Snippets

Something that works in town X will not necessarily work in town Y

The criticality of initial conditions

The critical importance of initial conditions to the outcomes that emerge is another central tenet of non-linear dynamics and the complexity sciences. In discussing the patterning process of the brain, de Bono similarly points out that simply changing the entry point to a pattern can lead to a totally different outcome. The crucial effect that the sequence and timing of arrival of pieces of ‘information’ has on the outcome is therefore vitally important to the patterning process that takes place and the patterns that emerge.

In the context of organizational conversations and interactions, this similar dynamic occurs. The sequence of gestures and responses pattern the conversation and determine its outcome, whether in terms of organization-wide designs (strategies, structures etc), local actions, or patterns of underlying assumptions. These conversational exchanges therefore shape – and are simultaneously shaped by – the outcomes that emerge.

- Chris Rodgers

…rather than scale up successes (the fruits), we should focus on scaling up the processes that led to such successes (the soil).

Replicate starting conditions

The Lorenz butterfly is significant becasue it illustrates the concept of “sensitive dependence upon initial conditions.”

The fact that something works in one context…does not mean that the outcome can be replicated in another place even if it similar. Each specific context is not fully knowable, and the interaction of agents in each context will be different in each case. We can replicate starting conditions and monitor for emergent patterns, damping and amplifying according to their efficacy but replication of outcome is not possible

(Source: informalcoalitions.typepad.com)

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Polarization from categorisation

A critical dynamic of organization from a complex responsive process perspective is polarization. Stacey argues that the act of naming or categorizing an experience places it into one category rather than another. This identifies and accentuates the similarities that exist with other experiences placed in that same category and, at the same time, emphasizes the differences from experiences that are categorized differently. In this way, experience is polarized into similarity within categories and difference between them. As a result, the paradox of simultaneous similarity and difference within and between categories is lost sight of.

In much the same way, de Bono states that the mind has a marked tendency towards polarization. Even though the choice between two competing patterns may be very fine, he argues that one of them will be chosen and the other one completely ignored. Once such divisions are formed they become self-perpetuating and grow further apart. This results in a tendency to move to one extreme or the other, rather than maintaining a balance between them.

- Chris Rodgers

Related

“…allowed ontology (the nature of things) to determine epistemology (the way we know things)”

“The distinction between a sense-making framework (data precedes framework) and a categorisation model (framework precedes data)”

…without boundaries humans will not distinguish between different types of action and analysis. We are not good with gradients.

…allow the boundaries in the Cynefin framework to emerge from the data

Boundaries are necessary for human sense-making. If we gave people a spectrum from chaotic to stable then people would settle in the place of their most comfort.

If we create boundaries, then if we can create a first step which involves a choice as to which side of the boundary we are (backed up by narrative based definition which is amenable to coherence based evidence). With that done it is a lot easier to get people to accept that in a particular context they should do something they are otherwise uncomfortable with. By socially constructing the boundaries from an open space we enable people to see things in a novel and interesting way, something that imposing a two by two categorisation framework would never achieve.

Gradient models don’t create boundaries and humans need boundaries to think differently. With a gradient people settle where they feel comfortable

…a framework with boundaries allows people to see that they need to behave differently in different contexts.

The danger is the confusion of boxes with boundaries. Boundaries allow us to create differences as we transit or approach them, boxes on the other had are confining, static and limiting

I don’t like 2by2 matrices because they create a categorisation approach in which the model precedes the data so people make things fit. As you can see from the first link the framework emerges from the data so its better for sense-making and is more likely to recognise a changed or changing context.

Every system has a boundary. It may be porous, and indeed a complex system must have “ports” or “dendrites” to interact with the environment. Context is a function of boundaries. Personally I do not like gradients, because soon everything is relative (and nothing has position then) and when that happens anything goes and I do not get closer to solutions either. With ports and dendrites there is no crossing of boundaries, it is what helps the system interact and it can be truncated or extended or narrowed or widened in specific ways to allow for the process of experimentation, which is also core to sense-making.

