attention on designing ecosystems to heighten the innovation and performance of people. I lay out some thoughts about learnscapes and shaping ecosystems below, using key concepts from the Dachis Group’s framework, initially discussed in an earlier post on HP’s WaterCooler project. I don’t claim these insights provide proven techniques for shaping enterprise ecosystems. But, I do think they point in a useful direction for those thinking about Enterprise 2.0 and social media strategy to keep in mind. Read the rest of this entry »
About a month ago I read What Would Andrew Do?, an unbook by Jay Cross and friends. I’ve mentioned Jay’s work in previous posts dealing with elearning 2.0 and collaboration in informal learning. In particular, its important to remember that focusing on informal learning doesn’t mean we must disregard the relevance of formal learning because learning is never 100% formal or informal.
However, the term scalable learning probably does require a bit of clarification. After all, isn’t elearning supposed to scale to the size of the learning group and remain available when they need it, where they need it, as long as they are connected to the Web? Well, yes–and it does pretty much. Nevertheless, instructional designers too often fail to incorporate emergent learning requirements of the organization, the enterprise, into their learning architecture largely because the approaches used to evaluate learning content (whether elearning, blended, or instructor-led) do not incorporate assumptions about the larger ecosystem’s need for the co-creation of knowledge.
The concern for whether the learner is exposed to every thread of content in every course, and assessed for mastery of the information, tends to predominate design thinking about learning,and for compliance training sometimes this is required. However, too often, instructional design fails to focus on whether the learning scales to support the learner’s ability on-the-job to recognize a problem as a particular kind of problem, much less provide the ability to find the learning content that provides a solution.
I don’t intend to delve here into the minutiae of distinctionpossible between types of learning. Suffice it to say that when a learning architecture supports all types of learning along the range of formal, non-formal, and informal experience, it must design formal learning in small enough chunks to serve as resources for non-formal and informal learning activities. It also means that the knowledge created using non-formal learning (whether mentored or accomplished in collaboration with peers), or informal learning taken on its own, needs to become a performance resource in developing new formal learning content.
Jay contends that the performance challenges facing organizations are most aptly conceptualized as a learnscape, a concept initially articulated by John Seely Brown and Paul Duguid. In the August 2009 issue of Chief Learning Officer magazine, Jay offers the following synopsis.
Learnscapes are the factory floor of knowledge organizations. The “scape” part underscores the need to deal at the level of the learning environment or ecology…The “learn” part highlights the importance of baking the principles of sound learning into that environment rather than leaving it to chance.
Companies must move beyond their fixation on getting bigger and more cost-effective to make the institutional innovations necessary to accelerate performance improvement as they add participants to their ecosystems, expanding learning and innovation in collaboration curves and creation spaces. Companies must move, in other words, from scalable efficiency to scalable learning and performance. Only then will they make the most of our new era’s fast-moving digital infrastructure.
The participants that Hagel, Brown, and Davison refer to consist of consumers, customers, partners, and employees using social media to talk about, talk to, and engagethe products and services, i.e. brands, that an enterprise markets. Don’t misunderstand the focus on performance in the discussion of scalable learning. It isn’t about the traditional focus on efficiency, pursuing ever leaner processes for the sake of officially recognized best practices. Rather, the focus is on creating the knowledge needed to adapt to emergent challengesand manage the flowof that adaptation through the enterprise’s ecosystem. For learning architecture it begins with understanding the importance of keeping the focus on distinctions between push and pull learning.
Does your organization approach using social media in its business as something to fear or as something to evangelize? Several recent observers note that incorporating social media into business involves changing the culture underlying communication patterns and decision-making in many large organizations.
Amber Naslund, for instance, tells us that adopting social media means changing the mindset on how to do business. In particular, she says using social media in business means “giving your customers a visible, valuable say in how you do things, and having the faith that doing that is just good business.” On the other hand, Caroline Dangson, of IDC contends enterprises aren’t yet sold on social media and that “there are executives still fearful of the transparency that comes with the social media spotlight.” Specifically, Caroline says that,
Corporate culture has everything to do with adoption of social media. I believe the number one factor preventing full adoption of social media is the lack of executive trust in employees. This culture is about control and creates a workplace of silos. This type of workplace is not set up to be social and the silos are barriers to worker productivity.
So, here social media sits, between fear and faith. Needless to say, the truth about social media’s implications for business design lies somewhere in the middle. The fact of the matter, as Todd Defren tells us, is that we need to begin seriously discussing “how Social Media Thinking will impact the greater whole of the company.”
