As a Data Analyst / Business Analyst, let me assure you: Not all of us are stupid (some are, for sure), but there’s only so much you can do about stupid managers. If they decide that a certain measure is key, it can be really hard to explain why it isn’t that important or where a certain distortion comes from. To compound this, some managers genuinely don’t understand their business processes and are unwilling to have it explained to them. They’ll make assumptions about how things work, then base their demands on those.
For an entirely made up example, consider a department manager looking to monitor a software development team’s workload. That workload, to them, consists of bug tickets and feature implementations. Not counted here are feature requests because, apparently, fielding them and discussing their feasibility isn’t actual development work. That’s management work, which is the Product Manager’s job… Except the Product Manager can’t unilaterally decide whether something is feasible without consulting those actually familiar with the code, taking up the developer’s time. On the other hand, since it’s an internally developed tool for other units, they can’t just say No to every request or else they risk people calling their team’s funding into question.
Now, you have the choice between frustrating yourself and annoying the manager by trying to explain all that, or gritting your teeth and just giving them the stupid chart on bugs closed and feature implementations completed over time. Guess which one is healthier for your employment prospects?
And we haven’t even started talking about the variance in effort of bug fixes or about non-feature work for code stability or QA. Eventually, we’ll reach the point where the measure becomes a target and you have to start reframing bug fixes as features and splitting features up into smaller features just to make the figures look nicer.
What I’m getting at is this: Sometimes, the analysts aren’t to blame, but the managers making decisions.
That’s not to say there aren’t absolutely shitty business analysts out there that will gladly figure out ways to polish the figures and then cash the check for making the figures look better.
Thank you for that perspective. It seems to be somewhat similar and thankless to when I get tasked with taking microbio samples from the machines to check for contamination and then get grumpy department leads because the analysis results show over and over again that their cleaning procedure is inefficient.
As a Data Analyst / Business Analyst, let me assure you: Not all of us are stupid (some are, for sure), but there’s only so much you can do about stupid managers. If they decide that a certain measure is key, it can be really hard to explain why it isn’t that important or where a certain distortion comes from. To compound this, some managers genuinely don’t understand their business processes and are unwilling to have it explained to them. They’ll make assumptions about how things work, then base their demands on those.
For an entirely made up example, consider a department manager looking to monitor a software development team’s workload. That workload, to them, consists of bug tickets and feature implementations. Not counted here are feature requests because, apparently, fielding them and discussing their feasibility isn’t actual development work. That’s management work, which is the Product Manager’s job… Except the Product Manager can’t unilaterally decide whether something is feasible without consulting those actually familiar with the code, taking up the developer’s time. On the other hand, since it’s an internally developed tool for other units, they can’t just say No to every request or else they risk people calling their team’s funding into question.
Now, you have the choice between frustrating yourself and annoying the manager by trying to explain all that, or gritting your teeth and just giving them the stupid chart on bugs closed and feature implementations completed over time. Guess which one is healthier for your employment prospects?
And we haven’t even started talking about the variance in effort of bug fixes or about non-feature work for code stability or QA. Eventually, we’ll reach the point where the measure becomes a target and you have to start reframing bug fixes as features and splitting features up into smaller features just to make the figures look nicer.
What I’m getting at is this: Sometimes, the analysts aren’t to blame, but the managers making decisions.
That’s not to say there aren’t absolutely shitty business analysts out there that will gladly figure out ways to polish the figures and then cash the check for making the figures look better.
Thank you for that perspective. It seems to be somewhat similar and thankless to when I get tasked with taking microbio samples from the machines to check for contamination and then get grumpy department leads because the analysis results show over and over again that their cleaning procedure is inefficient.