- Jan Roodt

The danger with boundaries is when people use them to exclude “the other”, to live within boundaries rather than to transcend them. The point of the Cynefin model is to allow people to live on both sides of the boundaries and to behave appropriately depending on context

(Source: informalcoalitions.typepad.com)

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Complex systems include patterns, randomness does not

Among the people I talk to about complex systems, a common point made is that the future is inherently uncertain or “unknowable”…it results from the concept of emergence “breaking” determinism (as well as from quantum uncertainty)…

…it’s important to distinguish between randomness and complex systems because the latter includes patterns whereas the former does not; and…it is patterns that determine our ability to anticipate and / or influence the future…

…let me define “patterns” as systematic relationships between the component parts of some complex system that are expected to persist for a period of time. My colleague Hank Sohota offered an alternative definition: “patterning” is a population wide tendency to think and / or behave in a particular way.

It is informative to distinguish between patterns and laws. The latter involve universality in time and space i.e. they are eternal and they are expected to operate in all circumstances and contexts (consider, for example, natural laws). By contrast, patterns are ultimately ephemeral and context always matters. In fact, we could think of laws as a special type of pattern: eternal and context independent

There is also the important question of identifiability. Many patterns in human systems are tacit or implicit to varying degrees, rendering them difficult or impossible to identify and – even if identification were possible – to quantify. As an aside, many traditional economists try to identify the eternal laws of economic behaviour because they think of a whole economic system as both unchanging and, implicitly, quantifiable.

Let’s look at randomness for a moment. If everything around us in our universe were random…There would be no natural laws…and there would be no forms of self-organisation (such as energy existing as mass and sub-atomic particles combining to make up atoms). But consider a thought experiment: suppose we take a less extreme version of randomness, say one in which we do exist but nothing around us were predictable, what then? Well, to be frank, there wouldn’t be much point in getting up in the morning. We wouldn’t know (for example) if people still spoke English, obeyed laws such as prohibition concerning murder, used the currency in their pocket…

We don’t live in a random world because patterns have emerged. They have created all of the order around us and by and large we expect most of this order – these patterns – to continue.

There is a relationship between patterns and prediction. In fact, I would note that not only do patterns exist and persist, we must rely on them in every day life. We make decisions in the present assuming the persistence of some patterns e.g. I will withdraw £50 from a cash machine today for spending over the next few days…

- Greg Fisher

Related

Whilst agreeing about “the importance of instabilities and the high degree of sensitivity to small changes in the contexts of stimuli”, it is, at the same time, essential that the brain functions in a way that tends to create ‘stable patterns’. Although the “instabilities” provide the capacity for pattern shifting and novelty to emerge, ‘stable patterns’ (or, more accurately, a tendency for patterns to be self-reinforcing and self-replicating) are essential if we are to function in our day-to-day lives.

For example, we can only readily use a cup to drink because of the patterning process that relates cup-like objects to drinking. Otherwise we’d need to learn this afresh each time. The “sensitivity to small changes” would come into play if, say, what we had perceived to be a cup turned out to be something different altogether. Our surprise (an emergent response) would then trigger a different pattern of thought and emergent sense making of a different kind. De Bono makes the crucial point that if the mind did not use patterns we would be unable to use language, since words indicate whole patterns of meaning.

…the brain provides an environment for incoming sensory signals to organize themselves into patterns and to trigger responses, based on what has gone before

(Source: synthesisips.net)

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“ Your pain is the breaking of the shell that encloses your understanding.

—

Kahlil Gibran

An individual’s personal frame of reference can be thought of as the ‘shell that encloses their understanding’. Change often threatens to ‘crack’ this ‘shell’; which is why it is often painful for people – and why individuals respond differently to what is proposed. The ‘deeper’ the perceived ‘cracks’ that change brings, the greater the ‘pain’ that is felt – and the more that people are likely to resist it.

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Sometimes we say “evolve”, when we probably mean “adapt”

Evolution is based on five principles:

Population - There must exist more than one version, or instance, of a system;

Replication - There must be a mechanism of making new versions from existing instances;

Variation - There must be differences between these versions or instances;

Heredity - The differences must be copied along from existing instances to the new versions;

Selection - The environment must impose selective pressure (some instances disappear, others survive).

