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.”
The Altimeter Group’s report from earlier this year, The Evolution of Social Business: Six Stages of Social Business Transformation, offers the above graphic to exemplify the way social networking develops as the social activities of businesses mature. I tend to feel skeptical about many developmental models in social business simply because markets differ, sometimes in fundamental ways, and businesses organize accordingly. However, since a previous post here summarized the currently dominant Hub and Spoke approach as falling short as a way to organize collaboration in relation to customer experience, I feel elaborating on that point is in order.
Shared experience, not just shared information, is fundamental to the social networks underlying collaboration and innovation. Many, if not most, employees don’t only need to get to know one another through reputation systems, like who people tag as possessing expertise. As Thomas Vander Wal continues to point out, comfort with one another is needed to develop a shared experience that encourages the open sharing of information.
Collaboration means getting to know that other employees possess expertise on this or that topic, but also developing comfort with one another by sharing significant symbols relating to self, family, friends, and social activities, thereby understanding one another as people. Shared experience with co-workers and customers is a key factor in innovative business practices. It is especially important to multichannel collaboration.
Shared experience is so important because, as Karl Weick so deftly noted almost twenty years ago, it provides the basis for mutual understanding or, to put it bluntly, how we understand one another when we do things together. Nancy Dixon recently offered a concise summary of this point which I recommend reading.
Trust between collaborators is an important factor related to collaboration effectiveness. Spending time talking to and learning about the people you work with provides the mechanism for trust to flourish – if they are trustworthy – or diminish – if they are not worthy of your trust…It makes sense that when people experience the same thing together – creating shared history and shared memories – it binds the group together in a much deeper way than merely having the same information.
So, you might say, what does this have to do with organizational silos?
The best way to begin answering the question is to look at an interesting insight offered by Mark Fidelman and Dion Hinchliffe regarding the cross-currents enterprises face in attempts to use social software to increase collaboration. In Rethinking the Customer Journey in a Social World they noted:
…it’s the mindset of the social world, where everyone knows what everyone else is doing, and perhaps even thinking, that may very well be the hardest to adapt to and instill in our corporate culture. It’s a world where those who know how to tap into global knowledge flows in social networks on the “edge” of our businesses will succeed. Thus, we need a new vocabulary for understanding not only our businesses, but how it will deeply affect the entire experience of our customers, from beginning to end. This transformation of thinking and working is required in order to access the significant benefits of truly remaking how we engage with the market.
Their thinking seems torn between insight into where the changes for business are headed and what they think likely to happen in the short-term. Dion in particular recognizes the fact that social business requires organizational transformation when, for instance, he asserts, ” social business is first and foremost a transformation involving people and the organizations they work with.” Yet, if you consider where he thinks the in-roads for social software (including social media) are for business over the next year or so, the contrast in perspective is pretty distinct. Dion says in another post that it is in the vertical space of enterpriseswhere most of the innovation is set to occur for social software.
While general purpose social software platforms can certainly be used in all of these areas, high impact application of social media to the way we work often requires application-specific constraints on conversations and the resultant community activity(my emphasis). This means social customer care benefits from conversations organized around support, social supply chain focused on ERP transactions, and so on, along with software that supports these applied uses.
Key factors, such as the amount of cross-functional interactions and size of community teams [with external or internal focus — my point], are putting a resource strain on community managers, particularly in large organizations.
A key organizational point is worth making here because it relates directly to the burdens the hub-and-spoke model, whether cross-functional or dandelion, places on collaboration between employees, customers, partners, and other stakeholders. Indeed, the “Tip” offered by Jeremiah Owyang of Altimeter regarding the “dandelion” hub-and spoke model is telling. He noted that,
the lines connecting the multiple hubs may be severed. Tip: provide way for spokes to connect to each other, not just be funneled through a central group.
Just likesocial networks do not respect organizational boundaries, edge cases do not respect vertical (read, silo-oriented) organizational constraints on conversation. This is an important point when you consider that most of the time spent by employees involves dealing with edge cases, i.e. exceptions to core processes. I suggest that at least part of this outcome results from the fact that not enough employees in the enterprise develop shared experiences. If you agree with me, I guess we just need to think about how to make this happen. If not, then you probably need a bit more detail which, hopefully, you can spare the time for.
