By Thierry de Baillon
Version française ici.
History, we know, is apt to repeat itself, and to foist very old incidents upon us with only a slight change of costume.
George Eliot
New technology is often disruptive, and social technologies make no exception. Today, quite everyone agrees on the necessity to focus on cultural change to help embracing the new behaviors they enable, and there is quite a consensus on the levers which might make the shift happen. Pilots, either as small scale projects or as fox-in-the-henhouse tools, are common practice, and integration into the flow of work is this year’s new black. Those are, in no doubt, pragmatic catalysts for change. But… are we really focusing on the RIGHT change?
And the pocket calculator hit the school system
Pocket calculators were banned from examinations for a long time after being allowed in the classroom. Then, gradually, they made their first official appearance as digital replacement for arithmetical and other mathematical tables. In accordance to Moore’s law, the power of calculators grew rapidly, and the school system began to foresee much larger applications for these devices.
In France, an official document officialized the use of any type of pocket calculator -even programmable ones- in 1986. Furthermore, their use was largely encouraged during mathematical classes. But the interesting part isn’t the fact that teachers recognized the benefits of the technology and further promoted them (‘adoption’ and ‘empowerment’ might sound familiar to you), it is what these benefits were intended to be. A new version of the document, still applicable today, was published in 1999, explicitly setting the purpose of calculators’ use. Translating from French:
Mastering the use of calculators use represents an important goal in every student’s training, as it constitutes an effective tool to be used in their education and during their professional, economic and social life. For these reasons, their use is planned in many teaching programs and should be widely accepted during examinations and competitive exams.
In other words, calculators’ mastery is now required because of the way they allow faster and more sophisticated calculation, and are a good introduction to man-to-machine language. Wow… Where we could free students from tedious tasks to focus on higher level concepts, leading to a different mathematical culture, what we got is mathematics-as-usual on steroids, and a focus on technology.
Redefining organizations
For more than a century, our economies has been based on a paradigm where profit derived from production of goods and accumulation of assets, and where offer-and-demand markets where the only measure of customers’ satisfaction. Today’s globalization has displaced production toward less costly countries, and it won’t be long before intellectual production follows manufacturing of goods. What can be replicated, it can be outsourced. Markets reveal the internal complexity of interactions between capital, capabilities and irrational considerations. Uncertainty has replaced growth, and there is a growing and unsustainable chasm between the civil society and big corporations pursuing their own goals.
In this context, unleashing the power of horizontal networking inside and across organizations represents a promising answer to some of the toughest challenges our companies, and, beyond them, our society, are facing today. Businesses must repurpose themselves, and adapting to these challenges means acknowledging that work, as a set of activities, is changing nature, and that organizations must redefine themselves.
This shift is already happening on the public web: Clay Shirky, and others, have shown how social technologies foster resilience and creativity, and allow the connective tissue of our societies to take back their central role in human life. Alas, on enterprise side, what we are seeing is mostly the use of these technologies to enforce work as usual, the change we are calling for is too often a desperate chase to more productivity and efficiency. As history tends to repeat itself, social technologies are the new pocket calculator.
Sandboxes, not pilots
What is the purpose of an Enterprise 2.0 pilot project? The no thrill answer is obvious: they are set up to facilitate the diffusion of Enterprise 2.0 practices into the organizational culture, and to demonstrate business value. They allow, often through trial-and-error iterations, to blend the impact of social technologies into the operational structure of a company. They are not meant to help redefining the nature of work by fostering new behaviors, they are instead meant to leverage these behaviors to enhance the way work is presently done. The numerous experts talking about implementing social technologies “in the flow” don’t say anything different.
Social technologies DO HAVE business value, indeed, and that value is far more important than the transitory productivity gains that many tend to highlight. Most of the problems businesses tackle today are way too complex to be addressed the way companies are run today. Networked communities are better armed to deal with wicked problems than any leader, no matter how insightful or visionary he could be. In that sense, Steve Job’s resignation from Apple is highly symbolic: it somehow marks the end of an era, the one of lonesome visionary leaders.
Rather than thinking in terms of pilots, it is time to open sandboxes throughout organizations. Time to allow open, free-willing individuals to gather around real business problems, whether they are financial, strategic or organizational, and to let them probe and discuss how they could solve them. Here lies the real power of social technologies. Empowering employees is not about giving them more tools or putting higher performance expectations on them. It is about opening up what really matters, and giving them the power to influence the destiny of the company they are working in.
With big data comes big challenges
Integration is another social business buzzword on these days. Integration into work, integration into our systems’ architecture. This is, of course, a view suitable to a finite world, where most of business activities and outcomes can be stored into a system of record, and correspond to our process-based neo-industrial organizations. Here too, social technologies suffer from the pocket calculator syndrome. But companies can no longer ignore the outside world, and the necessity to take account of your customers in core business practices will radically change the nature of work and our reliance on today’s IT architectures.