A single person does not evolve, because there is no population, only a single instance. There are populations of galaxies, but they don’t evolve, because they do not replicate. Computer programs can be replicated, but they still don’t evolve because the new versions are exact copies, with no variation. And businesses don’t evolve, despite variation and some replication, because they don’t directly inherit properties from the earlier businesses from which they were replicated.

For complex systems there is only one common principle: adaptation. Complex adaptive systems adapt to their changing environments. Though not all complex systems are adaptive (for example, star systems are non-adaptive), from a managerial perspective we are only interested in the systems with adaptive capabilities. A single person is adaptive. Computer systems are adaptive. Businesses are adaptive. In fact, most of the time when people talk about things “evolving”, they usually mean that things are adapting. A design doesn’t evolve. It is adapted to new requirements. And my children’s gameplay doesn’t evolve either. They adapt to my new requirements. Or else…

- Jurgen Appelo

(Source: noop.nl)

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Why do we praise generous acts more when they seem more selfless?

Just as humans often use generosity in self-serving ways, they also scrutinize the generous acts of others for underlying selfish motives. When a corporation donates to charity, for instance, we may wonder whether it’s just an effort to generate governmental or public goodwill, in order to avoid regulation or to drum up business. To assess a generous act in this way, however, is not necessarily to disparage the act’s moral value. Even if the act benefits the giver substantially, it may still be highly commendable and beneficial for the recipient; there’s nothing wrong with win-win situations. Still, people reserve a special place in their heart for acts that seem to be true cases of self-sacrificial altruism: the less we can discern self-serving motives for a generous act, the more we extol the act.

Why do we praise generous acts more when they seem more selfless?

It may seem slightly ironic, but we probably do so out of self-interest: as beneficiaries of such acts, we aren’t expected to provide anything in return, so we gain bigger net benefits than we would from acts that obligated us to reciprocate.

Here’s an illustration: in a study I conducted among members of a work team in an indigenous Amazonian society…Respondents overwhelmingly favored a member who worked hard for low benefit—an altruist—over one who worked hard for high benefit. (They also overwhelmingly disfavored one who worked little for high benefit—a free rider—compared to one who worked little for low benefit). In other words, indigenous team members preferred the actor who would produce higher net benefits for them, were they on the same team; as in our own culture, selfless generosity was praised more than selfish generosity.

But as praiseworthy as many acts of self-sacrificial generosity may be, we should remember that praising others for these acts is itself probably selfish.

- Michael Price

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Our species tends to loathe complexity, and prefers to oversimplify everything…

What led to the decrease, Gopnik found, was the combined effect of millions of small sustained actions by millions of determined people just trying to make their corner of the world a little better:

“Epidemics seldom end with miracle cures. Most of the time in the history of medicine, the best way to end disease was to build a better sewer and get people to wash their hands. “Merely chipping away at the problem around the edges” is usually the very best thing to do with a problem; keep chipping away patiently and, eventually, you get to its heart. To read the literature on crime before it dropped is to see the same kind of dystopian despair we find in the new literature of punishment: we’d have to end poverty, or eradicate the ghettos, or declare war on the broken family, or the like, in order to end the crime wave. The truth is, a series of small actions and events ended up eliminating a problem that seemed to hang over everything. There was no miracle cure, just the intercession of a thousand smaller sanities. Ending sentencing for drug misdemeanors, decriminalizing marijuana, leaving judges free to use common sense (and, where possible, getting judges who are judges rather than politicians)—many small acts are possible that will help end the epidemic of imprisonment as they helped end the plague of crime.”

Gopnik is saying, in effect, that complex ‘problems’ like crime, poverty, climate change, peak oil, corruption, pandemics, and unsustainable growth economies, are not ‘problems’ that can be ‘solved’ at all, but rather, as philosopher Abraham Kaplan explained, predicaments that must be “chipped away at” and adapted to. Our species tends to loathe complexity, and prefers to oversimplify everything, and the politicians, lawyers, corporations and media play on that loathing by always proposing analytic (“A or B”) dichotomies and simplistic “answers” — which cannot possibly work. “Three-strikes” laws, “trickle-down” economics, emissions trading schemes, subsidies, religious taboos and inquisitions, austerity programs, prohibitions, bailouts, military invasions and “quantitative easing” — these are all massively expensive complicated “solutions” to complex “problems”, and they have all failed spectacularly.

