You probably have felt like this. You've devoted some intense time to solve a very complex and difficult problem. In the process, you've researched the field, made attempts to solve it in a few different ways. You've came across and tested some frameworks as a means of getting close to the solution without having to do it all by yourself.
You've discarded some of these frameworks and kept others. Cursed and blessed the framework's documentation, Google and StackOverflow all at the same time. You have made a few interesting discoveries along the way, as always, the more interesting ones coming from your failures.
You've learned a lot a now are ready to transfer that knowledge to your customer, so you start preparing documentation and code so that it is in a deliverable state. Your tests become more robust and reach close to 100% coverage. Your documents start growing and get data from your notebook, spreadsheets and test results. Everything comes together nicely and ready to be delivered as a coherent and integrated package, something that your customer will value, appreciate and use for some time in the future (and pay for, of course)
And along the way, you've committed to your version control of choice all your false starts. All the successes. You've built a rather interesting history.
Of course, at this point your customer will not see any of the failures, except when you need to refer to them as supporting evidence for taking the approach you propose. But that's ok, because the customer is paying for your results and your time, and he's not really interested in knowing how to get these. If your customer knew how to do it in the first place, you would not be there doing anything, after all.
But it is exactly on these final stages where the topic of accidental versus essential complexity raises its head. You've spent some time solving a problem, solved it and yet you still need to wrap up the deliverables so that they are easily consumed by your customer(s). This can take many different shapes, from a code library, a patch set or a set of documents stating basic guidelines and best practices. Or all of them.
The moment you solved the problem you mastered the the essential complexity, yet you have not even started mastering the accidental complexity. And that still takes some time. And depending on the project, the problem, and the people and organization(s) involved this can take much more time and cost than solving the problem itself.
Which nicely ties to the "Excel" part of the post, which at this point you're likely asking yourself what exactly Excel has to do with accidental complexity.
The answer is: Excel has nearly zero accidental complexity. Start Excel, write some formulas, some headers, add some format, perhaps write a few data export/import VBA scripts, do a few test runs and you can proudly claim you're done. Another problem solved, with close to 100% of your time devoted to the essential complexity of the problem. You did not write any tests. You did not used any kind of source control. You did not analyzed code coverage. You did not document why cell D6 has a formula like =COUNTIF(B:B;"="&A4&TEXT(A6)) You did not document how many DLLs, add-ons or JDBC connections your spreadsheet needs. You did not cared about someone using it on a different language or culture where dates are expressed differently. Yet all of it works. Now. Today. With your data.
That is zero accidental complexity. Yes, it has its drawbacks, but it works. These kind of solutions are usually what is described as "shadow IT", and hardly a day passes without you coming across one of these solutions.
What I've found empirically is that the amount of shadow IT on an organization remains roughly proportional to the size of the organization. You may assume that larger organizations should be more mature, and by virtue of that maturity would have eliminated or reduced shadow IT. Not true. And that is because the bigger the organization, the bigger the accidental complexity is.
If you look at the many layers of accidental complexity, you'll have some of them common to organizations of all size, mostly at the technical level: your compiler is accidental complexity. Test Driven Development is accidental complexity. Ant, make, cmake and maven are all accidental complexity. Your IDE is accidental complexity. Version control is accidental complexity.
But then there's organizational accidental complexity. Whereas in a small business you'll likely have to talk to very few individuals in order to roll out your system or change, the larger the organization the thickest the layers of control are going to be. So you'll have to have your thing reviewed by some architect. Some coding standards may apply. You may have to use some standard programming language, IDE and/or framework, perhaps particularly unsuited to the problem you are solving. Then you'll have to go thru change control, and then... hell may freeze before you overcome the accidental complexity, and that means more time and more cost.
So at some point, the cost of the accidental complexity is way higher than the cost of the essential complexity. That is when you fire up Excel/Access and start doing shadow IT.