We are only seeing the beginning of an era where data, and the way it flows freely in real time, relegate systems of records into the dark age. Social CRM is setting the basis for a future where interpreting and inferring patterns from customers’ interactions will become an important part of work. Handling and interpreting big data meaningfully will come with more uncertainty and complexity than today’s IT architecture can cope with, and will require changing most of today’s assumptions about how we deal with technology.
As an example, consider the evolution of weather forecasting. The more powerful the models are, the less precise they become. Among the characteristics of complex systems is that their evolution can only be predicted if the original set of conditions is known. The more parameters we introduce, the more precise we have to be in order to get coherent results.
A lesson from history
Pocket calculators, in France at least, changed the way mathematics are taught, but not in the right way, and didn’t change the essence what is taught in courses. Social technologies have a similar power to seed and sustain an inevitable change in work requirements and organizational redefinition. Let us just be sure that history won’t repeat itself.
By Thierry de Baillon
Version française ici.
This post is the second of a two-parts article on design thinking co-written with Ralph-Christian Ohr (@ralph_ohr). You can read first part here.
The world we live in becomes increasingly complex. Complex systems in different areas of our life, such as business, environment, economy etc. involve ever larger numbers of interacting elements. Particularly human interactions are non-linear and result in a basically unpredictable system behavior. One major consequence of complexity is the fact that we have to deal with rising problem wickedness. Ted Cadsby remarks in an interesting post:
“The hallmark of a wicked problem is that it cannot be reduced to a single-cause explanation. Complexity arises from the interconnections between things – how parts within a system interact via intricate feedback mechanisms. The information signals we need to make sense of complex things are buried in a lot of noise, and we, unfortunately, are not adept at digging for cues. We have been conditioned by thousands of years of evolution, as well as our daily routines, to draw speedy conclusions by picking out simple, linear, cause-effect connections. This approach works well with straightforward problems like securing food, shelter and sex, or crossing a busy street. But we are now living in a world where multivariate and non-linear causal connections hide below the surface of our immediate perceptions, and diverge to different possible interpretations.”
Wicked problems are termed as “divergent” as opposed to “convergent” problems. For a so-called ‘tame’ problem, the problem definition is – though it might be very complicated – well understood and promises a solution. The more it is studied, the more various answers sooner or later converge. A divergent problem isn’t well defined and does not promise a solution. The more it is studied, the more people inevitably come to different solutions and interpretations. The process to tackle tame problems is assumed to be fundamentally linear, comprising a sequence of steps leading to a desired outcome / solution. In a complex environment not even a shared problem understanding can be taken for granted. We don’t know what we don’t know.
The question arises how wicked problems, emerging from complex systems, can be properly addressed. We’d like to suggest three ‘pillars’ that seem to be crucial in this context:
Experimentation
Complex contexts and wicked problems require an experimental approach. Because outcomes are unpredictable, decision makers need to focus on an environment from which good things can emerge, rather than trying to bring about predetermined results. This comes along with a tolerance of failure and the ability to refrain from imposing order. It’s essential to let patterns emerge and to determine which ones are convenient. Every experiment exposes new aspects of the problem, leading to further adjustments of the following solution proposal. In place of finding ‘the right solution’, problem understanding and solution must be woven together from beginning to end through explorative iterations.
Diversity and collective intelligence
Wicked problems solving naturally involve a diversity of stakeholders with different perspectives and interpretations. Given that many people care about or have something at stake in how the problem has to be / could be resolved, the process of solving a wicked problem is fundamentally social, and solving a wicked problem is fundamentally a social process. Shared understanding turns out to be a prerequisite for tackling wicked problems. It requires that stakeholders understand each other’s positions to have fruitful exchange about their different viewpoints of the problem – and to leverage collective, holistic, rather than fragmented or individual intelligence, to solve it.
Interpretive approach
A wicked problem usually implies a radical uncertainty, i.e. not simply an inability to predict which of several options will turn out to be the preferred one. No shared problem understanding exists and the context appears so complex that not even the possible outcomes are known. And in the absence of a specified solution, no analytical problem solving can be applied by breaking the problem up into a set of separable parts that can be assigned to different specialists. According to Lester and Piore (“Innovation – The Missing Dimension”), an interpretive approach is indicated in this case. This approach doesn’t target at solving problems or negotiating between contending interests, but at initiating and guiding conversations among individuals and groups. Involved people work through ambiguity and construct shared meaning. Through that process the participants come to understand each other – and themselves – better than before. It’s an open-ended process allowing insights and novelty to emerge.
The distinction between analytical and interpretive approach determines two different ways of understanding teams:
- Analytical perspective: teams are formed and re-formed of different members with particular competencies required,
- Interpretive perspective: teams can be organic groups that develop their own language and understanding over time and become greater than the sum of their competencies.
These ‘pillars’ get back to the constituting elements of a complex adaptive Design Thinking framework, outlined in the first part of this post.
Complexity doesn’t nullify present business models and processes, but it taints more and more of their effectiveness and relevance. In order to be prepared to face increased wickedness and complexity, organizations need to make sure to implement those pillars. Leadership is required to set directions, rather than goals, and to facilitate a culture where experimentation, ambiguity and uncertainty tolerance are valued.