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 »
People discussing the pace of change that organizations face in dealing with connected customers, globalization, competition, distributed workforces, innovation, etc. often assert that the world needs a paradigm shift to a new organizational form. I agree with the basic point. However, the way forward is seldom clear and simple when facing the need for dramatic changes in how we think about organizing what we know into practical changes to meet such fundamental challenges.
Just a side note here though. If you are not the sort of person who enjoys using historical insights to think about current challenges you probably don’t want to read the rest of this post.
Common wisdom among thought leaders discussing learning in organizations notes that most of the learning that occurs happens informally, or socially. A previous Skilful Minds post, Social Flow and the Paradox of Exception Handling in ACM , asserted:
people learning at work rely on social, or informal learning, around 80% of the time. Interestingly, I noted in a former post, Social Learning and Exception Handling, that John Hagel and John Seeley Brown contend that “as much as two-thirds of headcount time in major enterprise functions like marketing, manufacturing and supply chain management is spent on exception handling.” It is not coincidence that the two numbers are aligned.
The most basic point to remember is that exceptions to formal business processes require efforts to design a scalable learning architecture that supports content co-creation needed to adapt to emergent challenges and manage the flow of that adaptation through an enterprise’s ecosystem. Whether judging an adaptation successful requires it to result in new formal learning content, i.e. content co-creation, or a new business process, i.e. organizational innovation, or both, remains an open question.
Informal, social learning is key to exception handling since both make up most of what people do in organizing work in enterprises.
Of course, for every generalization there is usually an exception. My posts on business exceptions to this point largely focus on Barely Repeatable Processes (BRP) where informal and social learning assists employees solve issues raised by the need to improvise and handle exceptions to maintain a good customer experience, or solve issues experienced by other stakeholders such as business partners, suppliers, etc.
Recently, while reading General Electric’s A Connected World blog, one case described there led me to think about informal learning and collaboration with a different twist. It caused me to reconsider exceptions and look at the way attempts to make processes better by using working knowledge learned informally also produces exceptions in some organizational contexts.
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.
Courtesy of Wonderfully Complex’s photostream on flickr.
An early Skilful Minds post introduced The Great Innovation Debate, focusing on the distinctions between Tom Friedland’s conception that when it comes to innovation the world is flat, and the alternative point of view espoused by Richard Florida that the world is spiky. Meaning that the aggregation of creative people in cities, in proximity to one another, largely drives innovation and economic growth. As our previous post noted, John Hagel added an interesting vantage point on the debate by observing that, “Even though you can participate in innovation from more remote locations, if you want to develop your talent more rapidly than others, you are more likely to be able to do that in a major urban area.” In other words, the debate about innovation is largely a difference of viewpoints on the feasibility of effective collaboration across distributed people who work together to get jobs done. These collective efforts typically exist as cross-functional teams working with business partners, or customers.
The innovation debate was raised again recently when John Hagel and John Seely Brown added substantially to the questions behind it in a post titled, Friedmand vs. Florida and offered some key insights that coincide with key points from the McKinsey survey. The gist of Hagel and Brown’s position goes as follows:
It’s true that globalization has led to increased competition; however, there is also a significant opportunity for companies to access the talent gathering in different spike cities and then connect those people around the world using digital technology infrastructure so that they might leverage the skills of, and learn from, one another. Such a model does not develop overnight; to move from competitors to collaborators, participants must form long-term, trust-based relationships with one another. When these relationships develop, then firms can connect capabilities across spikes, and ultimately, pursue opportunities for innovation and capability building across spikes.
Consider the following observations from recent research on the importance of proximity in how team members relate to one another. A recent Forrestor report, Making Collaboration Work for the 21st Century’s Distributed Workforce (registration required) noted that most information workers (including Gen Yers) prefer email, telephone conversations, and face-to-face meetings. These preferences appear to result as much from limitations in the available collaboration tools as anything else. The Forrestor recommendations are three-fold:
create the sense of a “shared office” among distributed employees
use tools that follow distributed employees on the go
provide collaboration tools that make the work easier, i.e. are integrated into the work.