- Dave Pollard

(Source: howtosavetheworld.ca)

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Learning itself is a form of invention

Recently I had reason to revisit some of the work of W. Brian Arthur, one of my favourite economists; while doing that, I couldn’t help but re-read his excellent The Nature of Technology. In that book, he makes the point that invention happens for two reasons: someone identifies a need to be filled, as in building jet engines rather than propellor-driven ones; or someone observes an effect that can be used for something else, as in the discovery of penicillin.

While reading the book, I began to realise that learning itself is a form of invention: as I learn something, I create something inside me. I began to realise that the learning that takes place follows the same path as Brian Arthur’s classification of inventions: sometimes I learn by identifying a need and then trying to meet that need, and sometimes I learn by observing an effect and figuring out how to put that effect to good use.

- JP

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Self-organization is not the same thing as self-management

Organisation dynamics…“self-organization” is not something that is within the gift of managers to decide upon. It is at play just as surely in an organization ruled by the proverbial ‘iron fist’ as in one that has all the attributes of empowered self-management. However, the critical thing to emphasize here is that it is the conversational interactions that are self-organizing. And it is through the self-organizing interplay of these ‘local’ conversations across the organization and beyond that ‘global’ outcomes emerge.

Organization design, I see its primary purpose as one of shaping and aligning the various elements of the organization so that it is best placed to achieve its purpose…As part of the design process to achieve this, decisions will be made on structural aspects of organization, as well as on related processes, systems and procedures. And, whether by accident or design, these will both enable and constrain the ways in which people are supposed to work together formally. So the outcome might be one which facilitates greater self-management; or else inhibits (or even prohibits) it, in favour of greater centralized control.

Organization development…is heavily steeped in humanistic, people-based values and recognizes the impact of social, psychological and emotional aspects of organization on performance outcomes…it embraces a philosophy of management rooted in a positive view of the value of greater employee involvement and self-management…people’s willingness and ability to contribute and adopt leadership practices designed to foster mutual trust and enable greater self-regulation.
[In the] talent-based approach to role development…individuals would have greater discretion to organize their own roles and relationships to suit their particular talents and interests. However, implicit in this is the widely-held view that self-organization happens (or doesn’t) as a result of deliberate choice – either by management design or as the result of a ‘grass roots’ initiative
…at its centre is placed an individual’s core strengths or distinctive competence, on which their contribution to the organization – and personal growth - will be built. The framework then branches out in four complementary directions. These describe, in turn, the attributes of self-sufficiency, self-direction, self-control, and collaboration.

Leaders are not in control of outcomes

Many people, including me, when they first learn of this idea of self-organisation, immediately think of questions like “How can we empower employees to be self-organising?” or “How can we manage our people so that the emergence can take place?

I came to realise that it doesn’t make much sense to talk in this way because humans already always are self organising, even when they work in organisations with top down management approaches. If they are working in an organisation with restrictive management approaches, then they are still self-organising, with a given mix of constraints, power relations and so on that is determined in part by the management approach. This is because top down or highly directive management approaches give a certain combination of constraints and power relations.

A more useful question might be something like “How can we change the constraints and power relating so that different patterns will emerge from the self-organisation?”

The challenge is “How can I influence the constraints and power relationships so that different (hopefully more desirable) patterns of social interaction emerge.

Employee performance rides on commitment; which rides on motive, means, and opportunity

On self-organization and emergence: #1 - Processes not systems

Self-organization and emergence: #2 – Organizational dynamics v organization design and development

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Employee performance rides on commitment; which rides on motive, means, and opportunity

The proposition is that people need three things if they are to commit to excellent performance. These are: the Motive to excel; the Means to excel; and the Opportunity to excel.