This ambiguity should be reflected in the organizational design itself, as wicked problems often arise “on the edge”. Even if disconnected to main business operations, dedicated spaces need to be created for collaboration, empathy and conversation. Those spaces allow for transformation of diverse, subjective perspectives into collective insight and understanding. Furthermore, it’s mandatory to educate and hire appropriate people, being capable of following this approach and of unfolding their potential in such a collaborative environment.
Takeaway:
Increased complexity requires a transformation in the way we approach problems. While conventional problem solving is highly analytical, resolving wicked problems can be tackled by a design-oriented approach. Through combining experimentation, diversity and interpretive collaboration, subjectivity of individual stakeholders can be transformed into shared insight. Design Thinking based on these elements has true potential to be leveraged as social framework to utilize collective intelligence.
By Thierry de Baillon
Version française ici.
This post is the first of a two-parts article on design thinking co-written with Ralph-Christian Ohr (@ralph_ohr). As businesses are more and more challenged by the wicked nature of the problems they face, whether in strategic or operational context, we need to integrate more divergent and resilient reasoning in our decision-making practices. Cleared from all the fuss which so often surrounds it, design thinking could provide the ongoing transformation of businesses toward “social” with an actionable framework to leverage the true potential of collaboration.
Design Thinking is quite a strange animal. Attempts to define this discipline, in fact as old as creativity, framed by Tim Brown, IDEO’s CEO, in his HBR article published in 2008, are as numerous as practical evidence of design thinking in action are. Trying to broaden the scope of design thinking from the design field to the one of complex business and societal problems had raised the need for a much more formalized approach. Practical reasons abound: how could you sell services based on a methodology which only defines and unfolds itself during execution? How could you convince executives that pattern matching and sense-making are as much relevant than proven tracks of expertise in a given domain?
Connecting design thinking with the broader context of problem solving has lead to the growth of two equally harmful myths: the guru designer and practice as a process, emphasizing on subjectivity or linearity where empathy, empowerment and divergent thinking are needed. Design thinking isn’t saving the world or revolutionizing business, for sure, mostly because of these two illusory paths. But before throwing the baby out with the bath water, and stating, with Bruce Nussbaum, that “Design Thinking is a Failed Experiment“, it is worth considering what is turning wrong. Speaking of creativity, learning from failure (if any) is usually a much more fruitful attitude than shooting the messenger.
A process is a process is a process
To allow design thinking to tackle business problems beyond design, it was assimilated to a process. One can easily understand that design thinking doesn’t fit the usual focus on linearity and convergence, so important in the conventional culture for efficiency most organizations emphasize on, and suitable for most traditional innovation approaches. This is an important issue, don’t misunderstand me, but do you really think that companies which give so much credit to Six Sigma or CMMI would welcome design thinking as a serious problem solving discipline? My bet is no. Of course, framing it as such a kind of process was, from the beginning, deemed to failure. There is a problem with “design thinking as a process”, but where does it really lie?
Contrary to expectations, “process”, in the business universe, has no straightforward definition. Processes do not necessarily rely on linearity and certainty might sometimes be fuzzy (think Adaptive Case Management), or divergent. Nevertheless, every flavor of business processes shares a common feature: an intrinsic independence from the people operating them. In this context, even when confronted with the most innovative organizational culture, “design thinking as a process” cannot fit. Not because of the mess and fuzziness associated with creativity, but because of the subjectivity involved: design thinking is highly interpretive and subjective, and most of its outcomes are dependent from the designer’s capabilities. Here lies the catch: this subjectivity is the disease which prevents design thinking from living up to its promise. Here lies also a paradox: subjectivity is as much a problem as it is a necessity. Without it, we fall into the dry world of business processes, unable to sparkle creativity. With too much of it, the ugly head of the guru designer shows up, enforcing a vision which fits more the designer’s ego and reputation than true business needs.
A complex adaptive framework
Most of the problems design thinking intends to solve have no unique formulation, no single solution. Despite the many definitions given, framing design thinking itself is a challenge. For many reasons, it can be considered as a complex adaptive framework aimed at addressing other complex dimensions of business. I view the whole design thinking approach as navigation through a fitness landscape: the problem occupies the base plane, while the third dimension symbolizes the “validity” of possible solutions. Framing the problem means picking up a starting point on the problem plane, then the whole approach consists in climbing up the hills in several directions, through iterative methods, until maxima are reached.
The choice of a starting point is highly subjective, and relies on designers’ personal background, experience, empathy and intuition. There is nothing wrong here, except that complex systems behave according to initial conditions, and this behavior cannot be mastered unless all parameters are known. Little changes might lead to vastly different outcomes, and further actions might well end up in dead-end local maxima, far from optimal solutions. It takes a leap of faith for businesses to follow such tracks. Who will decide which starting point is better, if both satisfy the context? How could the degree of “fitness” of any chosen direction be measured, unless pursuing them all up to the end?
