I'm exactly the type of person that thinks everything would be better if there was just a ~Central Data (Science) Strategy~, but to play devil's advocate for a moment--how many engineering teams actually have coherent guiding policies that underpin all decisions and activities?
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"Software" is about as vague a raw material for achieving business value as "data" is. Not every engineering org is humming along perfectly happily, and yet SWEs don't seem to have the same level of existential malaise as data professionals. Why is that?
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My feeling is that it's a result of three big factors: org size, clearer expectations of the profession, and standardized patterns of collaboration across teams.
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It's obvious how org size matters. If there's more people to do the work, it's easier for it to get done even without detailed planning. You don't have to manage your resources carefully because there's more redundancy
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Clearer expectations for the profession is also pretty straightforward. SWEs are less likely to be asked to do something that's outside their skillset because the average tech employee as a fairly good idea of what the skillset of an engineer actually is.
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Replying to @imightbemary
It's ridiculously common for the same team if not individuals to be expected to do a bit of data engineering, a bit of forecasting, and a bit of product/corporate strategy, simply because that's just all Analytics, right?
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