'Serial' season 2 - and how the US Army failed to rotate its knowledge

Bowe Bergdahl is infamous as the US Army soldier who in 2009 voluntarily walked of his post in Afghanistan and into the arms of the Taliban. His gripping story is currently being told in the excellent 'Serial' series 2 podcast. 

The US Army is renowned for developing the original 'after action review' during the Vietnam war. This was the genesis of the US Center for Army Lessons Learned, which generously shares it's innovative techniques that maximise organisational learning. So, how did the Army use it's knowledge in tracking down Bergdahl? Badly, according to Major Jason Dempsey, a military planner with huge experience on the ground. In episode 2 of Serial entitled 'The Golden Chicken', Dempsey explains that that the US Army "rotated a few thousand dudes through there every seven to twelve months". He continues that "after 7 years of war there is no institutional knowledge of the in Afghanistan, nearly none. We were not there long enough to get fully engaged".

It seems that knowledge continuity and handover continues to be problematic even for the most mature knowledge organisations. In this case, with potentially lethal consequences. 
 

Tip; start with the first episode of Serial, before listening to 'The Golden Chicken'. Warning; you will be hooked!

Boardroom automation? The implications on knowledge activities and senior positions

There has been a lot of discussion recently about the impact of workplace automation and in particular the latest developments in artificial intelligence on knowledge work. This McKinsey article points out that senior staff, proxied by a high hourly rate, are also likely to be impacted. It notes that it is not jobs per se that are being affected, but many of the activities that those jobs entail.

We know that the KIN professional services firms (consulting and legal) are well aware of this development. For example, in legal decision-making and finance using the blockchain. How about other sectors? How do you see non-manual and knowledge intensive jobs being impacted?  Is this being received as an opportunity (for example to release time to focus on high-value customer activities) or as a threat to job numbers?

What are the organisational learning implications?

http://www.mckinsey.com/insights/business_technology/four_fundamentals_of_workplace_automation?cid=other-eml-nsl-mip-mck-oth-1512

(Photo credit: Wikipedia)

The Pickle Problem - applying market economics to knowledge sharing and collaboration

I'm a fan of National Public Radio's podcast 'Planet Money'. Last week they ran a 15 minute episode on how the distribution of produce donated to food banks in the US was transformed by an ingenious market solution. By the way, that's an economic market, not a produce market. 

The issue was illustrated by the need to get fresh fruit and veg to Alaskan food banks, when the perception was that long-distance chilled transportation was problematic. Hence an abundance of pickles in Alaskan food banks and an oversupply of potatoes in Idaho.

A centralized distribution network across charities had been set-up but, as with many centrally planned economies, was inefficient, slow and lacked local knowledge. The solution, described in this excellent podcast, was of the creation of 'Feeding America's economic trading market in both food and logistic solutions. The design, based on a kind of eBay, uses 'fake money' or shares, distributed for free to all food banks. They can spend this on donated produce or trade to move donations that are an over-supply or not needed at that place or time. You know that little buzz you get when you win an item on eBay; apparently participants get that when they 'win' a truckload of peanut butter (long shelf-life, not fragile, high in protein and kids love it).

It is an elegant, efficient and despite many doubters, very successful system. Not only that, but it connected many different people involved in food banks, produce production, supply and logistics. An unintended outcome was the creation of a Feeding America knowledge bank as well an efficient food distribution system.

'Knowledge markets' within large organisations tend to rely on 'if we build it, they will come', tech platforms or altruism. Could a free-market economy of the kind tried and tested in Feeding America's program, apply to knowledge sharing and learning lessons in large organisations and other networks? Could 'knowledge shares' be used as behavioural economics to incentivise collaboration? I'm acutely aware of unintended consequences, such as hoarding or gaming the system. These were uppermost in the system designed for Feeding America, but who would have thought that applying free-market economics to a charitable social enterprise would work? I'm co-facilitating the KIN Workshop 'Knowledge in Action' tomorrow which will focus on behavioural economics; I hope we have the chance to explore this idea. Do you know of organizations or networks that have tried applying market-forces to knowledge sharing?

