Book Review: Arbesman - The Half Life of Facts: why everything we know has an expiration date

I don't why I never thought of knowledge as decaying over time. Especially when knowledge acquisition and transfer / spread is my specialist topic. Arbesman provides excellent examples and a logical argument to support his hypothesis that facts die out at a predictable rate. This is a fascinating thoguht, especially as in healthcare we believe that we constantly press against "old" facts which are stuck in the system. A reframing to think about what their "half-life" might be, is a useful and inspiring one.

Arbesman has come up with new vignettes rather than trotting out the old favourites. This is not a new take on an old subject, but rather a new subject requiring some disconfirming thinking.

Most popular posts on the Spread Good Practice blog

Here is the list of the most popular posts on this blog for the last 6 months.  If I'd had to guess I'd not have guessed these - nothing like a good bit of measurement to separate fact from opinion!

Model 2: data, information, knowledge, wisdom 22 Dec 2010, 1 comment 640 Pageviews

The quickest way to spread scale up change 21 Jul 2010 484 Pageviews

Model 1: data, information, knowledge, wisdom 20 Dec 2010 339 Pageviews

Using Twitter in the Classroom or Organisation 2 Sep 2010 320 Pageviews

Productivity 1: Operational Efficiencies are not e... 24 Oct 2010, 1 comment 284 Pageviews

Model 7: data, information, knowledge, wisdom

I thought I would stop at 7 models on the data, information, knowledge and wisdom theme - afterall, the brain is supposed to be able to hold a maximum of seven thoughts at any one time.  I've left my favourite to last. I particularly like the examples given at each stage. You can read more about this model on this blogsite.

Model 6: data, information, knowledge, wisdom

The Liebowitz (1999) model of DIKW is helpful if you are looking for something with details to give you ideas on what you might do in your own work. I can see how this can be used to evaluate large scale programs. The value aspects are useful reminders of the underlying purpose in moving to each stage, and therefore gives an idea of what might need to be planned for in a large scale program to achieve each step.

Model 5: data, information, knowledge, wisdom

So let's start 2011 by continuing the data-information-knowledge-wisdom series of posts with something creative from Topicscape's Mindmap directory:
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I like the zone of potential - zone of possibility continuum as well as half the "effort" being below the surface which can only really be explained by doing a drawing like this.

Model 4: data, information, knowledge, wisdom

The Model from Infovis below shows just what I always struggle in explaining to tohers as to why the results of one project cannot just be pushed onto other, adopting, groups.

The producers, the pilot projects, create the basic data and some information (patterns) about it. The consumers (the adopters) need to retest this in their own environment.  Any pilot project that can be written up in a way that helps the consumer to bridge the gap from information to knowledge will likely be more successful at spread than others. This can include things like: you can adapt this in the following way, we did the following and it didn't work but it may work in xyz circumstances etc.

Model 3: data, information, knowledge, wisdom

One of the QI refrains is "increase the capability and capacity of employees". While this is a great concept, easy to declare and impossible not to support, for me it lacks any concrete applicability. What exactly is meant by this? There is another one of our data-information-knowledge-wisdom models which may help pin down what might be meant. Next time you hear somebody say the capacity/capability thing then whip this model out and ask them to explain their intentions and expectations along the data to wisdom curve.

 The challenge here is to produce learning experiences that enable someone to move up the curve. In my experience, much of healthcare improvement work is focused on developing data based skills - how to measure change. Some people get to the information stage where they learn to look for patterns, say by using SPC charts. Can they port this knowledge to other projects in a predictable way? Can they make intelligent choices? To what extent do the participants on a QI project become "wise"?

The above curve comes from Designing Knowledge Eco-Systems for Communities of Practice.  The web resources are excellent - especially if you are developing CoP's as part of your QI strategy.

Model 2: data, information, knowledge, wisdom

There is an excellent post about wisdom on one of my favourite sites - Big Dog and Little Dog's Performance Juxtaposition (yes, really!).  It's a place I recommend you spend some time checking out.

