Efren's employer recently acquired a competitor. The competitor had been struggling for a number of years, and the acquisition was a last ditch attempt to preserve at least some of the business (a complete closure was the only other option).

Now, "struggling for a number of years" sounds fairly vague, but due to some bad database design, we actually have a clear indicator of exactly when the company gave up:

CASE YEAR(SomeDate)
    WHEN 2013 THEN  
        SUM(Estimate2013)  
    WHEN 2014 THEN  
        SUM(Estimate2014)  
    WHEN 2015 THEN  
        SUM(Estimate2015)  
    WHEN 2016 THEN  
        SUM(Estimate2016)  
    WHEN 2017 THEN  
        SUM(Estimate2017)  
    WHEN 2018 THEN  
        SUM(Estimate2018)  
    WHEN 2019 THEN  
        SUM(Estimate2019)  
    WHEN 2020 THEN  
        SUM(Estimate2019)  
    WHEN 2021 THEN  
        SUM(Estimate2019)
    WHEN 2022 THEN  
        SUM(Estimate2019) 
    WHEN 2023 THEN  
        SUM(Estimate2019)  
    WHEN 2024 THEN  
        SUM(Estimate2019)  
    WHEN 2025 THEN  
        SUM(Estimate2019)
    WHEN 2026 THEN  
        SUM(Estimate2019) 
END

Here we have the classic "add a new column for every unit of time" design anti-pattern. A fun, traditional piece of difficult maintenance. But here we see exactly when maintenance stopped: sometime in late 2019 or 2020.

Now, I'm speculating a bit, but, I suspect this is pretty clear evidence of how the pandemic may have impacted some businesses. Someone was supposed to add the new column. They may have been laid off, or retasked. The maintenance task that had seemed so affordable to the business a year prior suddenly became untenable.

"Debts that can't be paid won't be paid," as the saying goes. Here's technical debt that couldn't be paid. So it wasn't. And the result was a company going under.