If any one of these three conditions is missing, there cannot be commitment. At least not in the sense described here. There may be good intentions, without the means or opportunity to deliver against them; there may be the ability to deliver, without the opportunity or desire to do so; and there may be a ‘golden opportunity’ to make a real difference, which remains unfulfilled through lack of motivation or capability. In none of these cases, though, can there be a commitment to excellence.

The aim, then, is to stimulate people’s intrinsic motivation to contribute to the best of their ability…At the same time, leaders can strive to stimulate conditions in which these motives can be more effectively mobilized and applied for business benefit…the motivated application of these in a particular instance can only occur if the opportunity to do so is available. This requires leaders to work to break down the organizational, technological, perceptual and other barriers that inhibit performance

Individuals are likely to perform better where the content of their role aligns with their personal strengths and interests. To maximise contribution and commitment, the scale and scope of these roles should ideally expand over time, whilst ensuring that people’s developing capabilities keep pace with the degree of challenge that they face. Where mismatches occur, these are likely to create anxiety (high challenge – low capability), boredom (low challenge – high capability), or apathy (low challenge – low capability); all of which are dysfunctional for individuals and organizations alike.

The context within which people work.

The degree of choice that people have within their work…there should be adequate and increasing scope for self-management and genuine participation; and for the creative self-expression of individuals’ talents and motivations.

The following two factors are also important:

The congruence that exists between the organization’s stated purpose and values, and people’s everyday experience of organizational life…Commitment is likely to be undermined if people’s views of what’s going on differ from the official line. People will deduce the organization’s de facto purpose and values from their own and others’ perceptions, interpretations and evaluations of everyday events

Managing the creative tension between continuity and change…Commitment is both threatened and potentially enriched by organizational change

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Leaders are not in control of outcomes

…despite what might be suggested by the formal trappings of organization, decisions arising wholly from rational analysis of ‘the facts’ and step-by-step decision-making are rare – if they exist at all. In practice, people tend to make progress through informal interactions, ad hoc sense-making conversations, ongoing political accommodations, and plain, common-or-garden ‘muddling through’.

Most significantly, perhaps, whilst leaders might be formally ‘in charge’, they are not – indeed cannot be – in control of the outcomes that emerge from the complex interplay of the myriad local interactions that constitute everyday organizational life.

This is not a matter of incompetence. Far from it. But it might be portrayed as such, were it not to be covered over by the superficial gloss of management speak and formal process rituals that maintain the illusion of rationality, predictability and control. Or if there was no post-hoc rationalization of actual outcomes that savvy political behaviour demands.

Despite being formally in charge of the organization (or a part of it), they are not ‘sitting in the stands’, dispassionately observing and controlling other peoples’ actions. They are ‘on the pitch, playing’. Power relationships might ordinarily be weighted in their favour – and often significantly so. But what they think, say and do, and how this plays out in terms of outcomes, is ultimately determined by everyone else’s thoughts, words and actions that comprise the complex social process of everyday interaction.

One of the major challenges to established management thinking that is posed by Stacey’s radical perspective on complexity, is the recognition that there is no outside agent (the manager) objectively observing what is going on and controlling the activities of others from an external vantage point.

Some advocates of a complexity approach see it as providing a new set of prescriptions for managers to use to control their organizations. Principal amongst these are those who see organizations as “living systems” and adopt a Complex Adaptive System view of organizational dynamics (calling on managers, say, to apply a set of simple rules to facilitate self-management).

Stacey’s complex responsive process view argues that these prescriptive approaches perpetuate the myth that managers can somehow stand outside the action and control it from a detached viewpoint. In human organizations, there is nobody outside the process of interaction. Managers are unavoidably involved in the give-and-take of local conversational exchanges through which outcomes emerge – even in their absence! At the same time, they cannot control these outcomes. Although managers can act with intent in terms of their own contribution to the dynamic network of interactions, they cannot be certain what outcomes will actually emerge.