As noted in an earlier post, keeping in mind the distinctions between formal, process-oriented organization and informal, practice-based organization is crucial in thinking through the collaborative challenges posed by social software for enterprises and designing for the experiences supported. We can learn a bit about the complexity of the challenges involved by considering a recent framework offered on social business design by the Dachis Corporation team and discussing the way it relates to a recent report on an experiment in enterprise social media at the Social Computing Lab of HP Laboratories.
The title for this post is drawn from a recent assessment of SharePoint 2007 offered on Thomas Vander Wal’s bog, Personal InfoCloud. Thomas’ post, as always, offers a unique point of view on what Enterprise 2.0 consists and, specifically, how SharePoint measures up. He isn’t offering his own formal assessment as much as reporting the stories clients and potential clients shared with him over the past couple of years. The social software stack, in particular the difference between collective understanding and collaborative understanding, frames Vander Wal’s perspective.
Given SharePoint’s widespread use, and the growing interest in applying social media applications to collaboration challenges in organizations, Thomas’ discussion deserves wider attention. His overall impression is well summarized in the following point.
SharePoint does some things rather well, but it is not a great tool (or even passable tool) for broad social interaction inside [the] enterprise related to the focus of Enterprise 2.0. SharePoint works well for organization prescribed groups that live in hierarchies and are focussed on strict processes and defined sign-offs. Most organizations have a need for a tool that does what SharePoint does well.
This older, prescribed category of enterprise tool needs is where we have been in the past, but this is not where organizations are moving to and trying to get to with Enterprise 2.0 mindsets and tools. The new approach is toward embracing the shift toward horizontal organizations, open sharing, self-organizing groups around subjects that matter to individuals as well as the organization. These new approaches are filling gaps that have long existed and need resolution.
In other words, SharePoint works well for situations in which defined groups need to reach a collaborative understanding of project requirements, their role in achieving those objectives, and what success means for the project. It works less well in providing resources allowing people across the enterprise, and across teams or departments, to discover connections with others and develop social relationships for networking together in ways that meet both personal and organizational challenges.
Without going into links to specific posts, I’ve noticed a trend among many blogs I try to keep up with over the past couple of years. I can’t count the number of times I’ve seen prominent bloggers post publicly about having to pare down the list of RSS feeds they read, or tweets they respond to. Since Peter Kim’s blog is the most recent instance of the trend I’ll use one of his recent posts as an example of what I mean. Peter noted that he increasingly hears an echo chamber across social media blogs in which the same content, case studies, anecdotes, etc. gets repeatedly posted and commented on. More cynical observers might contend that the complaints about information overload from influentials is a little like strutting in front of a crowd. Nevertheless, it is difficult to dispute the point that attention is a scarce resource on the Web. So is engagement.
Ross Mayfield recently pointed to a study published by researchers at the Social Computing Lab of HP Laboratories that addresses the point succinctly by pointing to constraints on friendship in directed social networks such as Twitter. A directed social network is characterized by an absence of explicit reciprocity constraints, fifty people can follow one person without that person necessarily following any of them. First Monday’s most recent issue includes an article, Social Networks that Matter: Twitter under a Microscope, that reports on a study of Twitter users by Bernardo A. Huberman, Daniel M. Romero, and Fang Wu of HP Laboratories.
The authors analyzed data from 309,740 people using Twitter. They compared the network of interactions people actually engage in while using social computing technologies such as Twitter to the network of connections with whom one shares a social relationship. Networks of actual interaction are considered networks that matter by the authors.
By networks that matter we mean those networks that are made out of the pattern of interactions that people have with their friends or acquaintances, rather than constructed from a list of all the contacts they may decide to declare.
In other words, the research focused on reciprocity as well as connection in studying the social network of Twitter. Read the rest of this entry »
Bruce Nussbaum recently declared Innovation is Dead, initiating a lively discussion around the issue of whether one term for change is better than another.
Before listing out Bruce’s key points, it is important to recognize that he isn’t saying that innovation is unimportant. Rather, he is pointing to the necessity of approaching meaningful change as a transformation of relationships between people and institutions, not just innovation at the edges through altering the systems allowing us to manage products and services.
1- Our institutions aren’t working. They are broken. Corporations, investment banks, health care, schools, universities, Congress, transportation. The current crisis is accelerating the breakdown in the major institutions of our lives that began in the 90s.
