"When the only KM tool you have is a hammer..."

The biggest problem I have seem with KM isn't any particular approach, or system, but rather the idea that one approach is seen as a panacea across the breadth of corporate experience that we call knowledge.

Dr. Randhir Pushpa recently wrote a blog post about the role KM plays in the journey from art to science. It's a good article and includes a few useful tips and links. However it seems to suggest to me that the desired outcome is always to guide and develop every business process toward the science end of his scale.

This Journey turns up frequently in management discussions.

• Roger Martin, in his book "The Design of Business" calls it "The knowledge funnel",
• Dave Snowden uses his Cynefin model to describe the dynamics of these domains, and how leadership should make decisions based on them.
• Paul Hobcraft uses this to describe the cycle of innovation, the key takeaway being that each domain benefits most from a specific type of practice.

But there are times when the journey from complex/emergent practice (so called "Art") to highly ordered/systematized process ("Science") should find equilibrium based on local context.

What do I mean by that? Well, some processes (i.e. making french fries) should be hard system. ie: all the benefits of efficiency and standardization. In this case quality is seen as uniformity. However others (i.e. aspects of management consulting) may need to stay highly flexible at the more creative/emergent end of the spectrum because a customized and highly contextual solution is seen as high quality.  Others will settle in the middle, complicated area where the maintenance of a body of expertise is desired. Efficiency and effectiveness is blended and short-term economic value is always balanced by the medium term requirement to be adaptable to changing market forces.

If you are interested, the Creative Melbourne event on next month explores this journey in a radically hands-on way by bringing people from various industries together to co-create solutions to large community problems.

The new ISO 30401 standard makes this point by insisting we examine our organisational and stakeholder contexts first, before jumping to solutions, systems and process change. What is important to note is that all parts of the journey can be shared and stored as corporate memory, we just use different techniques. People who think we should "Write all knowledge down" may get a shock when they view the access rates of their online knowledge-bases. The question is "How do we connect people with knowledge" and then the concepts of collecting and capturing become useful tools rather than the soul objective of KM.  This has a secondary benefit of creating a demand for knowledge, meaning the knowledge holders aren't just recording what they know in the lame hope it might be used someday, but are actually helping people and the knowledge gets recorded in the process. (FYI Knowledge Centered Support does this really well).

Essentially, by insisting we take a double loop learning approach to KM, we should also be open to other parts of the organisation needing to be that way too, to achieve their best outcomes.

Interview with Arthur Shelley about the new ISO KM Standard

Well, after several years of hard work by an international committee the new ISO-30401:2018 Knowledge Management Systems standard is upon us (you can preview and purchase it here). For us Down Under this replaces the old Australian KM standard AS-5037:2005 but also builds on some of the lessons we gained from it.

As with most new things, change can be hard. That is also true of standards and just like the arrival of ISO-9001 before it, the new KM Standard has some doubters and naysayers; some saying it’s too late, others questioning the non-collaborative ISO authoring process and of course the ones standing on either side of the road yelling it goes too far, or doesn’t go far enough, etc, etc.

RealKM’s article last week gives some of the details but I wanted to find out from one of the authors just what the standard is all about so I interviewed Dr Arthur Shelley to get his take as the Australian ISO representative on the committee. You can see the interview below.

One of the things that has always struck me about KM is the difference between the simplicity of most of the concepts when compared with how long it takes the average manager to understand them. Maybe it’s because we all think. So thinking about thinking is unnatural as a fish pouring themselves a cup of water. Whatever it is, there is an obvious gap between those who practice KM and those never exposed to it.  

When I asked Arthur about the benefits of ISO-30401, he pointed out the power of a single international standard to address this inequality by providing a measurable foundation for knowledge work in organisations, even when you don’t have internal advocates. For those of you that have ever tried to excite policy change in a government department, this is great news and an important contributor to winning over the committees and lawyers that stand in your way. For those that know what factors are needed for success but have trouble convincing management that all them need to be in place, this standard helps you get support for the less obvious ones, helping you avoid the “You don’t need some show of support from us young lady, just install the software and I’m sure they will all use it.”