Fractal behavior is another characteristic of complex adaptive systems which closely relates to design thinking. As prototyping and testing takes place, design thinkers progressively gets into details from feedbacks, those details belonging to the same initial formulation of the problem at different scales (global design, ergonomy or touchpoints, realization capabilities,etc), each scale being as important as the initial approach in the overall solution taking shape. A problem is that, at some point, one scale might not fit the solution at all, and little overlooked changes might produce huge changes in the overall system. You might, for example, tumble into a feature which might disrupt the manufacturing capabilities of the company you are working with. At that time, what can be done? It is usually a matter of jettisoning the work made at larger scales and jumping back into a different part of the problem space, switching to a vastly different solution because of a tiny, but critical, detail. Such a disruptive move means creative destruction, and isn’t an easy decision to make, as it involves highly subjective dimensions. Design thinking is about decision making – instead of boiling down a problem to one large decision, designers make lots of little decisions, learnings as they go. Therefore, navigating complex problems and ambiguity through small, iterative trials is highly determined by a subjective and continuously challenged assessment of the context.
Design thinking = critical thinking + design doing
In the hope to be better accepted in the business world, design thinking has given up the subjectivity associated with experimentation, and without which creativity simply doesn’t exist. Similarly, in its search for a better way to find solutions, it has forgotten that problems cannot always be framed without ambiguity.
Back in the eighties, I remember attending a meeting in a Japanese fabric company. The meeting’s goal was to agree on next season’s trends to start the manufacturing of new fabrics. Attendees, which included designers, product and sales managers, discussed about colors and textures for several hours, often taking little thread samples in their hand and rolling them together to get a concrete view of how it would look like. At the end of the meeting, no decision was made. Attendees didn’t agree on anything but general color trends, but kept some of the hand-made thread samples for further exploration and technical feasibility, ready to produce fabric samples for testing.
This was an enlightening experience for me, and still is thirty years later. It superbly illustrates how design thinking could thrive at resolving complex business problems. Critical thinking among stakeholders is a much better way to seed creativity than relying on individual designers. Early parallel and conflicting exploration holds more promise than relying on individual bias. The activity out of which something innovative emerges, is social and highly interpretive. It involves guiding connected conversations among individuals and groups to determine the range of alternatives from which convergent choices are made.
Subjectivity is a key component of design thinking which, to be accepted and profitable for businesses, should be tightly tied to organizational context. This requires a novel, and more resilient, approach to design thinking: we need designers who have a sound understanding of all the parameters involved, leaning on networks and groups of stakeholders, harnessing critical thinking, and linking outcomes to their own range of experience and expertise, through design methods. Let us call that parallelogram-shaped designers (strong specific business understanding linked to strong design expertise) in a collaborative enterprise. I sense this might also be a good definition for management 2.0.
Read Part Two
By Thierry de Baillon
Version française ici.
Our world is changing, so is the way we are thinking about it. The rise of online networks has not only modified our possibilities to connect and exchange knowledge with other people, but also has it given anyone with internet access a new, almost (not yet totally, but for how long?) unalienable, power. From charities to tyrannies, from companies to markets, a lot of this power is shifting to citizens and customers. Paradoxically, the more people gain access to it, the less we can think in terms of mass. Individuals, their diversity, their relationships, their interactions, matter more than the standardized bulk dynamics prevailing in the industrial logic.
To adapt to this change, organizations have to reinvent most of the ways they operate. Customers are no more passive buyers to target. Companies are no more fierce industrial strongholds aimed at infinite growth and bracing their back against long-term competitive advantages. Work is no more a clearly designed set of tasks, defined by roles and rewarded by career paths. Trees grow no more to the sky. Previous equilibrium between production, sales and profit is broken, and a new one is required, which embraces the evolving complexity of relationships between customers, companies and workers.
SD-logic and co-creation of value
Service-dominant logic draws a framework in the quest for such an equilibrium. By switching from a transaction-based model of organizational justification (I sell therefore I am) to an interactive model of value creation, it provides us with critical insights on the necessary mutation economic actors must undergo to survive in an ever more challenging environment. I already wrote about service-dominant logic (and you can learn a lot more here -and on the SD-logic website if operational again-), but, at the risk to oversimplify the works of Steve Vargo and Robert Lusch, let me recall some basic principles of their theory: companies do not market products for customers to buy; they make proposals (of products, of services) which customers hire (thus on a momentary, but not instantaneous, basis) to help them get their job (the real-world activity they want to use the product or service for) done. Value is co-created by company and customers during the whole length of time the customer uses the product / service.
For companies, beyond profit and other measurable benefits (reputation and loyalty for instance), value means knowledge about their customers’ needs, expectations and uses, which drives further development of better products and services, and better engagement. For customers, value also means knowledge about how to better fit their needs. Through value co-creation, both parts evolve.
