Observations In How Things Go

Have you ever noticed the way new ideas and innovations seem to decay with their mainstream acceptance and growth?

The usual scenario plays out something like this….

1) A new idea or innovation is developed. The core community which includes the originators of the concept and a small group of early adopters contribute to its betterment, fine tuning and working the concept. These early adopters also promote the particular idea, innovation or methodology.

2) The community is comprised of mostly like-minded people all contributing their particular talents for the betterment of the whole. This is the pinnacle of the communal symbiosis for any new idea or innovation. The community is focused only on the betterment of the concept.

3) Now things begin to get noticed by the larger population and the core community starts to grow. This seems a good thing but in reality, the growth of the group leads to the decay and ultimate corruption of the original value of the idea of innovation.

So why is there; this inevitable degeneration and how does it happen?

What seems to happen is that as more people become aware of the concept, the fewer true collaborative contributors you get entering the community. The new idea quickly becomes the latest trend and is USED in the truest sense of word. The new community becomes widely known and becomes seen as a must do/have item. It is during this transitioning that the foundation principles of the original community are under the greatest threat.

The core community becomes the latest bandwagon to jump onto by the rest of the broader community. It is this extra weight of the “Hangers On” jumping on the Bandwagon that breaks the axel and makes the wheels fall off. These “Hangers On”, USE the new idea or innovation as a means to virtue signal and big note themselves. The focus drastically shifts from collaboration and the concepts improvement, to a “What’s in it for me” narrative.

This often leads to the decay and ultimate failure of most new ideas.

These “Hangers On” join the new community not out of like mindedness or a collaborative philosophy with a willingness to contribute and embrace the foundational idea or philosophy of collaboration. Their motivation is to be seen as part of, what I call, “the leading herd”.

So how do you identify the “Hangers On”?

They rarely understand the innovation or the collaborative nature of learning, they just want a quick fix to their problems. Just like students wanting to know the answers rather than putting the effort into actually learning and understanding the lessons they are taught.

Some final thought to share.

“With great acceptance comes greater corruption.”

If you are a member of a core group be watchful of the decay which will degrade the foundations of your community. This doesn’t mean not to share your ideas or innovations but to understand that you can only really learn when you have reached the particular mind set or mental maturity to actually learn and understand.

Knowing something does not mean you understand it.

Knowledge is not Wisdom but only its starting place.

Anything learnt needs to become part of your daily experience.

Not everyone is ready to learn and embrace new and foreign ideas at any particular time.

TRANSPARENCY; the Emperors New Clothes and You can’t handle the Truth

The very term Transparency as used in the modern world of Management and IT is at best ridiculous and at worst dangerous and an unsettling endeavour.

Harsh words but think about it; few of us could actually deal with knowing every detail about everyone or everything. The human animal has not evolved to store and process billions of bits of data and analyse them without bias or errors. The terms “Option Paralysis” or “Information Overload” spring to mind.

Despite our modern life styles, which are information saturated, we actually only skim or glance over the actual information by taking other people’s narratives as easily digestible chunks. The fact that, very few of us even try to understand the complexities of our own environment natural or man made, socially and biologically is testament to millions of years of evolution which has resulted in our ability to filter and categorise.

This same ability to group similarities and make inferences from them is the very same reason we find the simple task of analysing data, without bias very difficult.

We often extrapolate from only a few data points and behave as if the presented data is “True” because it supports our previously held beliefs. We even find the weight of truth behind an unsubstantiated and sample of one (statistically irrelevant) as highly engaging and important :-Anecdotes.

So is it any wonder why, as a general rule we find true Transparency difficult. We actually don’t want transparency; like the Emperor, once he realised he was naked, we feel exposed; naked for all to mock and find fault. So is it really Transparency that we crave or is it actually the ability to access the information that we need or may need to complete our tasks well and in a timely manner, without any foreseeable obstacles or errors.

So instead of Transparency we actually require a “Need to Know Framework” that would allow us to recognise and highlight important information in concentric layers of Impact and Importance from you the Epicentre. This framework would be derived from the PRISM – a topic for another blog.

Lean Kanban United Kingdom 2013

I enjoyed attending LKUK13 and would like to share some of the snippets that I found interesting. These are from my notes and are my interpretations – any mis-interpretation is entirely my responsibility and I am happy to receive any corrective feedback.

Mike Burrows – Kanban is like Onions!