I hope you enjoy this short chat with Arthur. It was recorded in the middle of a thunder storm with massive hail falling right outside, so apologies for the audio quality. 

If you would like to have a chat yourself with Arthur then you will have a golden opportunity next week at the AusKM Conference in Melbourne, Australia.  Click here for tickets and the chance to discuss your projects and goals with some of the top KM people in the world as we are hosting the Global Network for the first time. An opportunity not to be missed.

The Difference and Danger of Information versus Knowledge Management - a cautionary tale

Let me tell you a quick story. Recently at my uncle's funeral I had a fascinating conversation with an old farmer who's son was following in his footsteps on a property up near the Murray River.

He was talking about all the technology now used in farming, like scientific assessment of water tables and salinity, satellite and drone based land surveys, computer controlled water allocation and measurement leading to fantastic efficiency, as well as crop and nitrate selection algorithms to ensure maximum harvest and cattle health.  These are all the benefits of the technology world we find ourselves in, and around the corner, AI is going to take another step forward in terms of predicting larger agricultural and business problems before they occur so farmers can reduce the chance of loss due to bad weather, lack of water or over investment in certain income streams.

But after waxing lyrical about all the new innovations in farming, he laughed how his son had just lost nearly $200,000 worth of hay sheds in 5 fires over a two week period.  It turns out that the young farmer had not dried the hay sufficiently before bailing it and the residual moisture, when stacked in large sheds had caused spontaneous combustion and the lost of considerable stock and assets. But how did this happen?  Surely this knowledge is 101 for somebody working on the land?

Knowledge Lost

Not many people outside KM are aware that for nearly 1400 years, the recipe for making cement (Roman cement) was lost.  In fact we still haven't found it.  The reinvention of Portland cement has led to our modern construction industry, but Roman cement lasts 2,000 years (so far) yet our "Portland" cement is lucky to last 200.  So what happened?  How can this be? How can such foundational knowledge be lost to the entire human race?  Well, whatever the reason, if we can forget how to make cement, then we can definitely forget less important skills and techniques and that is what happened to this farmers son, but before we start pointing fingers, lets consider the technological change over the past 30 years and especially one important aspect of those changes that effects all of us in whatever industry we are working in.

I am sure when I say "Hay bales" to you, unless you are a farmer, you will probably have a picture in your mind of the small rectangle bales that you can still buy at the pet store to feed your rabbit.  About 3 feet long, you can easily carry one on your knee by holding the two pieces of baling twine that hold it together. These were the bales that I grew up with as a child on a dairy farm and making them involved cutting the long summer grass, turning it with a tractorised rake several times over 3-4 days so it properly dried before baling and storage in hay sheds. I have done this many times. I remember the large gatherings of people and trucks to cart in the hay from the paddocks followed by lots of shared food afterwards.  I learned every part of this process, sitting for hours on the tractor either mowing or raking, but there was one bit that was always a mystery to me. "When was the hay dry enough to bale."  This was determined by the weather and the amount of moisture in the grass before it was cut and I know WHAT I had to do, I even knew HOW to rake the hay, but knowing WHEN?  My father would pick it up, bend it, feel it, listen to it and once I even saw him bite some before he would pronounce "OK, it's ready. We bale it tomorrow".  This drying was critical due to the chance of fire mentioned above, and I have seen two sheds burn down over the years including one of my uncles who, from memory, had hurried a baling to avoid the coming rains.

Last week I had the chance to ask my dad how he first learned to do this given all the variables involved and the high cost of getting it wrong. He said he had been taught it by an old farmer and a lot of it was based on the feel and sound as the hay is twisted. I asked him to describe what "ready" hay was like and he said "well it kinda just feels dry, you know?" This is a common reply from masters.  They can no more describe the tacit knowledge involved in this complex task than you can describe how you actually manage to maintain balance while riding a bike. You just have to do it to know how and more importantly you have to know the importance of doing it so you take the time to get it right.