Do take 15 minutes of your day to listen tohttp://www.npr.org/sections/money/2015/11/25/457408717/episode-665-the-pickle-problem

Move along there - Service Design Thinking

When looking in Google's toybox, I came across the wonderful Google Trends. In preparing for the recent KIN Webinar on 'Why Design Thinking will Save Knowledge Management" with Arno Boersma, I thought I would compare the frequency of headlines over the last 10 years for the phrases 'Knowledge management' and 'Design Thinking'.

'Design thinking' puts the customer/consumer right at the heart of every process, making engagement and satisfaction much more likely.  In recent years, investment in good product design has proven it's worth  (iPhone, Dyson, Alessi etc). Good design as applied to services tends to focus on the web (Google Search, heylululemon, TripAdvisor). Of course the smartphone is increasingly a 'service carrier'. But what about healthcare systems, tackling radicalisation or even entire organizational redesign? IBM are doing just that - they are training much of their management workforce in design thinking and are employing over 1000 designers.

The KM term may drop off the graph, but the fundamentals of Service Design Thinking - empathy, iteration, experimentation (with a tolerance for failure) and collaboration are critical for the future of knowledge sharing in an increasingly complex and busy world.

If you are looking for a great primer in design thinking, I heartily recommend the September cover story of the Harvard Business Review 'Design Thinking Comes of Age' https://hbr.org/2015/09/design-thinking-comes-of-age

Knowledge Needs Action To Create Value

The theme for the forthcoming KIN Workshop (1st December 2015) is "Knowledge in Action". Hopefully a title that will resonate with anyone who practices knowledge management, since it reminds us that knowledge without some form of action is worthless.

We consume knowledge in a variety of ways, e.g. through academic courses, reading or experiential learning. But what's the use of all of this accumulated knowledge while it remains dormant in our heads, or stored on our bookshelves? We can only realise the value of knowledge if we do something with it, and we all know that "to do" is a verb. So knowledge plus some form of action will release value.

Readers will have noticed that I've used a stock image (with permission) by John Antonios which is a variation of my equation, i.e. knowledge plus action equals power, which perhaps give more emphasis to this 'knowledge + action' dynamic, but I prefer to think of value rather than power, partly because some people may associate "power" as "self empowerment". And no doubt we can all think of examples (mostly bad) where that has happened throughout history....or in our workplace?!

Value is a different matter, because it can't be personalised or self-attributed; it's a measure of the benefit that might be gained by other people, for example from goods or a service.

One of the simplest ways of creating value from knowledge is by sharing it. We may not realise what value has been created by sharing our knowledge. We don't know what decisions we have influenced or the impact of those decisions. We can sometimes recognise the value of something we've said or done by the reactions of others, or the feedback we've received over time, but that's not always the case.

Speaking for myself, I've learnt far more from people than I've ever learnt from books, though I don't wish to dismiss books as a very useful source of knowledge. However, the power of tacit knowledge can't be underestimated, and we've never had better opportunities to tap into this knowledge through our networks - personal, private and social.  Belonging to and growing these networks is no longer an option; it's an absolute essential if we want to ensure our knowledge and skills are continually honed and adapted to the rapidly changing environment around us. Darwin called it evolution, but it's more fundamental than that, it's about surviving.

So, coming back to the point about knowledge and value. Knowledge without action has no value. We can be the brightest and most intelligent person we know, but unless we do something with this knowledge we are as useful a chocolate tea-pot (I think that might be a British idiom, but I hope the meaning is apparent).  Doing means sharing, helping, supporting, tacit-to-explicit, speaking, mentoring, teaching....I'm sure you can think of many other action verbs. Doing nothing with our knowledge is an opportunity wasted, and our net worth (value) equals nothing, zero, zilch.

I'm looking forward to the KIN Workshop in December, and listening to the knowledge being shared by our line-up of presenters and facilitators, the knowledge shared between delegates during lunch and coffee breaks and doing my bit to share. For those unable to be with us, knowledge sharing doesn't end at the workshop. It's made available on-line (explicit), the action verb in this case is - you've guessed - "published".