2- Digital technology is disintermediating every organization, eroding the role of all middle men and women, from ad agencies to college professors, from newspaper editors to hospital administrators, from political parties to savings banks. The shape of all our institutions is radically changing.
3- The power to create and participate is moving to the masses. Digital technology is giving everyone the tools to tinker again, to design and shape their learning, their working, their play. Craft is back in newly significant ways that we are just beginning to understand.
4- “Innovation” is inadequate as a concept to deal with these changes. You have “game-changing” innovation, which is big but rare and incremental innovation which is small but common. “Innovation” implies changing what is. “Transformation” implies creating what’s new. That’s what we need today, a huge amount of totally “new.”
5- Design is the answer. I use the term “transformation” to capture the immensity of the task ahead of us and to guide us in the magnitude of that task, but the actual tools, methodologies and, yes, philosophy of that mission is found within the space of design and design thinking.
So far, the spirit of experimentation has provided a sort of ‘get out of jail free’ card with respect to having to demonstrate the value of digital and social media programs and initiatives. It looks like 2009 will change all that due primarily to three factors:
– the widespread awareness of social media use in a business context
– the economy
– the economy
In a similar tone, Peter Kim recently took up the issue of return on investment (ROI) of social media. His thoughts on the topic were a response to a post by Lewis Green. Lewis offers a distinction between focusing on ROI and focusing on business Value as two different, though complementary, ways of addressing the importance of social media to business.
At least since publication of the Cluetrain Manifesto, with its meme that markets are conversations, observers noted the importance of what customers say about a brand, online and off — but especially those online. However, a somewhat subtler point from Cluetrain is increasingly relevant to brands and social media. The point was made in the book’s Thesis 39: “The community of discourse is the market.” In fact, the thesis actually consists of several ancillary ones: Read the rest of this entry »
I’ve been meaning to write about Dan Saffer’s Masters Thesis since reading it a couple of years ago. A recent post by Mike Kuniavsky provides an opportunity to do so. Also, it appears that Dan left his position at Adaptive Path to found Kicker Studio, a product design company. In The Role of Metaphor in Interaction Design, Dan noted that metaphors help users/customers understand new products and services by providing cues that orient and personify the experience of the familiar with the new.
In other words, metaphors help us understand one thing in terms of another by highlighting similarities between the two, while at the same time implicitly recognizing differences. Dan also added that metaphors introduced to facilitate adoption of a new product can also limit its innovation in other ways. He specifically pointed to the Workspace is a Desktop metaphor, which conceptualizes the computer as an office tool primarily. I would add that the metaphor contributed to the myth of the paperless office by obscuring the differences between desktops and graphical user interfaces. Specifically, Dan contended that,
it could be argued that the desktop metaphor has hindered the development of ubiquitous computing as much as some hardware factors (p.22).
At the same time, he observed that the desktop metaphor was much more effective in gaining the widespread adoption of computers when compared to the previous metaphor, i.e. computers as programming environments. He recommended that whenever designers use a metaphor in a new product they need to begin with what is new, the subject of the metaphor, rather than what the metaphor refers to. In other words, don’t force functionality into a metaphor. Use the metaphor to support a concept rather than the other way around. The point builds on the design principle of Cooper, Reiman, and Cronin in About Face 3.0 to, “Never bend your interface to fit a metaphor” (p. 279).
David Armano recently made a distinction between interactive advertising and social media which he depicts in the image on the left. He noted that many companies mistake interactive advertising with social media and notes that the two differ in the place of PEOPLE in the strategy. Specifically, David points out that interactive advertising involves Human-Technology Interactions. Whereas, social media involves Human-Human Interactions enabled by technology.
The image on the left was used by Paul Dunay over at Marketing 2.0 in a recent post on digital signage. Paul notes that a recent Razorfish survey ranked digital signage (32 percent) as only second to mobile (51 percent) in importance as an emerging media channel. He also takes note of examples of new media channels that combine the two, mobile and digital signage.
The eLearning industry is taking a step into visual tagging this fall with the eLearning Guild announcement that each attendee at DevLearn08 will receive a personalized QR code containing their contact information. As we noted in earlier posts,
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Skilful Minds discusses Experience Design
and the ways it matters to client stakeholders, whether users, consumers, customers, learners, or just plain people.
Posted by Larry Irons 
Harold Jarche recently offered 
The emergence of social media provides people inside and outside organizations with a way to actively 
About a month ago I read 
David Armano
The eLearning industry is taking a step into 
Skilful Minds 