I like the way this model gets me thinking about how we learn - there are connections here to the Honey & Mumford Learning styles.  The fact that there is a continuum for context is also thought-provoking.  This model has left me wondering whether in many of our quality improvement projects we focus too much on the bottom left hand corner and assume the progression to wisdom will be automatic. What would happen if we thought more and designed more of the journey to wisdom into our improvement interventions (and by extension, into our evaluations of projects)?

Model 1: data, information, knowledge, wisdom

The old adage goes along the lines that knowledge can be defined as knowing a tomato is a fruit, and that wisdom is therefore knowing that you don't add a tomato to a fruit salad...  There are a number of models and frameworks that investigate the data-information-knowledge-wisdom continuum and in the this series of posts I cover a few of these.

For the theorist a good place to start is with an online paper A Primer:, Enterprise Wisdom Management and the Flow of Understanding by ScottCarpenter@CognitiveCybernetics.com

I like the way environment and context have come into play as important factors in understanding that knowledge and wisdom have a contextual perspective.

Sharing - Seeking; a necessary dynamic of spread

The concept of large corporate databases capturing and storing "good practice" and "knowledge" was discredited by the late 1980's due to the costs involved and limited impact. It seems a standard approach to problem solving is to "start with what I know" and then if really desperate "find someone who can fix the problem". I frequently find that few managers and teams spend a short time seeking out information from those who have gone before them with regards the same problem.

A corporate database tends to be fairly clinical in approach. Woudl you rather get your ideas from the place where all entries have been approved, or from the hundreds of places on the web where forums are filled with people sharing not only technicalities of solving the problem, but also the emotion. Trust and credibility is importnat. How much do we trust the corporate database and how much do we trust what someone has written on a Forum.

Today I had a nightmare with MS Outlook consuming most of my computing CPU. The compiter temperature was rising along with my frustration and a literal metdown was predicted. A quick internet search revealed this was a common problem. The Microsoft database gace some suggestions but I chose not to follow them. INstead I found suggestions from "real" people, who reported on their tests of change and what worked for them, in their circumstance. Problem was eventually fixed (it was an overlarge normal.dot file if you're interested...)

I am hugely grateful for those who are questioning, providing repsonses and generally sharing their knowledge on internet Fora. Search engines are brilliant at organising this morass of wisdom. I really can't see how closed shop databases can be as effective in helping others solve problems.

The bottom lie though is the use of this wisdomw is dependent on some seeking it. So who will be actively seeking infomration from your database? If they use an internet search engine will they find your knowledge?

Knowledge management has lost its bark

I'm reminded of the old saying "It's not what you know but who you know". This struck me when reviewing a large and beautifully presented collection of "good practices" collated onto a website by an organisation. This is one of many I see and the teams involved assure me this is part of their knowledge management strategy and one of the mechanisms they are using to share the good practices amongst their constituents.

So I've been wondering for whom these databases have been designed. The measures applied are mostly about counting the number of entries and the number of "hits". This no doubt gives the owner of the system some satistfaction that the extracted knowledge (and I use that term cautiously) is being tapped into. Personally, I am a great deal more sceptical about the whole business.

There is an industry of "knowledge management" and a quick search through the academic publishing databases through up some interesting omissions. I could find little researched and/or published about how individuals or teams successfully used databases and turned them into practical changes that delivered improved results in their organisations - as this is the expressed intent of those who are creating these systems. It is as though the databases have become their own self-sustaining life form, with a purpose now disconnected from their original objective. At what cost?

The databases hold the "what" of information. Some individuals may remember the database exists, find the time to search it, reach the case study, work out how it fits in their circumstance etc. In my experience, most people will either start to solve the problem they have on their own or at best, will find someone in their personal network who can give them some advice. So, how can we find ways to help people extend their personal networks so they can connect to people who can help them answer the questions they want?

Part of the answer to this is a technology literacy - being able to access and use some of the Web 2.0 function including networking sites like LinkedIn http://www.linkedin.com/, chatrooms, wikizines, collaborative documenting etc. Part is an emotional literacy - having the conversational and interpersonal skills to connect with others.

By over-emphasising the "what" are organisations deskilling the "who"?




For an example of a wikizine go to
http://www.zimbio.com/Quality+Improvement+for+Healthcare+Services
and please post some content!

(c) 2008, Sarah Fraser