That cost analysis seems incomplete. How much did it cost to implement in the first place? That seems like millions of dollars in capitalization before service expenses are even considered!
But there are still opportunity costs! It’s not free to install dependencies across numerous code bases and hook into and label the events, even for a small business.
This seems like an extremely small endeavor.
That’s also not what happens when a larger company integrates Segment into their applications! That takes many engineering months to set up and then maintain for the lifetime of the app.
If the full costs are analyzed, is the money spent well?
There’s sone irony here in that much effort is put towards analysis of user behavior but very little effort put towards accounting for where the money is spent internally.
That is why there is a slowdown in customers using these MDS products, not what the author of the article claims, rather that when feet are put to the fire, expensive services that haven’t paid off their debt are given the axe.
GG*GGP "someone in our org will ostensibly have a good reason for setting up an event in Google Analytics"
In this case they already have Google Analytics. The question is whether it was worth exporting that data to BigQuery.
Then whether it was worth setting up GA in the first place is not discussed.
I encourage anyone in a position to make purchases or who has a say in what engineer labor focuses on is to get a copy of Horngren's Cost Accounting. It should make my position very clear!
FWIW, there is indeed capitalization occurring when an organization incorporates analytics, even the "measure all the things" approach, but the question is, once the total costs are discovered, does the return outweigh the expenditure?
These things cannot be considered in isolation, especially when using advanced approaches like Activity-Based Costing, something that is basically a requirement for a product or service that is fundamentally software in nature. There is too much complexity to treat managerial accounting in a software setting like a steel mill.
The reason why this doesn't happen is YOLO business management fueled by the casino that is VC backed companies. But we are in a rapidly maturing industry where margins are slimming and costs need to be reigned in, especially in publicly traded companies where investors will punish a company that makes wildly off target financial projections discovered when cash flows are reported in the following quarters.
I encourage everyone in all management positions to start thinking about and tracking actual costs. Not story points, not customer use patterns, but cold hard cash!
That said, most routine data collection in our org isn't from custom instrumentation requiring engineering lift. It happens when someone sets up their own event in Google Analytics or adds a new field in Salesforce or whatever. This kind of bloat is inevitable, and at my scale (which is pretty big but not like F500 big), with my stack, it's always going to be cheaper to just ingest everything than to spend labor on trying to manage and minimize it, especially when I can ingest a lot of stuff for cheap or free and then discard what I don't need.