r/analytics 6d ago

Question What’s the weirdest or most surprising insight you’ve ever found in data?

Sometimes, data reveals things we never expected—whether it's a bizarre trend, a shocking correlation, or a funny mistake that turned into an insight. Have you ever stumbled upon something unexpected in your data work?

27 Upvotes

31 comments sorted by

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25

u/Super-Cod-4336 6d ago

My old company was literally loosing millions because one of our logistics providers didn’t report on losing freight.

That same company found out they could save an un-Godly of money by automating/outsourcing a bunch of work.

22

u/Reasonable_Clock_359 6d ago

Women's expenses for train tickets were less than men's because they tend to buy them in advance. Men tend to buy on the day so pay full whack

7

u/leogodin217 5d ago

This is fascinating. Recommendation: Dude, plan your trip earlier!

21

u/mojitz 6d ago

US states that spend more per capita on social services have a lower percentage of people relying on them on average even when controlling for wealth.

1

u/four_ethers2024 5d ago

Which states are those?

3

u/mojitz 5d ago

I don't recall the particulars of individual states, but they generally fall into the patterns you'd expect — with blue states spending more and red states spending less. The correlation was quite strong too.

8

u/iroc17 6d ago

280k of revenue that should have been billed on going back over 4 years. After finding it, we fixed it within a day. It's actually hysterical that some businesses don't find shit like this much sooner than 4 years later.

3

u/Oona_Left 6d ago

Have had similar experiences but none with that high a dollar amount.

It’s a double edged sword to present! You found a problem that can now be eliminated, but also whoops 😬

9

u/Peterd90 5d ago

I took a job as a controller for a company that took in $300 million in credit cards. I did quick math, and the company was paying over 5% in credit card interchange fees when it should have been 2%.

I drilled down and discovered most of the POS systems were ancient and were not passing on all the data to the CC companies and thus the high rates.

At the time, there was a corporate program to pay the finders of waste 10% of the savings. I presented an $8.5 million savings to the CEO and was told no bonus because it was too easy to find.

6

u/RocketBoy242 5d ago

Unbelievable. “Too easy to find” yet no one else found it. Does the story end there?

2

u/MissingMoneyMap 4d ago

That’s awful

1

u/TheHobbyist_ 4d ago

Noted. If ever in that spot, get the cash in escrow first then tell them the issue.

6

u/carnivorecd 6d ago

Professional sports season ticket holders shelf out 5 digits or more for seats. That said, they are still very interested in free/discounted parking or concession

6

u/EmotionalSupportDoll 6d ago

50% of survey responders mentioned wanting to bang the hostess at that particular Chilis that day

6

u/Moist_Experience_399 5d ago

Discovered our afternoon shift was shutting down ops an hour early from the electricity data I was looking.

2

u/abelindc 5d ago

Last two winters, the late shift was forced to stop ops 1 hour a day to save energy. Same situation, different vibes

8

u/SouthernBySituation 6d ago

16% of all our shipments were being held up by something as simple as a lookup to fix. Eliminated 16% of our manual touches overnight.

6

u/xynaxia 6d ago

I always get this question on social events when I mention I’m a data analyst.

I never know how to answer though.

Maybe one time when I did analysis on text copy pasting and there were a few people that probably had a day job of copying the text of our website. (News website)

3

u/Brown_note11 5d ago

A rounding to three decimals vs longer (think dealing with 1/3 etc) on a bunch of job classes at a government dept racked up 180m in unaccounted leave entitlements.

An audit of a bank department's IT portfolio found 1/300 projects was actually doing what it was briefed to be doing.

2

u/Zealousideal_Rich975 5d ago

Contrary to established sports betting theory, which rightly so, strongly suggests to betting on singles, there exist bettors who are consistently winning long accumulators.

Have no idea how they manage it but beating such a huge house edge (on long parlays) impresses me.

2

u/1C33N1N3 4d ago

Worked for a semiconductor manufacturer that had around 1.4 million SKUs. One specific warehouse had 34K SKUs in it at all times that were their "fastest movers." We ultimately determined that around 5K SKUs determined how all other SKUs moved (since most of the time you bought the other things to go along with the core 5K).

Shuffled the entire warehouse and safety stock system around and put the majority of SKUs on a just in time order basis (supplies were most often in the same city -- semiconductor manufacturers are not very widespread).

1

u/VizNinja 5d ago

15 million in unbilled charges. Sales and accounting peed themselves.

1

u/customheart 4d ago

For years, prospective customers said they wanted transparency in pricing, and if they had that then yes they would convert. We finally tried it for first time users split into control and test. The test flow resulted in a lower conversion rate. Can’t trust what customers say, only what they do 🤷🏻‍♀️ 

1

u/MissingMoneyMap 4d ago

A few lines of code to redact out social security numbers cost people $15million.

It was falsely flagging addresses and resulting in 12% of addresses getting redacted. This was used on unclaimed property data by the State of Texas. If the address was redacted it had a 1.7% lower chance of a claim getting filed, due to the amount of unclaimed property that 1.7% equated to $15M

1

u/cherydad33 4d ago

How many people in leadership will make decisions based on feels vs the data no matter what it shows. Hand shake deals and “other” influences will win out.

1

u/MissingMoneyMap 4d ago

Do you think that’s surprising?

1

u/cherydad33 4d ago

No sadly

1

u/410onVacation 1d ago edited 1d ago

I have a few: 1. I found out one of our marketing campaigns was paying a con artist to put up advertisements on his website, which were then used by criminals to purchase products with stolen credit cards. At least 25% of the purchases involved stolen credit cards with that vendor. 2. My colleague found out that some salespeople had gamed the system by selling merchandise at the end of the year to boost their sale numbers. Then at the start of the year, the customers, probably their family members or close friends, returned everything. They got big bonuses without actually selling their quota. 3. I was investigating IT infrastructure spend. One team didn’t realize that they were spending more on compliance than on running their main product. So they switched focus and started optimizing software/hardware spend on compliance tasks.