Furthermore, value is neither created in the void, nor in a simple dual firm-customers relationship. People talk, compare, their own networks influence the overall value creation. Companies, too, are part of networked ecosystems composed of suppliers, subcontractors and many other stakeholders. As more and more people share knowledge through their online networks, as more and more companies get in the use to listen and engage with them, they will get more and more involved into customer-driven innovation, and will co-evolve.
The dynamics of co-evolution: competition
Co-evolution dynamics are originally related to natural ecosystems and living species, but are more and more considered in organizational and societal theories, as an inherent part of complex systems behavior. Co-evolution happens when a system and its environment, or different subsystems, are influencing each other to change.
The first kind of co-evolution is competitive: a system evolves to gain advantage onto another, in a typical predator/prey relationship. As more companies turn to customers and other parts of their ecosystem for added value, they will compete for what best serves their needs in a particular category, which involves several risks.
The first risk of a purely competitive co-evolution is relativism: competition involves getting advantage, but a subcontractor may work for several competitors (as Vargo and Lusch acknowledged), or customers may give insight in reference to competing products (imagine I own both a Kindle and an iPad). Companies may end up trapped in a kind of Zeno’s paradox, a zero-value sum, driving just enough innovation to get closer to their competitors’ best proposal.
The second risk is called the Red Queen’s dynamics, and is a hypothesis formulated by the American biologist Van Valen in 1973, stating that co-evolution in tightly related species doesn’t preclude any of them from extinction, whatever the number of precedent evolutions might be, and more and more considered in economic research. In our business context, it means that companies might be obliged to dedicate more and more resources to value co-creation, thus to evolve, not to thrive, but just to stay in the competition. Following the Red Queen’s hypothesis, engaging in that sort of arms race would equal, for companies which aren’t deeply involved in design-driven innovation, an overwhelming takeover by customers.
The dynamics of co-evolution: cooperation
While a truly cooperative economy might be seen as a mere utopia, cooperation, whether between firms or with customers, is a business reality. Whereas collaboration’s dynamics, requiring aligned goals, resources and outcomes, are mostly endogenous and pertain to a shared system’s level, cooperation takes its power from diversity, empowering each actor through shared information and behaviors. Meaningful sustainability initiatives assume active cooperation between whole business ecosystems and customers. Coopetition, which combines cooperation and competition, is gaining acceptance as a powerful business strategy in our networked economy.
Still an emergent domain of research, cooperative co-evolution doesn’t suffer from the same flaws as its competitive counterpart. Furthermore, it provides to value co-creation an interesting analogy with the cognitive learning process; all actors gain and create knowledge from information available, according to his own needs, expectations and personal background. Could we therefore use the different types of cognitive learning to provide a practical frame to the promises of the service-dominant logic? That’s a great perspective I would love to discuss with you. Online networks are transforming the way we behave, chances are good they will transform the way business is done. For better.
By Thierry de Baillon
Version française ici.
As ever increasing speed and amount of available knowledge are reshaping day after day the world we live in, it looks like a gap is widening between the way most businesses still operate and the capabilities needed to deal with our environment’s growing complexity.
Organizational responses to overall increasing speed too often are costs reductions, automation and optimization. Efficiency has become the new business’ black, and BPR is its credo. But speed isn’t only a factor we have to cope with; it is deeply transforming the nature of our relationships to the world. As Paul Virilio wrote: “The speed of light does not merely transform the world. It becomes the world. Globalization is the speed of light.” When considering speed as an external constraint, companies are keeping themselves deliberately out of many of today’s new fundamental dynamics. Pushing the gas pedal won’t drive anyone faster than the engine was built for, and current business engine was assembled in the — industrial – XIXth century, and amended more than thirty years ago with the rise of the process-driven enterprise.
The shy face of Enterprise 2.0
On every subject, for every aspect of our life, the quantity of information available is so tantalizing, that we cannot simply store all information we need at some time into our memory anymore. Such abundance has transformed our cognitive process: we now mostly remember links and references to information, extending our memory map, our knowledge, to a network of peers and sources. The more information is made available, the stronger and wider this network becomes, and the faster knowledge is able to flow. This networked nature of our representation of the world in turn participates in increasing the global speed of the world.
One major Enterprise 2.0 frameworks’ motto is to help companies to deal better with this information overabundance, to make organizational knowledge expandable and faster to access, with the help of social software: connecting with the right information at the right time. So far so good. Power has shifted from knowledge to knowledge sharing. Cool; but for how long? Even if there is little hope to break the 90-9-1 rule in organizations, information is becoming ubiquitous in an exponential way.
A recent attempt to deal with this growing quantity of knowledge flows is content curation, to allow for a better distribution of information. Unfortunately, this only helps facilitating knowledge acquisition when the desired outcome is already known, since what is relevant to you isn’t necessarily so for someone else, or even in another situation. Context is missing here. What we need is another way to filter information in context, another way to make information usable through non-deterministic tasks. The real power resides in knowledge use, not in knowledge sharing.