I can't yet put a figure on the value of all of this shared knowledge, but I know we're going to have a room full of knowledge, plenty of actions, so one thing for sure is that lots of knowledge + lots of actions = lots of value!

Hope to see you at the workshop or online.

Steve Dale

Just bad luck? HBR article on organisational learning (or lack of it)

Bad luck omikuji tied to ropes at the Yasaka shrine (Photo credit: Wikipedia)

Be honest - when you experience a failure, how much to you attribute to bad luck, timing or circumstance? How much to your own competence? 'Attribution bias' and other factors that may inhibit our learning are referred to in this excellent HBR article on organisational learning (or lack of it).  https://hbr.org/2015/11/why-organizations-dont-learn

Thanks to Daan Boom of https://collaboration.worldbank.org/ for highlighting this article

Maximising your network or community participation - it's not what you think

You may have heard it referred to as 80:20:10, the Pareto effect or something similar. I'm talking about the phenomenon that only a small proportion of your community or network are active contributors, the remainder being 'lurkers' or 'freeloaders'. An obvious example is the ratio of Wikipedia contributors to readers. 

One would think that getting the majority or all your community members to be active would be a good thing. However, crowdsourcing research by Zoran Levnajic at the University of Lubljana has shown that there is an optimum level of participatory effectiveness. Counterintuitively, it's not to get everyone to participate.

"Modern information technologies allow for massive number of subjects to be involved in a more or less spontaneous way. We introduce a modeling framework through which we study the effectiveness of crowdsourcing in relation to the level of collectivism in facing the problem. Our findings reveal an intricate relationship between the number of participants and the difficulty of the problem, indicating the the optimal size of the group"

With typical active-contribution rates for networks at around 10%, clearly efforts to increase participation are necessary and worthwhile. We can however take some comfort from this study showing that having a large proportion of potential contributors or consumers (I prefer these terms to the pejorative 'freeloaders') is actually a good thing. 

Which of your networks get close to Levnajic's magic 50% active participation rate?

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  Written by

  Gary Colet

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What does a new broom know?

You may be familiar with the thought experiment sometimes called the 'is it the same broom?'. In a the 12th episode of the last series of Dr Who, Peter Capaldi asks "you take a broom, you replace the handle, and then later you replace the brush. And you do that, over and over again. Is it still the same broom?".It's actually a modern variant of the ancient 'Ship of Theseus' question, in which the philosopher Plutarch asked whether a ship which was restored by replacing every one of its wooden parts remained the same ship.

This came to mind when a client recently told me that when analysing staff turnover in a particular department of 24 people, it was discovered that not one individual had been in post 5 years ago. If every member of staff was replaced over that period, is it the same department? Well of course it is; but it raises the question of continuity, and in particular what that department knows. I thought it fascinating that not only did they not know what they had forgotten, but had no idea that they might have had forgotten anything (credit: Donald Rumsfeld). Another very large organisation I met with this week told me they were now experiencing 50% turnover per year. That's an entirely new ship, or broom, every 2 years. They had vastly ramped-up their graduate recruitment program to compensate.

The know-how and organisational learning implications of this are enormous:

1. Knowledge retention initiatives for experienced individuals or those with unique knowledge simply cannot wait until someone leaves. A proactive risk-management and prioritisation process is vital to ensure scarce support resources are used effectively.
2. On-boarding has to be effective and well-supported. 
3. Knowledge must be stewarded by professional or subject-matter networks, not just vested in an individual.  Building up this 'latent' or network knowledge capability is the most sustainable risk-mitigation for such a scenario, but rarely a priority under such pressure.

Centuries after Plutarch, the philosopher Thomas Hobbes introduced a further puzzle, wondering what would happen if the ship's original planks were gathered up after they were replaced, and used to build a second ship. I leave you to ponder what this might mean for an organisation's knowledge distributed to the four winds.

Evidence-based decisions also need Critical Thinking

During World War II, the RAF lost a lot of planes to German anti-aircraft fire. They examined all of the planes that made it back to determine where to put protective armour. The picture below show an aggregation of where bullet holes had damaged the planes. Where would you put the armour? The answer appears at the end of this post (1).