I’ll get back to the major challenge among the three outlined in the Forrestor report (creating the sense of a shared office) in a following post. First though it is important to note that the Forrestor report’s findings indicate fundamental differences between the opposing points of view in the debate over innovation by Friedland and Florida, especially as they relate to distributed employees(i.e. people who are not colocated). For example, a recent McKinsey Global Survey of 2,927 executives, Making Innovation Structures Work (registration required), offered two key insights dealing with innovation that merit attention in relation to the topic.
“Companies cannot rely on a single innovation function alone to create successful outcomes, it must be integrated with the entire organization.”
“The functions located near talent or target markets have more market success and meet objectives more effectively than others, though they are less likely than the functions at or near HQ to engage regularly with company leaders.”
The first conclusion relates to the McKinsey report’s overall insight that organizations are more likely to succeed with innovation efforts when those initiatives are integrated with corporate strategy as well as benefiting from the engagement and support of company leadership. It implicitly recognizes the ineffectivenessof organizing innovation efforts that occur incorporate silos, such as innovation centers or research & development labs.
On the other hand, the second conclusion recognizes the constraints faced in organizing innovation efforts among distributed employees. Creating a sense of a shared office, or workspace, is fundamental to efforts attempting to integrate innovation and corporate strategy, especially if the corporate strategy involves social business.
In my thinking, the key to Hagel and Brown’s point is that, as Gunter Sonnenfeld recently observed in a post called Relationship Economics, “relationships are the foundation of the social web, and the basis for the flat, seemingly infinite distribution plane that is the Internet.” Rather than focus on whether the world is flat or spiky, serious attention is better paid to how enterprises organize collaboration and what limitations placeand cultural context impose on that organizational effort to create innovation capabilities. How to organize distributed collaboration and manage the social interactions involved is the topic that requires discussion when these concerns are brought into focus.
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.
One of my earlier posts discussed the learnability of a service as a key challenge for experience design. Today I ran across this early video from Don Norman on learnability and product design. I thought I would share it.
My last post dealt with transformations in the grocery shopper’s service journey in the United States since the late 19th century, after creation of the shopping bag. It noted that, before the shopping cart was introduced into grocery stores, the shopper’s journey started with paper grocery bags and noted the transformation required to get shoppers to use shopping carts.
In recent years, local and state governments, grocers and other retailers, as well as many shoppers increasingly understand the environmental impact of using so many disposable bags, whether paper or plastic. Not to mention the direct costs to the grocer in providing the disposable bags.
Paper bags cost four cents each on average and plastic bags one cent. The cost per year in the United States is over four billion dollars, leaving aside all the unintended harm to the environment. This post suggests that shoppers exhibit a purposive desire to use reusable shopping bags. When will the large grocery chains design the customer journey to reinforce the purposive desire of their shoppers? Customers expressing such a purposive desire need symbolic resources to aid them in remembering to take their reusable shopping bags,
from here
or here
to here
and, finally, here
Let’s start off with an anecdote.
Schnucks is a grocery chain in the St. Louis area that I sometimes frequent. The particular store I shop in seems to stock the best Bibb lettuce in my area and that is the main reason I go there. Earlier this year, as I entered that store, I experienced the simplest solution you could imagine to a recurrent problem many retail shoppers face.
Someone in this store took the time to mount a reusable Schnucks bag onto a matte board and attach it to the Enter doorway. Even though I was almost in the store when I saw it, the mere sign with no call to action gave me the motivation to turn around and go to my car trunk to retrieve some reusable bags.
My household owns 15 – 20 reusable grocery bags from various retail chains in St. Louis, Schnucks and Dierbergs. I keep several of those reusable bags in the trunk of my car to use whenever I go shopping, especially for groceries. I’m sure many of you do the same with stores in your area. Needless to say though, I can’t count the times I’ve reached the checkout counter and realized that the answer to the “paper or plastic” question is, “Oh crap, I forgot to bring my bags in with me.”
For those of you who own reusable shopping bags I’d wager you know the experience. In fact, one of the reasons my household has so many of these reusable bags is that my wife often forgets also, but she is not reluctant to just buy another one or two bags instead of using paper or plastic. Don’t ask!
In addition to an inexplicable sense of inappropriateness, which my wife says she shares, in bringing a Dierbergs bag into Schnucks, and vice versa, or banish the thought, to bring a Schnucks or Dierbergs reusable bag into Whole Foods or Trader Joes, the main culprit for my failure to remember is usually just getting in a hurry.