So what happened to our young farmer? Did his dad not pass on this knowledge? Well the answer is no, but the reason he didn't is what holds the great lesson in this for all of us.  You see about 25 years ago a new invention came out.  The Round Bale.  I am sure you have seen them standing about 6-7 feet in diameter in the middle of fields.  Sometimes they are covered in blue plastic or placed in long rows along a fence.  They are far easier and more efficient to transport and distribute to cattle. They don't need sheds and can be left in the paddocks, and importantly for this tale, they don't need to wait for several days of drying because they usually don't get stacked where the overheating problem arises. Apparently the knowledge of drying hay was now obsolete and didn't need to be passed on.  I am sure your organisation has many areas like this where a procedures (or the reasoning behind them) are not passed on or kept current because the processes have changed? In fact some information managers, lawyers and even knowledge managers will tell you that the forgetting is both efficient and crucial for protecting the company legally, saving computer storage space and allowing unlearning to occur in the evolutionary process. All this is true, but is there a down side, and what is the cost of this lost "Why" knowledge?

OK, so fast forward 20 years and a brand new technology comes out. Rectangle bales! Only these ones are the size of a VW Beetle.  They have all the advantages of a round bale PLUS the stacking ability of the old rectangle bales. What could possibly go wrong? Well if you are following the story, you have probably already guessed.  For all the information, and databases, and software, and research, and instruction manuals available to him, our young farmer had lost the ability to know exactly when his hay was dry enough to bale, and the resulting financial loss of both a season's hay, and the huge sheds that hold it were considerable; not to mention the impact on stock this coming winter when either silage will be short or hay will have to be purchased and trucked in. Not cheap.

Would you give your teenage son the keys to your Ferrari?

There is no doubt the growing power of digital technologies to both automate, provide insights and consider correlations of large datasets from multiple sources is leading to levels of business efficiency never heard of before.  In my own work, a recent project in one division saw a 208% increase in throughput, while reducing workload by 70% and reducing time-to proficiency for new staff from nearly 10 weeks down to just 8 days.  In my fathers time, these sort of gains would have been unheard of, especially in just a 3 month period.

However...

Implementing advanced digitisation and automation strategies in your company without co-developing the knowledge and expertise to manage them, is akin to handing your teenage son the keys to your beloved Ferrari.  Not only will all that amazing technology fail to make him safer on the road, the levels of power involved will dramatically increase the risk of catastrophic failure and considerable financial loss.

Don't make the same mistake as this young farmer.  If you have implemented IT projects that don't deliver on results, new software that fixes one problem and causes three new ones, or high staff turnover in the complicated operational areas of your business, then may I suggest that throwing more money and technology at the problem is not going to fix it.  Whether you are running a single automation project, or digitising your entire business, please, just talk to a Knowledge Management professional today and get your foundations laid right. You won't regret it.

* Image Michael Trolove used under CC. Picture of farmer under CC.

The pros and cons of considering frameworks and models

For a while now I have watched students and business associates try to pluck models (sometimes from thin air) and apply them to whatever problem they were trying to solve.

Recently a friend of mine tried to combine two quite different models to see if he could find some insight in to his next steps. This post is a few of my thoughts about the practice of thinking about and applying models and frameworks, as well as some feedback from Brad on these two specific models.

Lets start with a warning:

In their recent book "The Heretics Guide to Management", Paul Culmsee and Kailash Awati warn us that just as children cling to Teddy Bears to sooth their fears of the unknown, so can we all cling to various business models, strategic plans and operational budgets like they will solve all our fears if we are just faithful to them. Sometimes they are useful and give insight, but once the underlying assumptions no longer hold true, clinging to them becomes a fetish - one we often want to defend at all costs. I want to mention this up front because the danger of dabbling in new models, assumptions and ideas about how your world works is that you actually think you find a silver bullet thereby closing down your future creative possibilities while simultaneously giving yourself false confidence in a complex situation just because your new map tells you which direction to go.

Using models to kick-start our creativity

It is actually this set of possible steps that neuroscientist Beau Lotto points out as being the way we can increase our creativity and not just solving novel problems but increasing our ability to understand them in the first place. In this recent video on BigThink, he discusses how our brains evolved to avoid one thing: uncertainty, and so it is only capable of making small logical steps in order to avoid highly stressful cognitive dissonance. So when we see people finding creative, almost genius solutions to problems, we assume they are just really smart, but actually it is the range of "adjacent possibles" being much larger due to the broader, more complex and nuanced assumptions that they hold. Have a quick watch. I'll wait here 'til you get back.