This critical thinking exercise was just one that we used during the Knowledge and Innovation Network workshop on 'Evidence-based Decision Making' that we ran last week. Having reliable and complete evidence on which to understand the problem is the start. We learned from several case studies (VISA, IBM, Healthcare policy, Macmillan Cancer Support, the College of Policing and Norton Rose Fulbright) how they gather, present and analyse data, often in real-time, on which to make decisions. How often are your organisation's decisions made on the basis of the HiPPO (highest paid person's opinion) or symptomatic information?

Another experiential learning exercise I ran required teams to consider a 'scenario' and then rank 8 pieces of evidence in order of trustworthiness (2). The scenario was:

'You are a senior manager at a large Italian IT firm specializing in stock control systems. The productivity of the software engineers is below average for the sector. The Board of Directors wants to introduce a performance-related pay model, which the Finance Director says would ‘give the workers a financial incentive to carry out more work’. Since you are not sure what causes the low productivity of the engineers, you decide to consult a number of sources before you decide to implement a performance-related pay model.'

I shan't give you all 8 pieces of evidence, but here are just 4 for you to have a go at ranking, in order of 'trustworthiness' (a deliberately vague term).

1. You contact a senior consultant at a well-known consulting firm. This consultant tells you that based on his experience with a large number of manufacturing engineering firms in the US, the most likely cause for low productivity in firms such as yours, is lack of leadership. He therefore advises you not to introduce the performance-related pay model and provide leadership training for all supervisors and senior managers instead.
2.  The Chief Operating Officer (COO) shows you the graph below, indicating a wide variation of productivity between teams. It appears that teams with a large proportion of senior engineers (5 years experience and more) are twice as productive as teams with a large number of young and inexperienced engineers. She therefore advises you to invest in the training and support of young and inexperienced engineers and a more balanced distribution between the teams.
3.  The union representing the majority of the engineers has vigorously resisted previous attempts at introducing performance-related pay. The most recent of which resulted in a threatened strike ballot and even greater reduced output whilst negotiations were underway. The Board decided not to pursue the performance-related pay scheme.
4. The HR director tells you that the most likely cause for low productivity is lack of teamwork: it is well known that engineers in general lack social skills, and as a result don’t share task-relevant knowledge necessary to solve practical problems and improve performance. She therefore advises you to not to introduce the performance-related pay model and invest in team-building instead.

As you might imagine, having 8 pieces of evidence and 6 teams ranking them, resulted in a huge and passionate debate. This was of course the purpose - applying the principles of evidence-based decision making that we had learned earlier, to situations that are often ill-defined, with missing data and a host of assumptions that need to be made. This was a brilliant and stimulating exercise. The answers (or at least the consensus view!) are given below (3).

As an example of the importance of having a rich source of evidence on which to make decisions, how about this: "When making important strategic decisions, only 29 percent of organizations considered more than one alternative. Just adding a second option made it six times more likely that the decision would later be rated as ‘very successful.’ " (4)

Here's a final example of why critical thinking needs to be applied to data (5). 

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Answers and credits

(1) Answer to plane exercise (presented by Steve Dale): You only have data for the planes that have returned, not the planes that have been (presumably) shot down. You should improve protection in all of the places that have NO bullet holes.

(2) Based on an idea from Eric Barends of the Center for Evidence Based Management http://www.cebma.org/

(3) Answers to evidence ranking exercise (in order of trustworthiness and rationale):

#2 'The Chief Operating Officer tells you that …'. This is based on your own organization's data, which appears to provide objective and reliable evidence and comparison groups. Be careful about statements such as ‘appears to’; we would like to actually see the data regarding age distribution. Data points per team member may be a good indicator of productivity, but what about quality?

#1 'You contact a senior consultant at a well-known consulting firm...'. Represents professional opinion or experience since it is not clear what measures of productivity and teamwork were used. The opinion may be based on a general impression rather than reliable or valid data. How much influence does the different context (US) and different sector (manufacturing engineering) make?

#'The HR director tells you…'. Since no specific evidence is provided, the HR director’s advice should be considered a personal opinion or belief.

