Sorry to break this, but working with data doesn't mean you have a data strategy!

A lot of teams stay busy with dashboards, tools, and pipelines, and it creates the feeling that progress is happening, but when you step back and ask what has actually improved in terms of decisions or outcomes, the answer is often unclear.

The problem is that activity is mistaken for direction.

Building reports, adding new tools, and collecting more data can look productive, but without a clear link to business impact, it rarely moves anything meaningful forward.

Roberto Croci I've seen organizations with beautiful dashboards that nobody actually uses to make decisions. The real test is whether the data changes behaviour instead of looking impressive. Jun 1 1 like

The Executive Outlook Love this perspective! The key is designing data flows that influence decisions and measuring whether the insights actually change outcomes. Jun 2

tgroenwals shared this post · Apr 21

KOMAL CHHEDA

Apr 20 · archived Apr 21

The biggest myth in data teams is that data workflow is a straight line.

Data → Model → Insight → Decision

That’s not how real systems work, it only looks like that on slides.

But in reality, nothing is linear.

Before you even get to insights, you’re already stuck in definitions, broken data sources, conflicting metrics, and teams that don’t agree on what “truth” means.

Then comes modeling, where assumptions change mid-way.

Then governance, access, and compliance slow everything down.

And even after launch, adoption fails if the business wasn’t aligned on the problem from the start.

Rakesh Khanduja The biggest bottleneck in data isn’t analytics — it’s the messy loop between definitions, trust, ownership, and adoption.

The teams that win stop managing data as a pipeline and start managing it as an operating system. Apr 20 1 like

Yassine Sakkaf The part about definitions and truth hits hardest. Most delays don’t come from modeling, they come from misalignment before the work even starts, KOMAL. Apr 20 1 like

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