Consider the following numbers:
40% of 1,000 people surveyed by Consumer Reports in the United States say they own reusable shopping bags and use them along with grocery supplied plastic and paper bags
17% of 104,830 people surveyed by MSNBC in the United States say they consistently use reusable shopping bags
Any way you look at the numbers, many more people own reusable bags than use them consistently. Someone at the Schnucks store who posted the sign is obviously listening to those customers who end up at the checkout and express dismay over forgetting their reusable bags. None of the other five or six Schnucks stores I occasionally shop have posted such signs. Schnucks lacks a strategic communications strategy for addressing the green customer need in question, i.e. the desire to remember reusable bags.
Schnucks isn’t alone. Dierbergs doesn’t provide signs to support reusable bag shopping at the start of the customer journey. Neither does Whole Foods or Trader Joes, at least in St. Louis. Nevertheless, the Schnucks store discussed in this post developed a workaround for the overall failure of the company to engage the shopping journey needs of its customers. It serves as a paradigmatic example of service design brought to the wayfinding challenges of grocery shoppers who are interested and motivated to minimize their environmental impact.
A customer that voluntarily expresses dismay over leaving their reusable shopping bags in their automobile trunk, or at home, is also revealing a desire, an emotional response to their own failure to remember a personal commitment to a larger purpose, i.e. they want to act in an environmentally responsible way. It is a purposive desire. I suggest that such purposive desires are relevant to service design and wayfinding, and the sections below outline how.
Grocery shopping is one of those chores that we all have to do from time to time. I’m introducing the topic of grocery shopping as a service journey not because the concept is new. In-store ethnographic studies, and shop-alongs, implicitly recognize the concept. Few people who analyze what grocers do, and how people who shop in their stores get the job of buying groceries done, would be surprised that it is a journey. And, of course, the journey starts in the shopper’s home, which Tesco’s Fresh and Easy discovered the hard way when they expanded from the United Kingdom to the United States. What I want to do here is provide a brief, high level history of the U.S. grocery shopper’s journey, and key transformations of that journey, to establish the context for my next post.
Other than time, money, and typically transportation, two pieces of technology are critical to the journey we take as we shop, especially for groceries. We must collect items around the store and move them to the checkout counter. Once our grocery items are checked out and we pay for them, we must move those groceries from the store to our source of transportation. For many of us that transportation consists of an automobile, or other vehicle; for others it may be public transport.
A partial solution to the challenge of collecting items around the store came with the invention of flat-bottomed paper bags by Margaret Knight in 1870. However, it really wasn’t until Walter H. Deubner, a grocery store owner in St. Paul, Minnesota, created a shopping bag in 1915 (a paper bag with a cord running through it for strength) that a workable solution to the challenge of collecting and moving items from shelves to the checkout counter came along. The Deubner Shopping Bag carried up to seventy pounds of groceries. In other words, at least initially, the grocery bag was supplied before customers began to shop.
The invention of the shopping cart by Sylvan Goldman in 1936 provided the basis for changing the shopping journey. Consider the problems he faced in persuading shoppers to change their shopping journey.
Goldman’s concept was simple: make shopping easier for the customer and they’ll visit the store more frequently, and buy more. Unfortunately, the customers didn’t want to use the carts. Young men thought they would appear weak; young women felt the carts were unfashionable; and older people didn’t want to appear helpless. So, Goldman hired models of all ages and both sexes to push the things around the store, pretending they were shopping. That, and an attractive store greeter encouraging use of the carts, did the trick.
Paid female model pushing shopping cart.
By 1940 shopping carts had found so firm a place in American life as to grace the cover of the Saturday Evening Post. Supermarkets were redesigned to accommodate them. Checkout counter design and the layout of aisles changed.
As a result, shopping bags were relocated in the shopper’s journey, with the exception of small bags for produce and other perishables. The invention of plastic bags later on added another alternative for bagging, in the produce section as well as the checkout counter, and it was a cheaper direct cost than paper.
Today, the result of these basic technologies for supporting grocery shoppers makes the experience much easier, no doubt less stressful on the back and shoulders than carrying heavy bags around the store while shopping. My next post focuses on the current transformational challenge facing the grocery shopper’s service journey through the diffusion of reusable bags.
