Very nicely laid out. Though I must admit I'm not convinced that the root is data vs intuition. But I'm also not quite ready to refute it either.
This conclusion seems to find its ultimate focus on a tension internal to an individual and presumes that the individual has full agency and autonomy. That may hold in small organizations (where I'm often employed) but may not in larger organizations (where I often consult).
The DevOps example is a nice contrast because it easily roles up to the organizational level, even though several of its parameters can be applied at the individual level (work, time). So while data has the flexibility of application to both individual and organization, I'm not sure that intuition does.
As a final thought, I think there may be another dimension, or alternative expression of intuition. Perhaps it is rigor, or structure, of decision-making. The most structured expression of decision-making would be a coded algorithm which is completely deterministic in its results. The less rigorous end of the spectrum would be decisions based on emotional or other whims, nearly indistinguishable random dice roles or monkeys with keyboards.
I find that over time organizations tend to get more rigorous in their approach to decision-making, as they layer on processes and requirements in an effort to better manage risks and variations. Perhaps this is the basic contract with the concept of intuition.
Very nicely laid out. Though I must admit I'm not convinced that the root is data vs intuition. But I'm also not quite ready to refute it either.
This conclusion seems to find its ultimate focus on a tension internal to an individual and presumes that the individual has full agency and autonomy. That may hold in small organizations (where I'm often employed) but may not in larger organizations (where I often consult).
The DevOps example is a nice contrast because it easily roles up to the organizational level, even though several of its parameters can be applied at the individual level (work, time). So while data has the flexibility of application to both individual and organization, I'm not sure that intuition does.
As a final thought, I think there may be another dimension, or alternative expression of intuition. Perhaps it is rigor, or structure, of decision-making. The most structured expression of decision-making would be a coded algorithm which is completely deterministic in its results. The less rigorous end of the spectrum would be decisions based on emotional or other whims, nearly indistinguishable random dice roles or monkeys with keyboards.
I find that over time organizations tend to get more rigorous in their approach to decision-making, as they layer on processes and requirements in an effort to better manage risks and variations. Perhaps this is the basic contract with the concept of intuition.
I love this.
Geres my conflict cloud for data:
I want to succeed
I need to make good decisions rooted in reality
I should find the truth
I need to play well with others and look good
I should control the truth
You can't both look for the truth in earnest as a scientist may do because you must play along with others in the organization.
As Bezos put it : "we are not really truth-seeking in nature, we're social"
Problems persist because this conflict is inherent in decision-makers trying to collaborate.
Thanks for writing this.
"You need the methodology to be imposed from the top which means you have to get buy-in from the C-suite."
How do you recommend data teams get this buy-in? Or is it mostly out of their control?
I like how thorough this analysis is
“Such a methodology does exist! Amazon has been using it for years. It’s made up of three components:“
Do you mean the Weekly Business Review by that?