…de Bono’s early writings on the brain provide some ‘lateral reinforcement’ for Stacey’s position. In describing “the mechanism of mind”, he argues that there is not a separate agent at work, picking ‘information’ out of the environment, storing it on the brain’s ‘memory-surface’ and then picking it off the surface to manipulate it. Instead, stimuli (such as those arising in conversation with others) organise themselves into patterns without the involvement of any other agency. What emerges from this process depends on the ‘in-the-moment’ coming together of these particular stimuli and the patterning that has gone before. The latter will tend to channel perceptions and interpretations down well-trodden ‘pathways of the mind’ whilst retaining the capacity for novelty to emerge.

On self-organization and emergence: #1 - Processes not systems

Self-organization and emergence: #2 – Organizational dynamics v organization design and development

Organisations are not Complex Adaptive Systems

Organisational Culture - focus on what’s behind the behaviours, not the abstraction

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You can’t achieve change based on ideal behaviour, but you can change process and context

…you have to embed change in process, not depend on individual competence. You can’t achieve change based on ideal behaviour, but you can change process and context

Rather than trying to solve the problems of the world (or the organisation or whatever) by sitting around with a group of like minded people and creating pipe dreams about how things should be…you instead focus on what you can change in the here and now….

…if you want to change organisations, three basic principles:

You don’t lecture management on how they are old fashioned in their thinking, instead you put them into situations and give them tools where old ways of thinking are not sustainable and they have to act differently. If they work it out for themselves its sustainable.

You pick off areas where the pain threshold is the highest, for example (to pick up Agile themes) the interaction between approaches such as AGILE and the measurement and management practices of the HR function. You then create approaches that change the measurement and feedback mechanisms that work in parallel with existing methods. That new project management system (something I am working on to declare a commercial interest) can start to provide HR with better data on people and “competences” than their current systems so they choose to adopt it over time.

Sell middle-bottom-up an idea originally put forward by Nonaka and one I respect. It’s not too difficult to get senior management to buy into an idea, but it will only happen if middle management are bought in and they are the hardest.

- Dave Snowden

(Source: cognitive-edge.com)

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Using the Cynefin framework (more)

The challenges of complex systems are predicaments, not problems

Natural systems are highly effective but inefficient due to their massive redundancy (picture a tree dropping thousands of seeds). By contrast, manufactured systems must be efficient (to be competitive) and usually have almost no redundancy, so they are extremely vulnerable to breakage. For example, many of our modern industrial systems will collapse without a constant and unlimited supply of inexpensive oil.

As natural systems evolve to become more complex, their resilience increases. For example, more biodiversity means less vulnerability to pandemics. However, as manufactured systems become more complicated (e.g. through centralization and globalization) their resilience is reduced. A breakdown in a single component can cause the entire complicated system to seize up or collapse.

Most of the so-called intractable problems we are now facing (e.g. war, violence, poverty, epidemic disease, and the growing economic, energy and ecological crises) are not ‘problems’ at all, but complex predicaments. The challenges of complex systems are predicaments, not problems, because, since they are not mechanical, they cannot be ‘fixed’ or ‘solved’. Alternative, non-mechanistic approaches must be used to deal with them, which is what this article is mainly about.

Simple problems or situations (like hammering in a nail), with few variables (i.e. few things to consider) and which have obvious solutions (strike the nail with the ball of the hammer until it goes in), are best approached intuitively.

Complicated problems or situations (like fixing a car), with many variables, all of them knowable (at least with some study), and where the solutions aren’t obvious but cause-and-effect relationships can be determined, are best approached analytically.

Unfortunately, we are all too easily tempted to try to reduce complex predicaments (e.g. how to deal with the nightmarish global debt crisis), to simple or merely complicated problems (e.g. how to get banks to give consumers more credit in the short term so they can spend us out of recession, for now), because we’re good at solving merely complicated problems.

Complex predicaments (like running a social event or a business, or coping with economic, energy or ecological collapse) have these four characteristics:

The number of variables that can have an effect on the system/situation/event is infinite

Most of these variables are unknown or unknowable; only the most obvious ones can be listed or diagrammed

The relationships between cause and effect in the system are unfathomable; at best you can notice correlations that may or may not be meaningful

It is impossible to predict the outcome of an intervention in the system/situation/event (or when Black Swan events and other unforeseeable interventions will occur)

As we come to understand complex predicaments better, we’re learning that the best approaches to them are very different from what works best for simple or complicated problems. Because all the variables cannot be known, and because cause-and-effect relationships cannot be established in complex situations, analytical approaches (like systems flowcharts) used in complicated problem-solving simply won’t work.

