The numbers weren’t wrong

[u/WillingCamera3545]

This has been bothering me more than bad data ever did you can have a clean dashboard everything reconciles nothing is obviously broken and somehow two people can look at it and walk away wanting completely different things paid looks healthy, sales feels slower finance is looking at another number entirely. The weird part is they can all be right because they’re measuring different pieces of the same thing.

I’m starting to care less about making reporting prettier and more about whether somebody can look across all of it and decide what needs to change more dashboards haven’t really fixed that for me. If anything they sometimes make it easier to avoid the messy part where someone has to connect the numbers back to what the business is trying to do

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[u/MaxJustins]

This is usually a metric-definition problem wearing a dashboard costume. Paid, sales and finance are each right inside their own attribution window and date range - the fight starts when nobody agreed which question the number is supposed to answer. I got more mileage out of writing the decision next to the metric (if this drops 20% over 14 days, we do X) than from adding one more view.

[u/alurkerhere → u/MaxJustins]

Yep, this has more to do with data storytelling rather than the data visualization. I see more and more value in condensing down the data into the text takeaways while still providing the visuals and drill-downs for further investigation.

Show all the reporting, but give me the high-level of what you think and what it means.

[u/decrementsf → u/alurkerhere]

Two movies, one screen.

Look at a sculpture when the information you know about are parameters x and y, it's a rectangle.

Look at a sculpture when the information you know about are parameters are y and z, it's a circle.

Both are correct, they're looking through different sets of parameters at the same cylinder. When parameters are invisible to other groups because they have different backgrounds you get this funny game where each optimizing for their known information conflicts. This is where engineers will lay out all their parameters and compare to see what's missing. And non engineers tend to yell a lot and attach emotion to the yelling.

[u/Andrej-Zitnik → u/alurkerhere]

This is where I think the combination gets interesting. AI can surface the takeaway first, but I still want the chart/data behind it to verify why it reached that conclusion.

Have you seen people actually change their workflow this way --> insight first, dashboard second, or are they still mostly starting from the dashboard?

[u/WillingCamera3545 → u/MaxJustins]

That’s a good way to put it.

I think we were treating the disagreement like a data problem when really we hadn’t agreed on what each number was supposed to help us decide

[u/Lumpy_Alternative127 → u/[deleted]]

That’s the part that made Marketer interesting to me too more the idea of tying paid and measurement together than just adding another dashboard if every team is still working off a different number the reporting isn’t really solving much

[u/Rare-Ocelot87]

Sometimes the dashboard isn’t the problem at all the problem is nobody wants to own the call when two metrics point in different directions

[u/DR292]

had this exact thing and the fix wasnt a better dashboard, it was that nobody owned the across view. paid, sales and finance each had someone accountable for their own slice and no one was accountable for the version that spans them

once that role existed the dashboards stopped being where the argument happened, they were just where it got checked. is there anyone there whose actual job is the whole picture

[u/LazyTip8232]

I’ve started trusting the boring numbers more like qualified leads and closed revenue a dashboard can look great while the business still feels kind of off

[u/Defiant-Praline4024 → u/LazyTip8232]

That’s where I’ve landed too once the business numbers start moving the wrong way a nice looking dashboard doesn’t really make me feel any better

[u/Artistic_Coconut_823]

The hardest part for us wasn’t collecting more data it was getting everyone to agree on which number should drive the next decision

[u/LetsGoHawks]

somebody can look across all of it and decide what needs to change

That's the whole point of dashboards. We've all seen a million pretty dashboards and infographics that leave us wondering WTF they're trying to say. Don't do that.

[u/Top_Sentence1261]

that's the real skill nobody talks about enough. anyone can learn to build a dashboard in a few weeks but knowing which three numbers actually move the needle and how they connect to each other is a whole different thing

i've seen teams with the most polished reporting setups completely paralyzed because nobody wanted to be the one to say "we're looking at the wrong thing"

the worst is when leadership asks for more data thinking it'll resolve the disagreement but it just gives everyone more ammo to defend their own interpretation

[u/ObfuscateMe45]

I think analysts are supposed to be good communicators, and I'm having trouble understanding your post because it badly needs punctuation!

[u/ArielCoding]

Sounds like your metrics need couples counseling.

[u/Intelligent-Size-389]

Ai post ?

[u/Neither-Shopping-887]

I feel like this is the key reason why the whole "AI is coming for DA" bit isn't going to actually happen. You need someone to understand different stakeholders' needs.

[u/Andrej-Zitnik]

I think this is where “single source of truth” gets misunderstood.

You can put all the data in one place and still have three versions of the truth if paid, sales, and finance define the metric differently.

The harder part is agreeing on what the metric means, how it is calculated and what decision it should drive.

AI makes the “look across everything” part much easier, but it also makes the definition problem more important. Otherwise you just get a very confident explanation of the wrong version of the metric.

I’d rather have 10 governed metrics everyone agrees on than another 50-chart dashboard.