
Ask HN: How do large and complex organization make “data-backed” decisions? - ramoz
-- Im looking for more of a general answer, references, or even tooling.<p>A naive example is Amazon Web Services and their offerings. How do they decide what to build, offer, improve, remove, etc in their AWS catalog? Givens would be things like their employment capabilities &amp; constraints, work in progress, expected outcomes ($) , time, and Im sure much much more. Maybe it would be many decision trees that ultimately form a singular tree where they could feed it data from the past and run simulations to produce forecasting? I&#x27;m just left wondering how do they standardize this across the organization and make it simple for everyone to provide their necessary inputs (ie an engineering team providing WIP and velocity).
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4thaccount
Not sure about giant Amazon sized companies, but I think the medium sized
company (~600 employees) might share some similarities.

At the lower end of the ladder you have worker grunts. Some of these grunts do
base level work, so do more long term thinking, and some do a combination of
the two. Then you have lower and middle management which have their own
priorities and then at the top your executives which also have objectives and
goals. An efficient organization has the right people at each step of the
pyramid. In reality you have good and bad engineers and good and bad
management. When things are working, problems I identify in the technical
realm are understood by my superiors and relayed up the chain. Things they
notice at their level of the organization (key stakeholder interaction occurrs
here) is also prioritized. Besides some major initiatives led by the executive
team, I see their key role as administrative and working on the organization
instead of in the organization if that makes sense. Educating upwards is one
of the hardest problems in all companies past a certain size.