Another motto is to start with clear objectives. Business objectives… When quantity of information and speed of transmission are changing our way of thinking, are deeply transforming our lives, is it reasonable to believe that aligning corporate practices with private habits will spare us to rethink the way we work, the way we do business? Can we seriously think that getting from silos to clusters will save us deeper organizational transformations? Yes, we have to set up business objectives to any collaborative initiatives, but we have to consider which new kind of objectives can be achieved through social business, and what it means for the future of business.
The poor performance of processes
Umair Haque recently stated that “Making Room for Reflection Is a Strategic Imperative“. This is a nice injunction, backed with lucid and thoughtful arguments, but can we just “stop doing”, in an environment where speed has become the very stuff of things? I don’t believe so, taking a break is no more an option, and what we really need instead is to think differently. Accelerated growth of available data requires new ways to acquire knowledge and put it into action. In such a situation, unlearning has become as important as learning.
As most of our knowledge is now stored outside of our memory, the challenge not only lies in matching real-world situations with experiences stored in our memory, but also in pairing those situations with the right external connections, in order to gain access to the relevant knowledge. Not only do we have to deal with data, in anything but routine thinking, but with people, and our cognitive process now encompasses our networks. Information retrieval, and learning, had become inherently hyper-connected.
From internal “social” initiatives (let us consider them as knowledge networks rather than true collaborative environments for demonstration purpose) to customers’ relationships, present process-based approach to business is broken. Business processes expect a deterministic output; they rely on repeatability and explicit workflows, which often proves itself far from the nature of human relationships. The cognitive process, instead, is a non-linear mechanism, able to make sense from disjointed information. Cognition doesn’t appeal for processes, but for patterns. Furthermore, processes suit perfectly machine-to-machine communication. Human-to-machine communication needs to take into account user experience, which hardly resumes to processes, and human-to-human communication is all about weak signals and pattern recognition.
Knowledge work is all about patterns
Venessa Miemis has written a great post about the importance of patterns recognition in the cognitive process. To quote her: “there are strong and weak signals all around us, patterns, which indicate a change has happened, is happening, or has the potential to happen”. Business processes work as long as nothing changes, or at least changes slowly, which happens less and less in present business environments. Dynamic patterns, instead, are emergent phenomena of complex systems. They are highly adaptive and relate not only to existing flows (whether they be knowledge, work, customer journey, etc.), but also to how these flows change over time. In other words, they can be harnessed as predictive tools as well as operational routines design. A simple change in an underlying process might translate into huge and fast modifications of related pattern. Looking at the way patterns change (sometimes dramatically) in our networks provides us critical clues on how to improve broken processes, or on when to seamlessly switch to another one.
Here is a short summary of dynamic patterns versus processes characteristics:
| Processes |
Patterns |
| Linear |
Non-linear |
| Designed on purpose |
Emergent and self-organizing |
| Inside-out |
Mostly outside-in |
| Hard to change |
Highly adaptive |
| Need stability to perform |
Require instability to form |
| May cause formation or modification of a single pattern |
May emerge from multiple different processes |
Patterns are already used in business context. Emergent practices leveraged from online communities are patterns. Ethnography, and many design thinking methods, invoke pattern recognition to decipher customers’ behavior. Social learning implies the use of patterns in knowledge acquisition. Dynamic patterns are much more adapted to knowledge work than business processes are.
As they can be broken down to processes, monitoring patterns’ evolution in networks represent a promising way to handle the exceptions crippling most of the processes in which human interaction is involved. Integrating pattern recognition into work might require dedicated competencies, but it also requires new approaches. Adaptive Case Management is a promising framework to help dealing with knowledge flows rather than with processes, considered the fact that not only should we focus on information, but also on the way information, and connections to it, changes over time. Time has come, to understand that information is not only the blood of our networked organizations, but also their bones.
By Thierry de Baillon
Version française ici.
Whether we like it or not, everything seems to have gone ‘social’. Social media (which has for me only little to do with media), social business (on which I merely agree with Stowe Boyd’s definition), social platforms, social commerce…
One of the latest additions to this list ‘à la Prévert’ is social customer. Our customers are now chatting online, extensively using (or not) social media, and we, benevolent companies (we are not yet social businesses, but will be very soon), are listening to them, engaging with, and, ultimately, selling them our products and services, which they will afterword comment together in social networks… This looks great, except that the social customer doesn’t exist.
Customers are still customers, regardless of how you look at them, and the fact of using new tools doesn’t mean they will buy more of your social-mediated products. Calling your customers ‘social’ is a lame attempt to say: “hey, we are a social business, notice how cool we are: we are both tagged as ‘social’. So let’s be friend, and for sure you’ll love what we are showing you”.
It is time for companies to grow up, and that rather than calling their customers ‘social’ and focusing on tools that are mostly meant for private conversations, they begin to build trusted relationships through their own channels and tools, and follow a business -not bozo- logic. Your customers deserve to be considered seriously, so does your business.
More on that in the presentation below:
By Thierry de Baillon
Version française ici.