#4 'The union representing…'. Whilst this threat and previous experience may be a very important factor in how and when such a scheme is implemented, it is not relevant as evidence for the effectiveness of performance-related pay.

(4) Source: Professor Paul Nutt, Fisher College of Business at Ohio State University, strategy-business.com

(5) Source: Gizmodo.com

Lessons learned - the big daddy of failures

In the 1980s General Motors was in trouble. Financial trouble (Detroit was surviving on massive government cash handouts), union trouble (workers would deliberately leave rattling parts inside door panels and get drunk on the lines) and was losing massive amounts of market share to Japanese imports. Toyota and Honda were showing-up the GM products for what they were; shoddy, poorly designed, thirsty dinosaur cars. Then came a remarkable offer from Toyota - they would show General Motors how they build quality, profitable, desirable vehicles. Not only that, but they would build and jointly run a car manufacturing plant in the US to actually teach GM how to build the best mass-produced quality cars in the world. The result was the New United Motor Manufacturing Inc (NUMMI) factory in Fremont California.

Why would Toyota do that? Surely helping an ailing competitor would be like turkeys voting for Christmas?

What happened is the stuff of legend; a great story about how successfully applying lessons and transferring knowledge is nuanced and much more than replicating 'good practice'. Did Toyota know that GM would simply be unable to understand, let alone replicate, the culture and ethos that we now know as 'kaizen'? Did GM know that it was Toyota that actually wanted to understand the American way, so that its planned US manufacturing expansion would take account of US worker sensibilities?

For anyone interested in this story and the cultural and organisational learning aspects of knowledge transfer, I heartily recommend listening to Frank Langfitt's 'This American Life' NUMMI podcast.‌ First broadcast in 2010, this story is truly the daddy of lessons not learned, resulting in the original 'too big to fail' bail-out. The naivety, missed opportunities, incompetence and yes, some success will make you laugh and weep; like the big hairy auto worker whose life was changed by the experience. 

Did GM did learn and apply the lessons from Toyota? It took GM and the other US auto manufacturers decades to really take advantage of what Toyota offered them. That's probably why you are driving a Honda, Mitsubishi, Nissan, Lexus or Toyota today.

KRT SIG Announcement: Knowledge Transfer for Joiners - Please build me a spacecraft

Three years ago my son joined an advertising agency - it was his first job after university. Those who designed the agency's induction process had really thought about the know-how and know-who that somebody new to an organisation (or indeed the world of work) rarely gets . Each graduate was given a 5 week assignment that could only be achieved by them talking with campaign planners, account managers, creatives and a number of the back-office functions. This wasn't make-work, but a real project which helped them feel productive as quickly as possible. The unstated aim was of course also to help the newbies build their personal network. What reminded me of this was reading about NASA's Project HOPE - 'Hands On Project Experience'. Jon Boyle and Ed Hoffman of NASA recently published a paper http://km.nasa.gov/wp-content/uploads/sites/3/2015/03/Real-Knowledge-at-NASA.pdf that describes their 'knowledge services model for the modern project environment'. The section on how the HOPE program features a number of case-studies where early-entry NASA managers have to design, develop and launch an suborbital flight project in 18 months. In this way they learn quickly about the business, governance, operations policies and standards- and presumably started to build their personal networks too. All too often, new starters are thrown in the deep end of an existing project and expected to 'pick-up stuff' as they go along. An alternative could be to:  Engineer an induction project for new starters such that they make a contribution as soon as possible. This also reduces the 'time to competency' for the organisation.  Help them make a wide-variety of connections outside their immediate team/function Asks 'what else does this individual bring to the organisation, over and above fulfilling the job description?' This is particularly important and valuable for those joining from other organisations or with sector experience. I've come across organisations that do elements of these, but not all. Has anyone else come across intelligent and interesting knowledge transfer for joiners programs? Join in the discussion on our new LinkedIn group

ISO 9001 revision - what knowledge managers need to know

For those not familiar with ISO 9001, this is the over-arching international standard for Quality Management. After a four year gestation, an update http://www.iso.org/iso/iso9001_revision is due out in September. For the first time this requires any organization adhering to the standard to demonstrate 'the management of organizational knowledge'.