The message is simple

Stop looking for silver bullets and start challenging your assumptions (all of them) while exposing yourself to as many different ways of viewing and thinking about the world as possible. Give your mind the raw materials for the creativity to happen.

Sometimes it is the process of questioning and comparing that leads to the answer, not the model itself. In the medical field it is called "praxis" as real-world data is compared with theoretical models, leading to action, more learning and hopefully the refinement of models or even a new addition to the scientific literature.

(As a side note, I should add an extra component from Matthew Walkers research in to how the brain consolidates these ideas during REM sleep. In his book "Why We Sleep", he presents some incredible evidence for the importance of a full 8-hours to integrate your hard won insights not just into tacit memory, but also to draw the long-bow connections that deep insights arrive from in the days that follow. Whether you are interested in knowledge, innovation & creativity, or just think you don't need that much sleep, I cannot recommend this book highly enough).

Following Brad's adventures

We don't need to be totally academic about it, but switching between theory and practice can lead to key insights as Gary Klein reveals in his new book "Seeing what others don't".

A good friend of mine, Brad Adriannse, recently posted his thoughts doing exactly this by wondering about the intersection of two models as part of his "self-unlimited" journey. Brad's scribbles are shown on the left and his post and initial thoughts are here.

This is interesting for several reasons. Firstly, his approach is less about bending the facts to suit a model and more about using the models as a set of lenses he can look at his situation through to see if anything becomes clearer (expanding his set of adjacent possibles). Secondly, he combined two, quite different models with a clear expectation that a combinatory insight may evolve. Finally, he didn't go build some new thing by himself. Instead, he started a conversation about similarities, differences and how the various intersections may be of benefit. Nice approach.

So lets talk about these two models - Is Brad on to something?

The two models he is considering are the Cynefin framework and John Boyd's OODA Loop.

It turns out Dave Snowden (the inventor of Cynefin) discussed this in his blog in 2012 and I liked his thoughts on the two because of the way he saw a different sort of OODA Loop being required depending on which Cynefin quadrant you are in. This is classic Cynefin - that is, find out what sort of problem you have before deciding what approach you take to solve it. My only problem with his argument, was that it only seemed to show one side of the interaction between the two. Let me explain.

Cynefin is a framework. It describes the different ontological spaces that a problem can be categorised as, therefore what is their nature and how are they best approached.

OODA is a procedural method invented by John Boyd to assess Dogfights in the Vietnam war. Standing for Observe, Orientate, Decide & Act, it overcomes both inaction and misreading of facts in highly fluid situations and has been applied in many different contexts, not the least of which being business and more specifically, management.

I should note that Brad disagrees with me here, saying that OODA is a Tao, rather than a procedure, but my point remain: One (Cynefin) categorises phase-space. The other (OODA) categorises a series of events over time.

Given this, I think there should be two (or more) interactions.

Firstly, with OODA as the time-based boss, I see Cynefin fitting in as a sixth sub-category in the "Orientate" phase. This not only helps understand more about the observation, but has two extra advantages. 1) It lends itself to not only informing the decision, but more importantly, in how the decision should be approached. And 2) it allows for reassessment of the Cynefin quadrant during each cycle instead of assuming that the problem is fixed in one space only (something that I thing Dave missed in his original post but Joseph Bradley tells me was worked out shortly thereafter).

This is especially important if you are trying to apply this to Roger Martin's "Knowledge Funnel" method where you are actively trying to move from problem to solution through the Complex (R & D), Complicated (Design & Delivery) and Simply (Operations) spaces.

