13 April 2018

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.


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.

08 April 2018

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.