I've had the devil's-own job navigating the ISO website trying to find out what this really means for those of us working in organisational change and knowledge management.

This is all I have been able to glean about the new requirement:
1. Determine the knowledge necessary for the operation of processes and for achieving conformity of products and services
2. Maintain knowledge and make it available to the extent necessary
3. Consider the current organizational knowledge and compare it to changing needs and trends
4. Acquire the necessary additional knowledge.

Why the words in bold? I am a fan of Josh Bernoff's blog www.withoutbullshit. In this posting he talks about the insidiousness of the 'passive voice' and how to avoid it. The highlighted words above exhibit the worst of this trend. To be fair, there may be more detail on what is meant by the 'knowledge necessary' or 'the extent necessary', however I can't find them in the labyrinth that is the ISO Technical Committee's website. I certainly hope that the final ISO 9001 document is written in more explicit, directive and helpful terms. If not, this is a missed opportunity to leverage the global International Quality Standard to reinforce the importance of knowledge transfer in organizations. 

The 'Passive Voice' Zombie Detector

In managing knowledge and encouraging organisational change, clear communication is paramount. This applies to how you get your message across and the techniques KIN advocates for effective know-how transfer. 

I've started following Josh Bernoff's postings on withoutbullshit.com for inspiring and practical tips on improving my written communication. Recent advice has been on the scourge of 'passive voice'. This is somethin

g we do without realising we are inadvertently and unnecessarily diluting the impact of our message. Simple things, such as using generalisations such as 'it is recognised that'. 

Josh's excellent posting yesterday was about how to identify passive voice with a simple 'zombie test' and how to fix it. 
Uncomfortable though it was, I forced myself to go back over the emails I sent this morning and apply the Bernoff Passive Voice Zombie Test. It was instructive to say the least. 

In a world where it is increasingly difficult to get attention (I'm currently reading Captivology: The Science of Capturing People's attention, by Benn Farr), why communicate with one hand tied behind your back? Make your voice assertive not passive - and listen to Josh on how to do it. 

"Big data: are we making a big mistake?"

The following is from what is probably the most useful and cautionary tale written about decision taking based on big data. Extracted from the March 2014 FT Magazine 'Big Data: are we making a big mistake?' by Tim Harford.

In 1936, the Republican Alfred Landon stood for election against President Franklin Delano Roosevelt. The respected magazine, The Literary Digest, shouldered the responsibility of forecasting the result. It conducted a postal opinion poll of astonishing ambition, with the aim of reaching 10 million people, a quarter of the electorate. 

After tabulating an astonishing 2.4 million returns as they flowed in over two months, The Literary Digest announced its conclusions: Landon would win by a convincing 55 per cent to 41 per cent, with a few voters favouring a third candidate.

The election delivered a very different result: Roosevelt crushed Landon by 61 per cent to 37 per cent. To add to The Literary Digest’s agony, a far smaller survey conducted by the opinion poll pioneer George Gallup came much closer to the final vote, forecasting a comfortable victory for Roosevelt. Mr Gallup understood something that The Literary Digest did not. When it comes to data, size isn’t everything.

Opinion polls are based on samples of the voting population at large. This means that opinion pollsters need to deal with two issues: sample error and sample bias.

Sample error reflects the risk that, purely by chance, a randomly chosen sample of opinions does not reflect the true views of the population. The “margin of error” reported in opinion polls reflects this risk and the larger the sample, the smaller the margin of error. A thousand interviews is a large enough sample for many purposes and Mr Gallup is reported to have conducted 3,000 interviews.

But if 3,000 interviews were good, why weren’t 2.4 million far better? The answer is that sampling error has a far more dangerous friend: sampling bias. Sampling error is when a randomly chosen sample doesn’t reflect the underlying population purely by chance; sampling bias is when the sample isn’t randomly chosen at all. George Gallup took pains to find an unbiased sample because he knew that was far more important than finding a big one.