The second linkage would therefore be the link from OODA to inform Cynefin. This would allow people already using OODA to refine it by placing an iterative operational model around the problem space in terms of Cynefin. However, I think more importantly, it would provide a clear, (and hopefully corporately endorsed) approach to dealing with the central Disorder space. Dave only touches on this in terms of a non-deliberate entry into Chaos (via the middle yellow arrow through Disorder), but by triggering a Cynefin review whenever a project or market moves into an unknown space I see real promise for challenging and valuable conversations to be spawned as a part of normal corporate process (an hopefully well before the consequent problems from inappropriate approaches arise to threaten the budget, or the entire project itself).

Summing up

So it seems Brad might be on to something and could help us The bottom line is Brad is applying these models in an attempt to separate what is complex and what is complicated and therefore how you should approach each. Well done! You should give it a try too.

I hope many more see how helpful this approach can be - even for truly wicked problems - without falling in to the Teddy Bear trap of course. To be creative, we have to unlearn millions of years of evolution. Creativity asks us to do that which is hardest: to question our assumptions, to doubt what we believe to be true. But Beau Lotto is right when he says it is actually the only way for us to reinvent ourselves for our changing reality.

"Can general critical thinking skills be useful?" Why is this even a question???

Today, the wonderful Lynne Kelly posted an article by Carl Hendrick about why we should not be teaching critical thinking skills in schools. In this article Carl puts forward the idea that specialist knowledge, that is your expertise in one domain, is not transferable to another. 

In fact he claims that people who excel in one domain may not do any better in the new domain than an average newcomer. Measured by standardised tests I presume?  Well I partially agree with his findings and yet disagree with his conclusion; but let me come back to that.   In sharing my thoughts with Lynne about the article I quickly realised it was a prime example of somebody working from an inadequate definition of knowledge and so I turned my response in to this blog post so this example could be shared more widely.

Choosing the right knowledge lens

The problem here is that Carl is using a faulty definition of knowledge. As a knowledge manager I run into this thinking all the time. Based on the computer metaphor, (a prevalent view of the brain in today's schools and universities) knowledge is simply "information" which is transferred and held in the mind like memory on a hard drive. Therefore, it tells us, we should see deep expertise, like that held by air-traffic controller, as a series of remembered skills, techniques and methods. It is a simple concept, easy to explain and rings true to our industrial-age "teacher-student" experiences of learning. Thus its popularity. 

From this model it is a small step to think that knowledge of this sort could be easily transferred to different contexts and even different people. In fact one might be tempted to think more general types of knowledge or skill could be re-applied in many different contexts. Not only that but educators, seeking to have the greatest impact in the shortest amount of time and effort, would naturally seek out these general concepts; just as they do in more specific areas such as maths, science and language.

We don't hold tacit knowledge,
we are made up of it.

There is just one small problem with this "Knowledge is an object that is held and transferred" view; neuroscience doesn't back it up. Any first year brain science student can tell you that memories aren't stored in a specific part of the brain. There is no RAM or hard drive. The brain does have the ability to remember facts and figures, but it does so in a funny almost fuzzy way. Just ask any judge or lawyer about the legal mechanisms in place to overcome witnesses inability to clearly recall facts. 

Knowledge managers call this type of memory implicit knowledge. We define it as knowledge that can easily be written down or made explicit, but knowledge goes further than that. Much of our expertise is held as what we call tacit knowledge; so called because of its most familiar form: muscle memory. Even those who are brilliant at remembering and recalling implicit knowledge actually master tacit techniques such as memory pegs, sensory and geographical tags, humour, surprise, emotion and narrative to do the heavy mental lifting. 

This tacit knowledge is not information based as we know it, but is instead the emergent aggregate of the billions of neuronal firings learned through untold numbers of interactions with the world around us. We don't hold tacit knowledge, we are made up of it. It is who we are and learning something new we are becoming someone new. This is the messy and complex truth of what knowledge actually is, and while it is harder to apply in a classroom or training context it also doesn't break down like the simple computer metaphor of the brain does when pressed with evidence.

So what is wrong with the common definitions of knowledge?

Attainment of knowledge now becomes exposed as an individual's ability to process information against previous experience in order to make effective decisions and take actions that build value for the individual or their group. 

