I am industrial engineer who worked 10 years in automotive industry as Lean Expert, Project Manager and R&D manager. We had EU funded manufacturing innovation projects. We have designed manfucturing robots that didn’t exist at that time. And in those times it was so challenging for me to manage these projects.,

I didn’t know until I changed my career to HR and consultancy, that actually in R&D I was mainly dealing within the complicated domain. It is harder to decide, harder to position yourself if you are in the complex domain. So let’s explore what I mean by this through Cynefin Decision Making Model. 

Cynefin model was ceated by Dave Snowden. He describes it as a Sense making and Decision enabling framework. The model is very deep and needs a huge effort to understand fully. For the sake of simplicity we will be exploring the 3 domins in it. Obvious, Complicated and complex domains. 

In the Obvious or the Simple domain, the cuase and effect relationships exist. They are predictable and repeatable. It is like baking a carrot cake. If you use the same ingredients and the same recipe, you will have the same cake at the end. 

In the complicated domain, there is a couse and effect relationship that exist but it is not so self evident. You need to sense, anayse and if you do not have the expertise your self, need to bring some experts in. Like designing a robot like I did when I was an R&D Manager in, or building a rocket to send to the moon. 

When we come to the COMPLEX DOMAIN, there is no evident causality. Things happened once some way, would not need to happen the same again. Cause and effect is only obvious in hindsight, with unpredictable, emergent outcomes. So the decision making model here is TRY (SO EXPERIMENT)-SENSE and RESPOND. 

If you would like to analyse, you will get analysis paralysis here. We should conduct ‘safe-fail experiments’, we cannot do ‘fail-safe design’. With trials, failures and learnings from them; an ‘emergent, new practice’ evolves. 

People say parenting is not rocket-science; but parenting, leading an organization, managing a cultural change program, getting in process a new HR & management system; all are in complex domain.

Experimentation is the process of trying methods, activities to discover what effect they have. Experimentation encompasses success and failure with its iterative nature of understanding what works and what does not. Both results are equally important for learning, which is the main goal of any experiment.

With Experimentation, 

• Decisions made by data, NOT opinions or assumptions, 
• Framework to question the status quo: 
• “Yes buts….”, beliefs, assumptions, biases… 
• and trigger new ideas,
• New ideas tested in production, 
• Users/customer data & feedbacks collected, 
• Product & process development guided by user/customer behaviour & preferences, 
• Emerging possibilities become observable. 

Safe-to-Fail Experiments are, 

• Small scale experiments, 
• Variety of angles, 
• Not random shootings in the dark,
• Not to ensure success or avoid failure;
  • to build your knowledge of the system, 
  • see applicability of change ideas by allowing those ideas that are not useful to fail, 
• Beneficial ideas to be enhanced and amplified. 

If you would like to start to design your safe-to-fail experiments, you may download our Safe-To-Fail Experiment Design Template.