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nobody has permission to think about disasters when estimating project completion time

I've been a part of a few large scale system implementations and we documented every significant risk to the project at the beginning and as we went if new ones presented themselves. This seemed to be a standard part of the PM's playbook, and I used to to save critical organizational capabilities when things collapsed:

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I raised risk on a must-not-fail deadline, but it actually failed and was the camel straw that brought the project down. (An Oracle product) PM's were didn't appreciate the risk. There's still probably an Oracle VP out there who really doesn't like me for using the established project protocols that allowed me to escalate the issue to the president where I worked and way above the VP in Oracle. On my own initiative I kept the legacy system-- supposedly partly decommissioned-- updated just in case so we could fail-over softly. This was unexpected: When failure became obvious I reminded the VP that I had raised the original risk, and then I had prepared for it. I think their plan had been to box us in to meet their increased $ demands.

It was part of another missed deadline required for a major milestone 25% payment on the contract, and it was a fixed-price contract so they should have absorbed the costs.

Instead, when the failure progressed to my area, we all showed up to work one day and everything was gone. No contactors, nothing was left, like a cleaning crew had cleared it out. A week of negotiations failed when they wouldn't budge from demands for extra $$millions to keep working on the project, plus their missed 25% milestone payment.

Ultimately I lost a years worth of work when things entered lawsuit land and sued each other for breach of contract. (we won-- or settled at least. The fixed price contract was clear, and the missed deadline were partly due to demos of fake functionality that didn't actually exist or components they knew would be EOL'ed after signing the contract & before implementation would begin. The case for outright fraud was pretty strong: We had videos of the demo.)

In case you're wondering, I don't like Oracle. Though with a different product we were still forced to use Oracle DB's. Those I actually don't mind and were a huge step up from the ~2000 MS SQL Server & much older DEC VMS file-based database that wasn't SQL compliant or relational.




I’ve struggled with Out of Life support from almost every database vendor. They create something that is very hard to change, upgrade or rip out, and then require you to upgrade it every few years. Lots of hidden costs for the buyer. They’re generally in a better negotiating position than understaffed IT departments.


Out of Life support was a huge issue in the case I outlined above. I kept things ticking over on my side, but there were no more updates from the original vendor except for bespoke work we had to pay them for to complete annual updates for federal compliance issues. Actually we pooled together with a few organizations in the same boat to do that until we rebooted the failed project.

To give the legacy vendor credit though, It was a legacy product 5 years past its "final" EOL and kept honoring the maintenance agreement and providing ToS updates for a long time. In terms of the database itself, it probably helped that it wasn't their own: It was native to OpenVMS and hadn't substantially changed in at least a decade. Ultimately that made data migration a bit easier since industry tools for migrating from VMS systems had reached maximum maturity by the time we got around to it.

I still have a soft spot for that old system though: It lacked any sort of modern functionality newer than about 1995 and the underlying application has it's nroots in the 60's. But it was fast & I had low level access to do some complex things much more easily than the upgraded system (installed about 6 years ago). You won't get much faster than a well-tuned decades-old system running on modern hardware, at least not unless you need something that can handle medium-to-big data.




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