The common definitions of knowledge* being "an asset you capture, store, transfer and apply and build value" lead people to terrible conclusions, like:

• "Just get her to write down what she does",
• "We need manage our knowledge, what software should we use to do it?", or
• "It doesn't matter if our development team quits, we can just hire new programmers with the same skills", or worse 
• "So today is your last day and you've really helped us over the last 5 years. I have 45 minutes before my next meeting, so can you tell me everything you do and I'll make sure somebody keeps an eye on it." (Yes, I really did hear that said to a deep marketing expert who had helped build and maintain most of the operational and sales support systems in the company.)

Think about maths tests. A question asking the student to write down the formula for gravity is testing recall of implicit knowledge. But a question asking the student to solve the time for a rocket to travel to the moon taking gravity in to account is testing for deep tacit knowledge. (Once you understand this you will never cram for a test again!)

If you are still a little confused by the difference, it can be enlightening to consider what happens when they are lacking. Inadequate information tends to degrade how efficiently we get something done. But inadequate knowledge degrades effectiveness. Without knowledge we may drive perfectly obeying all the speed limit signs, but end up on the wrong side of the city. 

So can knowledge actually be transferred?

So returning to our air-traffic controllers, their deep knowledge is very much of the tacit variety. Sure there are plenty of lists: aircraft types, runway numbers and landing priority procedures that they must remember. There may even be critical thinking processes that they call upon to resolve the various conflicts that occur in their role. But when pressed to recall these, in study after study, deep expert's struggle to do so. Yet by placing them in fully simulated situations, they can recall immense detail in order to solve the highly contextual problem at hand. But context is the key and expecting this type of knowledge to somehow assist in another domain is non-trivial, just as Carl suggests.

However, because Carl is speaking from the computer metaphor of the brain, he wrongly goes on to conclude that all knowledge is specific and there are no general cognitive skills that can assist.  Even worse, he seems to suggest that they use up valuable storage space which will be needed for domain specific knowledge later in their lives. If we accept his assumption that all General rules are "implicit" knowledge, then we might be tempted to agree with him. However we have all experienced people that have walked into a brand new situation and yet very quickly achieved a level of apparent mastery with no prior experience in that domain. So what is going on here?

That's where the neural model of the brain assists us. At its core, the human mind is an amazing pattern matching machine. It's ability to seemingly scan and compare incoming information with petabytes of stored experiences, images, smells, sounds, facts, situations and contexts seems superhuman, especially in light of the fact that that same brain has trouble remembering to buy milk on the way home from work!  But as things are practiced over time, refined, connected with other experiences, they become part of us, who we are, what we value and how we think. You see it isn't the "stuff" we remember that makes us good at something else - Carl is right there - but the very process of learning how to understand and master these new skills do. Not the amount we hold, but the process of learning to hold it. That is one of the reasons I called my business DeltaKnowledge. 

Not so alien after all

But it turns out that we have an innate understanding of knowledge in this form.

People have been aware of this for centuries. From the use of stories, myths and cavern paintings then later monuments like walking circles and Stonehenge to store and transfer knowledge socially, through to ancient Masters of the game of Go helping Shoguns to plan abstract military strategies and even the nursery rhymes that we use to teach our children complex ideas, values and social constructs. It is all much less about remembering "stuff" and far more about becoming knowledgeable, even wise. And that of course is what we call these people who seem to be able to successfully transfer their knowledge across domains. They are people whose wisdom we covet. We talk about sports people who when asked about making a critical play, they respond "It just felt right". We talk about the General who was asked how he made such an amazing decision in such a novel and complex situation, to which he answered, "lots and lots of good decisions." And when asked how he made lots of good decisions he answered, "lots and lots of bad decisions."

So then, should we be teaching our children general critical thinking skills?

My answer is an emphatic "YES!".

But not with the expectation that they will go and directly apply them like a maths formula, or recount them in a test of memorisation. But rather as a series of stories and examples that they can call on to build their own novel solutions to the problems they will face that possibly don't even exist yet. That is building deep, broadly reusable, tacit knowledge.

Oh, and the next time you find yourself wondering how you or your company will build the knowledge to solve some problem or other, may I suggest you start by first asking yourself "Am I trying to solve this by simply acquiring information? Or am I truly increasing our intellectual capital by building deep experiential knowledge?"