The Literary Digest, in its quest for a bigger data set, fumbled the question of a biased sample. It mailed out forms to people on a list it had compiled from automobile registrations and telephone directories – a sample that, at least in 1936, was disproportionately prosperous. To compound the problem, Landon supporters turned out to be more likely to mail back their answers. The combination of those two biases was enough to doom The Literary Digest’s poll. For each person George Gallup’s pollsters interviewed, The Literary Digest received 800 responses. All that gave them for their pains was a very precise estimate of the wrong answer.

The big data craze threatens to be The Literary Digest all over again. Because found data sets are so messy, it can be hard to figure out what biases lurk inside them – and because they are so large, some analysts seem to have decided the sampling problem isn’t worth worrying about. It is.

Does cheese consumption cause death by bedsheet? Correlation is not causation

Yes, there is an apparent perfect correlation between Per Capita Consumption of Cheese vs Number of people who died by becoming tangled in their bedsheets.

This and other crazy correlations come from the research I am doing on 'Evidence-based Decision Making' for the Knowledge and Innovation Network Autumn Workshop. I was reading an article in this month's Wired magazine about 'spurious correlations' when I came across Tyler Viglen's website. Tyler has lots of funny and ridiculous examples to prove that correlation is not the same as causation. Even when decisions or inferences are made on the back of 'evidence', it's worth understanding what you are looking at.

Here is Viglen's random correlation generator http://tylervigen.com/discover. Have fun.

Related articles

• The "Starbucks Effect": Correlation vs. Causation
  

Shoelace tying modalities (seriously)

Which is more effective?

1. Describing to me how to tie a shoelace
2. Writing down how to tie a shoelace
3. Drawing a diagram of how to tie a shoelace
4. Showing me how to tie a shoelace
5. Getting me to practice tying a shoelace

It's a no-brainer, right? So why is it that we give so little thought to the preferred learning style and appropriate modality for learning at work? Knowledge assets should be created with the user in mind, not the creator or author. Word or Powerpoint seems to be the default format, when a more appropriate medium may be more powerful and transferrable. 

This was bought to mind last year when the superb Lulu Pinney ran a 'Knowledge Visualisation' workshop for KIN. We looked critically at examples of good and bad infographics. It became absolutely clear, through example, how appropriate content design impacts the transfer and adoption of knowledge. On my Knowledge Transfer skills course we look at the most appropriate and creative formats, channels and media, looked at through the user's perspective.

In case you were wondering, there are hundreds of diagrams and videos to help you learn how to tie a shoelace. Given the typically unfathomable example below, my suggestion is still to ask your mum to show you.

Watch your language - knowledge vs information

The pyramid of Data, Information and Knowledge has been knocking around for years. I often see 'Wisdom' tacked on top. I find the word slightly pretentious, so prefer 'Insight' as it is more action oriented. 

The terms 'Knowledge' and 'information' are used interchangeably by many people and with little thought to what makes them different. This is not just a semantic argument; how we manage each is very different and requires different skills. I use this graphic, or a variation of it, at the start of many of the knowledge transfer training sessions that I run. I also use an illustrative example, such as:

• Data - Field 1:13, field 2: 12, field 3: 08:17 
• Information - The timetable for my number 13 bus to work shows that it is scheduled to arrive at my closest stop (12) located on Ridgeway Drive at 08:17 
• Knowledge - Through experience, I know that this bus is sometimes 2 or 3 minutes early, often full and that mothers with strollers get on the front rather than back doors, as that is where the stroller space is.
• Insight - Walk to one stop before Ridgeway Drive by 08:10 and get on using the rear doors (insight)

There is no way you would get that knowledge or insight from the bus timetable, but you might if you talk to a fellow passenger.

By the way, the layers in the graphic do not represent a hierarchy of importance. Informed decision taking depends on evidence as well as insight. Accurate and timely data is critical in both operations and evidence based policy-making. 

The bridge between information and knowledge is metadata; the human factors that make information findable and most importantly allow people to connect. I've recently added the metadata layer to this graphic to emphasise this.

A holistic view of managing information and knowledge is important, but let's get on the right bus.