  • If we organise the work, we make it possible for people to re-roganise around the work
  • Ask if any single improvement can benefit the Customers, team and organisation – the improvement is good if all 3 can benefit from it
  • To help with paying attention to flow, then keep work sized to see movement every day
  • Small acts of leadership – such as the routine from Toyota – leaders can ask
    • What is the process?
    • How can we see it’s working?
    • How is it improving?
  • Agreement from people versus agreement between people

Liz Keogh – Cynefin in Action

  • Frog thinking vs bicycle thinking – we can take a bike apart and put it back together, and it will work again – not a frog
  • We’re discovering how to discover stuff by doing it
  • Deliberate discovery – Risk (newest things) first – tell the story that’s never been told
  • Focus on how we can quickly get feedback

Edward Kay – Mulit-client Kanban

  • The ‘ready’ column makes a good handover point
  • Use ‘Help’ tokens to indicate that you need assistance with a story – either with context or skills – so that you don’t interrupt others and they can select their own time to help you

Torbjörn Gyllebring – #NoMetrics – the ephemeral role of data in decision making

  • Lines of code is the best metric (and everyone hates this) – great for archaeology, but it’s all from the past
  • Ethics – in a position of power, you start to influence people – do no harm
  • Our customers are those whose lives we touch
  • Clarification should be at the centre of any measurement effort
  • Data needs to always be relevant
  • Informational measures are useful – but it depends on how people perceive it
  • ODIM – a good model – Outcomes, then Decision, then Information, then Metrics – use the metric and then discard it
  • Know why you need the data

Yuval Yeret – Kanban – a SANE way towards agile in the enterprise

  • When trying to change culture, engage in marketing – identify and nurture opportunities
  • Start with leaders and managers
  • Need to balance between prescriptive guidance and no guidance
  • After a chance allow time to stabalise and recharge – then provide good reasons to get out of recharge mode

Chris McDermott – The Other Side of Kanban

  • Encourage shared understanding – not managers are dating agents and chaperones
  • Add a ‘ready to celebrate’ column onto the board

Stephen Parry – How to develop Lean leadership and create an adaptive, learning and engaging organisation

  • Reciprocity only works when there is a sincere and genuine feeling – does not work if there is a feeling of manipulation – It can be negative
  • ‘Dont bring me problems, bring me solutions’ is an example of leadership abandonment not empowerment

Chris Young – Models, Maps, Measures and Mystery

  • Asked why customer approval waiting times went up a lot – led to the idea to have customers sit with the developers
  • At one stage the customer started leading the standups
  • Added an extra column to personal kanban board ‘didn’t happen’ next to the ‘done’ column

Jabe Bloom – What is the value of social capital?

  • A value stream is a linear view of the social network
  • Swarms – form temporary teams on high-value problems with volunteers
  • Emergent slack – have 20% of time spent on interruptible tasks (tasks that no-one is waiting on)
  • Social capital is the ability to distribute and leverage trust (reciprocity)
  • In a low social capital environment we use consensus models
  • In a high social capital environment we trust each other to make decsions
  • Authority removes social capital (consumes it)

Jim Benson – Beyond Agile

  • Flow if you can, pull if you must (pull systems are all remedial)
  • No recipe for success – just a recipe for not likely failing
  • Trying to do agile versus delivering value

Zsolt Fabok – I Broke the WIP Limit Twice, and I’m Still on the Team!

  • If you understand small, incremental evolutionary changes and pull, then you can decduce the rest
  • The goal is to have a stable system – easier to improve it

Alexis Nicolas – Management hacking in progress

  • Managers should focus on learning. We can live with problems for 1 or 2 days because we have better risk management
  • Change is viral – not prepared planning – we can design a viral change

Troy Magennis – Cycle Time Analytics – Fast #NoEstimate Forecasting and Decision Making

  • Statistics is more of a logic problem than a maths problem
  • When we forcast, state the level of uncertainty – ask what point would sway the decision
  • Every choice we make changes the outcome – Decision induced uncertainty
  • Diagnostic models allow us to  run ‘what if’ scenarios
  • Estimating what could go wrong is more important
  • We should update our forecast each time we finish a piece of work because we have learnt more

Shadows

The image that I have used at the top of these pages is a photo that I took outside the London Zoo on the pathway between Gloucester Gate and The Broadwalk path. It was in February 2012 the week after CALM Alpha and it was a beautiful day – I think that the temperature reached 16 or 17 degrees Celsius. I felt almost alone – there were not many people around and I took a few photos from the same point such as the one below looking at the zoo.

Exif_JPEG_PICTUREI chose the image for this blog because there are some shadows at the front and not many shadows cast by the trees in the distance due to the scattering of clouds that were in the sky. I find the idea of shadows interesting, it is another way of looking at an object and I wonder if we can use the concept to look at methods and principles or values?

If we start with a principle or value from Agile or Lean – are the methods that we use like the shadows of those principles or values? Or is it the other way around?