If a problem is re-occurring and between lots of people, it's probably the fault of the system that powers it. The system in this case is the software, so blaming the software is appropriate.

No it isn't. This isn't a gotcha. This is probably one of the most well known software behaviors on the planet.

You KNOW the problem exists, yet you STILL choose to use the software, THEN expect it to change its behaviors because its inconvenient for your very specific use case. Microsoft aren't going to fix this behavior because there are likely millions if not billions of spreadsheets that rely on it.

That is not a software problem.

People don't choose to use Microsoft products, the software is chosen for them by their organization. For a problem like this, the existence of the article may very well be the first step to switching to another solution. The first step in that process is raising awareness that there is a problem.

If only the organization was run by people.

To a first-order approximation, all people are not management.

we stand on the shoulders of excel users, thats the reality.

A convenient cop out there.

"I didn't install it, I only chose to use it for something it isnt suited for instead of looking for alternatives, not my fault"

People working in large organizations are frequently not even allowed to install software that isn’t pre-approved by N layers of management. The bottom line though is that Excel is made for data entry. If it’s not suitable for that use case, that’s a big problem with the product-market fit.

Excel isn’t a data entry tool. It’s a rather sophisticated analysis tool for tabular data. It’s success is derived from the fact that it’s very good at this, and is so easy for users to pick up. Mind boggling amounts of commerce and administration are driven my Excel.

It is however most suited to accounting and logistics tasks. For any more novel use case, you’re going to have to put some thought into how you use it, or use a more suitable alternative. Even for the tasks that it’s very well suited to, there will always be more sophisticated alternatives. But I’d consider the way it lowers the the technical barriers to entry an overwhelming positive, even if it doesn’t completely absolve the users from learning about how their data works. I have the same frustrations with developers who have been trained by ORMs to have no idea how RDBMSes work. But I consider it their fault for not learning their trade properly, rather than the fault of the people who make nice tools to help them.

I really like the comparison to ORMs

I cannot imagine a single piece of software that is more widespread and used without issue by huge swathes of people than excel.

But one specific use case for genetics means its totally unsuitable & and big problem with the product. Got it.

?

Excel documents almost always have issues, independent of genomics[0]. I can probably just skim through my emails and find a bunch of problem spreadsheets all over.

Fundamentally, the problem is threefold.

1) excel tries to be smart, and this works in the easy case and breaks down in the edge cases. The edge cases also tend to appear with larger data entry as various one-offs, so it’s particularly insidious

2. Excel is difficult to validate (formulas are hidden, naming things properly is a bit of a hack, no real typechecking, data constraints can be set but it’s hard to check what’s set to what across all cells, etc)

3. The typical user / target market isn’t trained to use what facilities excel does happen to offer.

Ultimately, the problem is that excel doesn’t “scale”, and by default you get the wrong thing.

And even if you know how to set things up properly, it’s near impossible to be sure it stays proper.

[0] https://www.marketwatch.com/story/88-of-spreadsheets-have-er...

Right. I doubt genomics registered as much of a market segment, and probably still doesn’t register.

> So we blame the software instead of blaming the downright lazy people who can't be fucked learning an appropriate tool even though that's their entire career.

Further, the software would be fine if you use it properly for this sort of use case (i.e. bring the data in via PowerQuery which has enforced types).

In reality the appropriate tool for research data actually doesn't exist (make it and become very rich). Excel is only sort of close if you squint.

There is one problem people have for their use case, so it’s inappropriate? Have you ever created an issue on some GitHub project? I guess you were using the wrong tool?

People choose their tools for some reason(s), and there is no law of man or nature that says that using a common tool for some esoteric purpose is somehow wrong, just because you consider it too easy.

That does not apply to the windows office suite, literally built on megatonnes of legacy & bug level compatibility. Or windows for that matter.

compbio is not a field you'd want to go in if you want to use well-written tools exclusively. There's tons of absolutely abominable Perl and R code powering critical pipelines everywhere you look.

What makes matters worse is that scientists, who are already not great coders, have to work with even less technical people (i.e. the physicians). These collaborative processes will inevitably involve software like Excel. Need your M.D. co-collaborator to annotate a gene list or whatever? Your CSV's getting re-saved in Excel whether you like it or not.