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The correct software for the job...

It's interesting to see how many people don't really understand that the results given back by any software, are only as good as the data entered into it to compute. In many cases the problem is not the software itself, but how people chooses the data to work with.

No matter how good the software is, if the right data sets aren't selected to begin with the results are just not going to be the ones expected. It's important to understand what data sets are meaningful to your problem, in order to make sure that those are the ones that are picked up. If not, all the hard work will be for nothing.

The problem that's being targeted needs to be correctly stated, so that the right parameters to be measured and the right data is collected to be studied. Armed with that information, the software can be better selected to the problems needed to be solved.

I've seen a lot of times, how a great piece of software selected to be used in a way it wasn't intended for. Needless to say, the results weren't the ones the users wanted and the software was blamed.

No software is a silver bullet that can solved every problem, that's why the user first needs to understand what needed from the software. Once that is clear, the software can be selected. Doing it the other way around is just asking for trouble that can be avoided from the beginning by selecting the correct software for the job.

In many ways, it's a matter of thinking before doing. Not doing so, only adds to the problem instead of solving it.

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