My last post discussed the Open/Closed culture fallacyin social business design. I made the point that leaders of large corporations are typically unable to answer the key strategic questions posed by David Armano of the Dachis Group in a recent important post, Re-designing Your Business Culture. Among other questions, David asked:
Do we want real connections established between employees, customers, partners?
How can we reward those in our ecosystem who actively contribute?
Do we actually want to engage those who want to engage us? Can we?
As this post’s subject indicates, my interest here is to explain how social network analysis, applied to the ecosystems of organizations, helps apply social business design in a manner that avoids the fallacy of open/closed business cultures. We can’t know how open or closed a business culture is until we research, analyze, and understand both its formal and informal networks.
This post continues David’s line of thinking by considering a combination of two of his strategic questions in light of the open/closed culture fallacy. I also take a stab at noting how to answer his last question.
Think about a closed business culture. Try to visualize what it looks like. What do you see? Does it look something like a pyramid?
Now, think about an open business culture. Try to visualize it. What image comes to mind? Does it look something like a spider web turned on its side?
These two imaginings pose similar relationships between their parts. A three dimensional pyramid flattened out is about the same shape as a spider web. It is a matter of perspective as to whether one is more open or closed than the other. When connections are made across, rather than only between, the existing nodes in a network we can start to visualize informal relationships in a way that adds value to discussions of culture. It sounds simple, at least initially.
So, how do these observations relate to culture and social business design?
The presentations from Transform are now available online. Take some time and listen to these videos if you are in the least interested in how to transform health care.
Health care is increasingly gaining attention as an area in which innovation involves informal learning, and many of the other topics that go along with using Web 2.0 to engage people. The current debates at the national level about changing health insurance carry with them an underlying focus on innovation in the design and delivery of healthcare services, an area referred to for several years as Health Care 2.0. And the Mayo Clinic is always at the top of the list when innovation is discussed in healthcare. So, it isn’t a surprise that the Mayo Clinic is sponsoring a symposium in September focusing specifically on innovating health care experience and delivery.
The symposium includes a number of segments with intriguing topics. However, the two I find most interesting are the Redefining Roles and the Content, Community, Commerce, Care, & Choices segments. It looks like a promising experience for those fortunate enough to attend.
Redefining Roles
This segment will introduce the emerging roles of disruptive technology and business model innovations in making products and services in health care affordable and accessible. It will touch upon the evolution of health care delivery systems — particularly hospitals — from geographically-centered and costly entities to decentralized and more focused operations. Participants will be introduced to emerging business models in health care, including facilitated networks — online communities of people who help to teach one another about how to live with their diseases. This segment will also explore the notion that health care can be designed to minimize the degree to which it disturbs peoples’ lives.
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Content, Community, Commerce, Care, & Choices
Communities of people are sharing health care-related content online. This has come to be called “Health 2.0.” Individuals and organizations have built business ventures around sharing content. But what does it take for these models to evolve into reliable facilitators of wellness? How can these communities link with existing bricks-and-mortar care delivery systems in ways that help people in their journey to wellness? What are “microchoices” and how might they be more powerful than all of health care?
My interest in using communities to enhance the service experience goes back several years. I had not considered their application to health care services until recently when an associate pointed me to several hospitals using social media to connect with patients. It looks like a promising area for innovation and highlights the relevance of informal learning to health care services.
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.
I first took real notice of the term “social business” in a post early this year over at Peter Kim‘s blog. The concept of social business is not limited to those enterprises seeking to “generate social improvements and serve a broader human development purpose,” though these are certainly admirable goals. Rather, social business is increasingly discussed as a frame of analysis for considering the business implications of large numbers of people using web 2.0 technologies, especially social media, within corporate enterprises as employees, or outside them as customers.
Channels, policies, processes, touch points and transactions are increasingly viewed as parts of the social experience organizations use to engage employees in collaboration, and customers in conversation. The common goal of the discussion involves transforming business practices to incorporate social relationships into the value proposition to customers and other stakeholders.
My recent reading of Wired to Careby Dev Patnaik (with Peter Mortensen) provided some basic insights for me in thinking about the development of social business practices. I highly recommend it to anyone with an interest in the intersection of experience design and organization. The book explores the concept of empathy in a manner that speaks to the social business discussion by pointing out that the result of a transformation is more than adoption of new technologies such as social media.