= - + - =

* Just as a footnote, one other, interesting model which blends these two is called KAM (Knowledge Asset Management). The idea here is to include Tacit, Implicit and Explicit knowledge under the knowledge banner but to stop the damaging assumptions by placing the focus on the "assets" that generate, transfer, store and apply it, rather than the knowledge "asset" itself.  Still prone to some misunderstandings, but has the advantage being easy to grasp for non-knowledge practitioners, and does keep the information tools in the supporting role where they belong. Quite powerful in large or highly structured contexts like air, rail, nuclear or mining industries. I am a fan of the way Ron Young brings this understanding to managers and executives. You can learn more about the approach in this short video here.

Social Collaboration tools in Foreign Cultures

Benedikt Sheerer is one of the up and coming young guys in the KM world.  I like his fresh approach, eager passion for social collaboration and the places it can take organisations in the Future of Work.

Based in Germany, recently he visited the Tokyo office of his company as part of the roll out program of their internal social collaboration tools.  You can read his report about it here.

Benedikt made three modifications to his usual launch presentation for the Tokyo staff. These were:

1. First: We reduced the amount of topics we explained and discussed. This was due to the language barrier (meaning it simply takes longer to get a message through). Moreover, since the Japanese culture is high in context, people need more time to make up their own picture.
2. Second: We also mitigated those messages that stress the social media possibilities to create short-cuts in the information flows (meaning: changing the role of management).
3. Third: We focused on longer practice sessions that allowed me to help each participant individually (otherwise reluctant to raise questions in the group).

I really liked these three modifications, especially the mitigation of messages about subversive applications of Social Collaboration tools. A lot of my Asian experience (being based in Australia) is with South East Asia, but the strategy is also applicable to Japan and something Westerners can easily overlook.

His insight that national and corporate cultures are interwoven is a good one. Possibly thanks to the popularization of Hofstede’s cultural dimensions theory, many seem to over-simplify culture or think of it as a separate master attribute, rather than the emergent sum of the many individual’s beliefs and behaviors (see update below). I like Harald’s advice to Benedikt to get the local people more involved in the process. Not just because it gets them engaged and starting on a learning journey, but because a project like this creates an environment where ideas and understandings can be explored in an iterative way and new applications of Social collaboration tools can be tested (and hopefully measured). This helps us avoid the “It worked there, so it must work here too” problem that many managers fall for.

Senior Executives are undergoing an interesting time right now.  The push for the advantages of the digital workplace is strong and I am seeing support for a lot of fantastic and progressive projects. At the same time, this is more than just process automation. There are long-term cultural and structural norms that are being challenged right now to allow digital (and AI after it) to see it's full potential. Challenges that appear to threaten of the executive's traditional power-base. Some are adapting, distributing knowledge down-to and among the decision makers closest to the problems. Others are centralizing power further through business intelligence tools, deep-analytics and the application of industrial-age thinking to modern knowledge workers.

Time will only tell what mix of the two styles will influence the successful companies of the future, but I think Social Collaboration tools are here to stay in some form or another. Whether it is corporate cultures or national ones, I think the key skill isn't going to be how to use the software, but rather how tolerant we are about others breaching what we consider to be our social norms.

UPDATE: After a challenge on twitter by Stewart MacLeod from State Trustees, I thought I should clarify things for the academics among us. When I refer to culture as the "emergent sum of the many individual’s beliefs and behaviours" I don't mean a simple addition. This concept takes in to account the embedded and embodied impacts of both the environment and artefacts that influence each of the individuals involved, like Org structure, technologies and a plethora of other factors that are both moulded by and in turn mould the evolution of the local sub-culture. For more of my thoughts about culture check out these articles here and here. For a really deep treatment of the subject, my nine part series on Knowledge Cultures is guaranteed to put you to sleep :)  I love Hannerz' quote when talking about culture:  "The term 'complex' may in itself be about as intellectually attractive as the word 'messy,' but one of its virtues in this context is precisely its sober insistence that we should think twice before accepting any simple characterization of the cultures in question in terms of a single essence."