Terminology, as language itself, always had a huge impact on our thinking. Considering the pervasive place social media has taken into our online lives, from mundane Facebook conversations to companies-wide collaborative platforms, including strategies as diverse as Youtube-based marketing campaigns, Social CRM initiatives or open innovation frameworks, it appeared to me interesting to look a bit closely at the words themselves: ‘social media’.
Conversely to Web 2.0, or Enterprise 2.0 (or anything 2.0, as far as it seems), the term ‘social media’ doesn’t have a clear origin to trace back. Despite that, it appears that everyone knows about it and has a more or less clear (even if not expressible) idea of what it is. Isn’t ‘social’ about conversation, and ‘media’ about the channels (technologies) that support it? Yes, of course, but meanings are obstinate, so let us listen to what the words themselves have to say.
Social by nature
When writing “Du contrat social” in 1762, Jean-Jacques Rousseau was, after John Locke, theorizing and popularizing the meaning of ‘social’ being the fact of pertaining to a human society as an organized (and beneficial) structure. In this sense, all of our interactions are social. Work, by nature, is social, since implying active interactions inside an organized system.
Symptomatically enough, ‘social’, as in ‘social media’ and most related concepts and tools, seems to relate more legitimately to the ‘outside’ world, where individuals discuss and interact ad libitum, than to enterprise’s world, where its use is even perceived as controversial. It looks like, in executive’s language, the word’s side connotations (of friendliness or of welfare handling) had taken over the deep political and economical implications of the word and of its use. Social CRM, for example, relates to interactions with customers, not to an internal collaborative evolution of CRMs.
Does that really make sense? ‘Social’ is at the heart of our organizations. It isn’t about Facebook. It is about how people interact with each other, how they exchange knowledge, and about the patterns emerging from these knowledge flows. It is the way we manage capabilities, hierarchies, practices, and collaboration. It is the way we drive business and profit. The necessity to deal with the shift needed to cope with a hyper-connected economy, with customers and workers new needs and expectations, cannot be avoided forever, and ‘social’ kept out of the work realm for long.
From media to mediation
Similarly as we underestimate the ‘social’ dimension of ‘social media’, we routinely overestimate its ‘media’ dimension. ‘Media’, as a singular noun, first appeared in 1923, the very same year the first commercial appeared on radio. Since then, its definition shifted from “a means of conveying something” (the original definition of medium) to “a channel broadcasting information”. Media is not about conversation (a two-way exchange of information), but about one-way diffusion of information. Or even, as McLuhan explained in “Understanding media”, about one-way influence this channel holds on our cognition.
Bill Ives, in his last post, pointed me to Douglas Coupland’s book about McLuhan, and to David Carr’s review. Carr quotes McLuhan: “The global village is a place of very arduous interfaces and very abrasive situations … When people get close together, they get more and more savage.” But is this vision, while striking if we look at individuals as a myriad of broadcasters, still relevant if we stop thinking in terms of pushing information through multi-fragmented channels and instead immerse ourselves in a global conversation?
It is no wonder brands began to think of ‘social media’ as new conveyors for push marketing information the same way they broadcast advertising in most other channels –and many still do-; the ‘media’ word is a testimony to that immature interpretation. But this is a reductionist view of what is really happening online: ‘social media’ have become true multiway channels to mediate exchange of knowledge.
It might be time to consider ‘social media’ (or should we say ‘social channels’) from a true ‘social’ point of view: a disruptive environment where knowledge flows freely, and sets the base for a new economical and political ‘social contract’.
I would love to hear your view about that and, oh yes I am late, I wish you a very very very happy New Year.
By Thierry de Baillon
Version française ici.
Business processes has recently became quite a buzzword among the Enterprise 2.0 community, notably since June’s Boston conference. It suddenly seems that the whole discourse has changed from a leadership-fueled point of view to a down-to-the-ground (and to the balanced scorecard) vendor’s one. Pragmatism? I rather think that this approach is severely flawed, in three places at least: core processes concepts, knowledge handling and customers’ consideration.
When cats are called dogs
I recently wrote about SAP StreamWork and the fact that, despite their claim, this new tool is not a collaborative decision-making solution, but allows for better collaborative problem analysis, which is not, and by far, the same. Mistaking the mean for the goal is a clever tactic: this allows for frictionless adoption of an otherwise useful tool into existing processes, with the added hype of 2.0 technologies.
In a much more subtler register, Bertrand Duperrin made a common mistake in one of his last posts ‘Community management and processes by the example’. What he calls “process” is in fact a resource lifecycle, describing who is involved, when, in relationship to whom, where a process is a matter of chained actions allowing to progress through this lifecycle. Substituting communities for individual along the flow is of course an improvement of the entire lifecycle, but has de facto no impact on the process design or execution. The difference is important, since processes were developed to minimize variability and risks, specifically facilitating and streamlining execution when different silos, different business logics, are working in parallel through complicated operations and/or organizations. Moreover, there are designed to be as people independent as possible. They are typically built to avoid “reinventing the wheel”; but what would happen if tapping into the networks comes out with a solution which doesn’t require a wheel at all? Predictability is processes’ mainspring and, unless breaking them into much smaller, adaptive, parts, which contradicts their efficiency chasing goal, socializing resources lifecycles won’t have any positive impact on existing processes, besides giving the opportunity to integrate 2.0 technologies into workflows. This clearly is a dead-end for anybody believing that Enterprise 2.0 is more than technology.