Wired to Care offers an approach to organizing business as well as creating design insights on how to engage customers to improve products and services. One of my earliest posts on Skilful Minds, Break the Golden Rule with Customer Dialogue Support, offered the following observation,
Many “customer care” approaches call for treating customers the way you’d like to be treated—the so-called Golden Rule. Treating customers the way we, as service providers want to be treated implies that we inherently know what’s best for them. A customer dialogue approach alternatively assumes that customers know, or can quickly learn, what’s best for them as individual customers. We need to treat customers the way their actions indicate they want, not the way we would want to be treated as a customer.
ReadingWired to Care persuaded me that my previous point only moved the discussion a part of the way to an understanding of the nuances of the Golden Rule for business. Wired to Care offers an interesting point of view on the limitations inherent in the traditional understanding of the Golden Rule, while contending that a full appreciation of it reveals truths about us as individuals, and our relationship to organizations, whether as employees or customers. It outlines three levels of the Golden Rule:
“Do unto others as you would have them do unto you” — the most basic level with limited efficacy unless people share the same view of the world
“Do unto others as they would have done to them” — requires increased empathy to distinguish the wants and needs of individuals
“Do unto each other as we would have done unto us” — provides for empathy by focusing on “how we’d all like to be treated, inside the company and out,” yet also recognizes that good business practice might additionally require treating people “better than they expect to be treated”
Dev contends that the third level of the Golden Rule provides a basis for integrating empathy into the everyday practices of organizations. Though he does not use the term social business, Dev’s analysis offers a foundational strategy for implementing social business through the concept of an Open Empathy Organization.
As part of an overall critique of self-oriented approaches to innovation, Skilful Minds first considered open innovation at Procter and Gamble back in 2006. The latter post is one of the most visited here.
Given my recent focus on transformation as a fundamental concern for those interested in design and innovation, the recent publicity about P&G’s Social Media Lab instantly drew me to take a look.
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.
As a previous post noted, assessing the business value of instructional design involves more than measuring the contribution of formal training to Level 3 and Level 4 outcomes defined in the Kirkpatrick model. Training professionals also need to understand and support informal learning processes, on-the-job and off, that enhance performance. Most of the learning that produces business value occurs informally, dealing with exceptions to formal business processes, yet most of the attention paid to learning is focused on formal training.
One can reasonably say that Web 2.0 applications, such as social software and social media, are changing the relationships between instructional designers and subject matter experts much like those between customer communities and product designers. Both increasingly involve situations of co-creation.
The emerging recognition of eLearning 2.0’s importance to enhancing collaboration and performance means that training professionals, especially instructional designers, can add value to their employer/client’s business by learning to facilitate and manage the co-creation of learning content with employees, or even customers. Anyone experienced in instructional design in recent years is familiar with the general challenge of co-creation whenever they use information content for course design ( slide shows, documents, etc.) that subject matter experts originally created as a resource for a presentation. The presentation content too often is substituted for observation and in-depth interviewing as a first step in analysis.
Such Rapid eLearning, though shifting content development toward the subject matter expert’s control, maintains the traditional role of training in incorporating design principles. The process of co-creation in eLearning 2.0, on the other hand, shifts control over development and distribution of learning content toward subject matter experts willing and able to share what they know, especially when they see other people who need to solve familiar problems.
Dan Saffer’s recent book, Designing Gestural Interfaces, makes you think anew about the hand dryers and faucets in public restrooms that respond to waving hands. In fact, Dan notes that gestural interfaces are currently found in specialized products paired to specialized activities in specialized environments. As he observes,
Public restrooms are currently a great example of this, but other spaces could easily take on this sort of “hothouse” environment. The next likely place for such experimentation is kitchens: they feature lots of activities, plus a contained environment with tons of specialized equipment (pp. 160-161)
Designing Gestural Interfaces is the first attempt I’ve seen to provide an in-depth discussion of the challenges in designing devices that people control through gesturing. Although it isn’t the central point of the book, Dan discusses restroom interfaces that wet hands, dry hands, flush toilets, and dispense SaniSeats. And one of his example photographs is notated, “Apparently, public restrooms are excellent places to find gestural interfaces.”
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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.
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Posted by Larry Irons 
Even though I was almost in the store when I saw it, 
I first took real notice of the term “
As a 
Skilful Minds 