Also, whatcha think on the article? Do you feel the process was valuable or brought positive non-obvious changes faster than they might have otherwise occurred? Also given the "tastes like chicken" genericism comment in the piece, what's a story that you think could /only/ have happened there?
Thanks!
Edit: real question
It very much reminds me of that show The Profit. Fix the books first, so you know where you're really at and what really needs fixing. Cut anything not making money. Focus on scaling the core business. I've seen all of these changes happen or are in progress.
Overall they've done a good job. As an old timer that's seen the good times and the money just spilling out, I can't help but want to grumble when they start cutting the fat, but it all makes perfect business sense.
I guarantee you that unless your company recently downsized (or is very small) there are things you can cut, because no one cared enough to fix them or they thought it was cool to have X even though X is not returning value.
A million times better that GSuite.
Does this mean unprofitable markets or things like janitors?
Of course, that was nothing that couldn't be solved through further attrition.
They were dumb projects anyway.
Also the liberal use of the word debt in the article worries me in the UK there have been a number of scandals where PE buys a company loads it with debt and flogs it to some dozy fund mangers and a few years later it all collapses - Debenhams is one example
Any employment requirement that produces a disparate impact has to be proven to be reasonably related to job performance. In practice, that probably means some kind of validation study tailored to each specific job catagory. That’s expensive.
The primary reason is that protected minorities score lower than average on IQ tests; without a legitimate business reason to set an IQ cutoff, you can be sued for discriminatory hiring. And because IQ is so granular, you don't want to argue in court that 1 point is a business necessity when you set a threshold of 110, and you reject a minority candidate with a 109 score.
[1] - https://www.theatlantic.com/business/archive/2017/04/economi...
We do quite a bit of general research and proof of concept as a part of our backlog, so the budget is there.
What do you/Vista consider to be the well-defined problems that machine learning solves? My understanding is that it is less well defined but I'd like to know what you think.
https://www.criteriacorp.com/resources/ccat_prep.php
Source: myself. I also work for a Vista company