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.

One loser in the UK election may be 'learning from failure'

Like me, if you are in the UK, you are probably thoroughly fed up with the General Election hype and puff. But bear with me on this one...

Frances Maude will be a loss when he steps down as Cabinet Office Minister. He appears to be a rare beast, a dedicated public servant who is not afraid of upsetting people to get his job done, whether you be a senior Civil Servant or MP of any party. He was the guy charged with saving £4bn per year from government spending by 2020; he is widely acknowledged to be on track to do just that.

Of greater loss will be his refreshing approach to 'learning from failure'. My goodness there has been ample opportunity to so that. Maude talked to the Sunday Times about a new civil service prize he introduced in 2014...

"I wanted to call it the Frances Maude Award for Failure. The criteria were that you had done something that had failed but you had learnt from your mistakes. In the end we had to call it the 'Innovation Award' and 70 of the 80 nominations were for things that had worked. No one felt that they could say that they had failed, but one should not have to be brave or fearless to speak out... If you are honest, voluntarily, about when things haven't done well, then you build up some trust".

That is great leadership and a good start to organisations, particularly big ones, acknowledging that when you innovate, some degree of failure is inevitable. As Einstein said 'anyone who has never failed has never tried anything new'.

Maude's leadership was well intentioned, but not enough. A client I worked with instituted high profile 'Failure Fairs'. That's a bit like inviting someone to voluntarily put their head in village green stocks. People need to feel safe that by sharing their, perhaps painful, experience they will not be humiliated or punished.

The other thing that is needed is that the learning is not just that "you had learned from your mistakes".  If you make a mess-up, it hurts and it's unlikely that you will repeat it. What's needed is for Mr Maude's successor to figure out how to differentiate between lessons identified and lessons learned. In other words, what has systematically changed as a result of that learning being applied to business processes or rules.

Roll-on May 7th.

Disclosure: I was the private sector advisor to a UK Cabinet Office review of 'Major Government Project Failures' carried out in 2000. Lessons learned anyone?

(Photo credit: Wikipedia)

Evidence-based decision making

We all have biases. It's perfectly natural for the decisions we make in life and work to be influenced by knowledge gained through prior experience and intuition. Most of the time this serves us well. However we would not expect major business decisions to be made just on on 'gut-feel'.

Using an open and transparent evidence base for decision making is now common practice in the Health and Third sectors and increasingly in Government policy making. Retail has been driving value from its customer data for years. Quality data, available in real-time is becoming an increasingly important resource for every organisation. Sources and quantity of data are proliferating and becoming almost cost-free; witness the 'internet of things' and open government data. Amazon and Facebook were built ground-up on 'big data' *.

However the analysis and facilitation skills needed are not keeping up with the huge leaps in data technology. By that I don't mean data scientists' skills, but managers' ability and confidence to make business decisions predicated on data analytics. A recent McKinsey insight highlighted the need for organisations to adapt if they are to get big results from big data. The example they give is that of an organisation geared around weekly or daily product price adjustments. Unless they adapt their business processes to leverage real-time competitor pricing and market conditions, they won't get the benefit from that data.

I am currently planning the Knowledge and Innovation Network members' Autumn quarterly workshop 'Evidence-based Decision Making'. This event is not for 'techies' or data-geeks; we will be looking at the organisational capability, processes and skills needed by KIN member organisations to improve rapid decision making. We have a great line-up of thought-leaders, case studies from members and experiential learning activities proposed. The KIN calendar will be updated as they are confirmed.

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* I'd heard the phrase 'big data' many times, but admit I didn't really know what it meant. Margaret Rouse has a useful explanation in her graphic; it is about exponential volume (Mb to PetaBytes), velocity (from batch processing to real-time) and variety (from spreadsheets to unstructured social data).

Supersonic collaboration

Bloodhounds aren't renowned for being fast. This remarkable Bloodhound will cover a standing mile in 3.5 seconds and break the 1000mph land speed record. When reading this remarkable story I was struck that it was a tale of near-perfect knowledge sharing and collaboration, as well as an engineering marvel. Listen to the audio clip of Yan Tiefenbrun, the MD of Castle talking about how he assembled the finest expertise from surprisingly diverse industries to develop completely new insights. They are not only building the fastest wheels, but a model for open-source knowledge sharing. If you face a daunting innovation challenge or knowledge-sharing problem, be inspired by this British cross-industry project.