Coping with complex predicaments requires a focus on continuously improving processes, not achieving outcomes. A key feature of complex predicaments is that an appreciation of the true nature of the predicament and an understanding of possible workable approaches to deal with it co-evolve. You can’t know the desired outcome up front, because you just don’t know enough about the situation. Your approach needs to facilitate this co-evolution of understanding, and enable you to go beyond selecting from currently known alternatives and simplistic dichotomies.

When complex predicaments are left unaddressed for long periods of time, they can sometimes worsen into chaotic predicaments (like the horrific challenge of homelessness in Haiti). Chaotic predicaments have the same characteristics as complex predicaments, with the additional attribute of massive turbulence, to the point that change and crisis are occurring so rapidly or continuously that any type of coordinated, rational response becomes impossible.

- Dave Pollard

Cynefin framework

Complicated management…NOT!

Introducing a degree of inefficiency so that the system as a whole has the potential to evolve

Systems that eliminate failure, eliminate innovation

From strategic planning to purpose and resilience

Inefficiencies are necessary for resilience

Efficiency destroys resilience

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Enterprise 2.0 practitioners realise this…

Patterns of enterprise 2.0 adoption, and measurement

JH: Companies are most successful when they realize that tech by itself will not achieve anything. Instead, companies have to change the way that they work.

1st pattern

JH: It is the same pattern that you have seen in the tech industry for a long time. Each wave of new technology comes into the enterprise under the radar. People start using it without permission. The broadest adoption of E2.0 within the enterprise is by teams with a 6 to 12 month timeline without permission of IT dept. They think “why not try this out” even though it is not officially sanctioned. It ends up being helpful to the team but it does not spread. When that team disbands you lose a lot of what they learned.

2nd pattern

Second form of adoptions is when an executive finds out about the new technology, and decides to deploy it. This is often good, but adoption process is a bit ad-hoc.

3rd pattern

A third pattern is becoming more prevalent: a check-the-box approach for cool things. Once it appears that all cool enterprises have to have a micro-blogging capability in the company, they get and deploy one. However these users are not always clear about why they are deploying it and what it is really useful for.

Strengthening the allies, and neutralizing the enemies

It is important to understand that it is about strengthening the allies, and neutralizing the enemies. The best way move forward is to show tangible improvement as quickly as possible.

We came up with the notion of “metrics that matter”.

Different metrics matter at different levels of the organization. Senior managers care and are motivated by financial measures. Mid-level managers are most focused on operating metrics. Customer churn rate, etc. Further down to the front line, there are performance metrics they are measured on a daily basis. To get the most impact, start with the overall financial pain points. If you focus on that, it may turn out the customer churn rate is identified as a problem that contributes to this.

Operating costs, not ROI

People talk about measuring the ROI. But the reality is that who ever controls the underlying assumptions can deliver whatever ROI they want. I have yet to see any enterprise that has gone back to look at the ROI to see if it materializes. It is better to focus on operating metrics. If your issue is lead time to get a bus on the road … you can track that on a daily basis. Then refine the approach. In many case studies on companies, very few had gone back and measured whether they actually achieved the projected success.

Focus on specific parts of the org, specific people. There is a general pattern where social software can make the most difference: exception handling. I call this the shadow economy of the enterprise. Ask an executive “where do people spend their time?” 60-70% of time is spent on exceptions, and this generally not very visible. These are cases that have been thrown out of the automated system — and you have to resolve them quickly. Must find the right people engaged, the right data, resolve the issue quickly. In general, this work is all manual, and very inefficient. What is social good for? Finding the right people, finding the right information, and getting them to work together.

How to measure impact of enterprise 2.0

ROI on social computing is silly

(Source: social-biz.org)

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