Processes are Taylorist knowledge
Cecil Dijoux recalled Michael Grives’ interesting distinction between processes and practices. Unfortunately, practices, built upon people’s behavior, and not upon the least variable output available, still fall short from giving us a way to harness collaborative work. When it comes to knowledge, they behave quite the same, fossilizing thinking into formal procedures.
Fostering the use of tacit knowledge, which represents 80% of available knowledge in an organization, requires a much more flexible framework than those given by processes and practices. Knowledge is variable, unfocused, complex, and messy. By building automatic workflow rules, by assuming that today’s conditions are the same as yesterday’s ones, processes segment knowledge into bits of repeatable information and decision making guidance, exerting a division of knowledge similar as the division of labour envisioned by Adam Smith. Socializing business processes won’t take advantage of collaborative work, but of specialized cooperative knowledge. The only feature of processes which might benefit from social integration is their ownership.
The customer-centric Enterprise
Besides owners, processes have customers. Dealing with internal customers is usually a matter of connecting dots, which often means offering predictable output through connected, repeatable, actions. This could be fine, regardless of the two precedent points, as far as external customers are not involved. But the social web is transforming the way customers act and react in a radical way, and maintaining our business processes to engage and interact with customers is nonsense. If capturing internal tacit knowledge in a non obfuscating way is a challenge, ignoring customers knowledge about your products and services will soon become a deadly attitude. Business processes, with their inability to deal with uncertain, irreproducible knowledge, are the least suitable tools to establish and maintain any kind of relationship with your customers.
Wait, we need processes
Yes, we need business processes. Not as we know them today, driving our organizations from end to end, but we need them as an infrastructure, to free knowledge workers from complicated tasks, even collective ones. But they must now be considered as tools at our disposal, not as our organizations’ backbones. Besides that, not any company is destined to become a social business, not any product or service is meant to be discussed about on the social web. The future of business is both brands and commodities, and that will be the subject of my next post.
By Thierry de Baillon
Version française ici.
I am often puzzled by the way organizations and agencies tackle social media, as if conversational marketing and Enterprise 2.0 were living in separate worlds, addressing totally different issues, pursuing irreconcilable goals. Do they?
Of course, when considering the ‘media’ part of Social Media, open Innovation, co-creation, social CRM, have very few to deal with Facebook campaigns or multi-millions views viral videos. But the ‘social’ part, a word which deeply unsettles more than a few from my Enterprise 2.0 colleagues, tells us a completely different story, made up of conversations, insights, and exchange of knowledge. More than ever, I see a whole continuum taking place in the Social Territory, setting the customer’s experience at the center of business and harnessing all those conversations to get things done in a better way and gain decisive competitive advantages. Social Learning, which involves leveraging knowledge gained through informal networked flows, appears to be the necessary link between Social Media and Social Business.
More on that in the presentation below:
By Thierry de Baillon
Version française ici.
As time goes by, I see more and more surveys and positive case studies about Enterprise 2.0 adoption. This is good, but not so much. Most of the time, use of technologies such as instant messaging or web conferencing is viewed as concrete steps toward Enterprise 2.0 adoption. But is there any behavioral difference between meeting up face to face with someone and talking via IP networks? Barely any; this helps saving fossil fuels for our planet’s health and sets up a hypothetical technological ground for some later adoption. Not that much to jump for joy about.
Monitoring Enterprise 2.0 adoption should instead focus on communities, networks, and flows of knowledge, These are the real bricks on which to measure change, with a lot of precautions nevertheless.
Communities of practice exist for some time now in big organizations. They gather people with similar or related roles in a company, and are built around practical cases sharing, knowledge emergence and collaborative problem solving. While this is a great move toward new modes of collaboration and new, tacit, knowledge capture, these communities are often heavily structured and managed, just to insure that they “work”. Regular fixed-date gatherings, mandatory outcome, fixed agenda and assigned roles are among common practices. In other words, keeping control on the internal working of communities of practice allow organizations to fit roles, responsibilities and (collaborative) productivity all together.
But communities are inherently dynamic and have fuzzy boundaries. Networks, which may both encompass or be nested inside them, are often unpredictable, uncontrollable, activate and dissolve on purpose, instill passion and disruption into communities. In networks relies the real power of communities. Without purposely enabling them and fully fostering their capabilities, which means giving up control and deeply changing the way we think about work, online communities are, and ever will, only be technology assisted para-hierarchical structures. Communities are the bodies, while networks are the souls of the collaborative enterprise. Without a real cultural change, ‘change toward Enterprise 2.0 adoption’ merely means creating Zombies 2.0. Is your company into ‘socialwashing’?
