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Most HR data is bad data (2015)
21–30 of 53 posts
Re: Most HR data is bad data (2015)
#22This is why you need to structure your review process around objectively verifiable info as much as possible. Have clear areas of responsibility for each individual, such that you can readily evaluate what they accomplished and how well it's working. They are responsible for a particular mission and set of objectives, and they either achieve them or they don't. This can't work without individual ownership, which is a…
This is pretty much impossible above a senior IC level, where job responsibilities are focused on coordination, collaboration and other "glue". The responsibilities are going to constantly change over time, and be different for every individual. Trying to define & document this is a fool's errand. I think you're way better served to set broader objectives that are not SMART goals and then continually discuss, identify and update concrete delvierables that serve the spirit of the overal goal. This helps stop actions from being irellevant or misaligned with changing priorities, and provides a body of hard evidence for evaluating performance. I encourage everyone I manage to spend a few minutes a week capturing all their accomplishments, specifically the "soft" ones that don't have artifacts and will be forgotten (by both me and the mployee), and take an initial stab at categorizing the item against our corporate values (because I know that's what their formal review will look like). I had someone (who is a high performer) turn their multi-hour review preparation cycle into a 20-minute cut&paste operation.
Re: Most HR data is bad data (2015)
#23Earlier quoted context omitted.
> who delivers 1/3rd the features as everyone else, but they offer such effective mentorship that their five teammates deliver features 2x faster? I haven't really encountered this. Generally speaking people who can teach others to be much more productive like that are unsurprisingly themselves, more productive. This fictional person would be better suited to a people management or coaching role as a individual contr…
Every team I've ever worked with (11) has had at least one person that would meet this archetype. Their team-based contribution usually wilts under the kind of individualized metrics being pushed for by some here and the team suffers as a result even if their own metrics get better.
Then do my second case, this person gets a different title so we can evaluate them differently.
Now with the major objection to objective performance review gone we can do that for the actual individual contributors.
Re: Most HR data is bad data (2015)
#24Earlier quoted context omitted.
Structuring the review around objectively verifiable data creates other problems. What if there's a developer on the team who delivers 1/3rd the features as everyone else, but they offer such effective mentorship that their five teammates deliver features 2x faster? If you design your review process around objectively verifiable data, then it's almost certain to undervalue a developer who's great at mentorship becaus…
> who delivers 1/3rd the features as everyone else, but they offer such effective mentorship that their five teammates deliver features 2x faster? I haven't really encountered this. Generally speaking people who can teach others to be much more productive like that are unsurprisingly themselves, more productive. This fictional person would be better suited to a people management or coaching role as a individual contr…
this type of person is exactly who we try to identify for staff and higher roles. They could be 20% or even 50% more productive as an individual, but if they raise everyone's game even 2% across 50 or more people they are producing far more value. The reality is they crush fewer tickets individually, and that's a good thing, but it gets perverted by a purely metrics-driven assessment.
Re: Most HR data is bad data (2015)
#25Earlier quoted context omitted.
People making lots of soft contributions like mentorship / leadership tend to be the kind of well-liked personable sorts who do well on non-objective assessments, which always manage to color evaluations even when you try to make them as objective as possible.
Not in my experience. I worked in 2 occasions with some older people (~ 65) that were the guru of their departments, very respected and listened. While people learned a lot from these 2 people, they were not too agreeable, but quite grumpy, I could say. That limited their careers, even if they were by far the best experts in their departments and overall the most valuable contributors, they were never considered for…
Same. The best people I ever worked with were grumpy graybeards (in spirit if not physically). Brusque is the kindest way to describe them. If you knew your shit, or at least demonstrated that you had exhausted your knowledge, they would help you.
That said, it isn’t _required_ for you to be a jerk; I’ve also worked with incredibly talented people who were generally kind. But they did not go out of their way to network and schmooze. IME, people who are concerned with what others think of them are the least accomplished.
Re: Most HR data is bad data (2015)
#26How about minimize how much anyone gets rated, and try to hire for, and structure incentives for, people motivated by: * success of the company, * success/happiness of the team, and * societally beneficial service (I assume this works best if your company also genuinely has those values. But if it does, no sense using the disproven methodology of sociopathic companies.)
If engineers are motivated by the success of the company, you get a Boeing situation, where company is doing well and planes are bad. Happiness of the team ... the guy bringing tequila shots and cupcakes to the office will be rated the best (we had a colleague that was baking cupcakes weekly, very popular, but not contributing otherwise to the company's success). Societal service? All companies are doing it, in some…
At modest size this is a self solving problem because companies full of cupcake makers and eaters simply go out of business. Boeing spent many years being led by the kind of folks who were motivated by the success of the company successfully and the wheels fell off—now literally—when it was lead by folks interested in short term profitability.
People have an inherent need to be useful to matter. Mr cupcake decided to matter by making friends with food but if his performance was objectively that bad it should be fairly easy to set performance goals of some kind and term him when he doesn't meet them.
This seems to be how a lot of functional places work best. Motivated people working together with relatively soft guidelines that turn into hard limits to get rid of dead weight.
Re: Most HR data is bad data (2015)
#27As a data scientist, this is one of those fuzzy subjective human problems that I just don’t think is going to be solved at all anytime soon. My proposal is that we allow managers and reports to shift around much more fluidly to find a good “fit”. How to implement that? No idea.
It really depends on the company. At large corporations with entrenched moats, government institutions, or quasi-government entities like large private universities, this definitely makes sense!
At startups with <50 people, there may not be a runway for all that. I've been summarily let go after 1-2 months at a startup for lack of culture fit, and it made sense to me -- they simply didn't have the resources available to mentor me and help me get my head in the right place.
Re: Most HR data is bad data (2015)
#28The author seems keenly unaware that all of this fake rigor in HR exists primarily so the company can say they have a process that is objective. This is not the same thing as actually having a process that's objective. More to the point, objectivity may not actually matter much because so much of how a team performs is down to how individuals within the team gel, and you can't train someone into having a personality…
Someone I know quite well works in aerospace. The team they were on was identified as outperforming all the other similar teams. Rather than making all the other teams more like that team, they broke up the team and spread its members around like some kind of FTE pixie dust. Most of that team left the org within the next 24 months, and none of the teams they joined got better. Some got worse. Applying the “promote yo…
The truly ironic thing is that they could have mined that effective team for people to move with meaningful raises/promotions in other areas slowly, moved new folks into that team to be trained by them, had that team work with other teams, studied that team or dozens of ways of actually spreading around the pixie dust. They just decided to get the golden eggs by cooking the goose if I can switch to another metaphor midstream.
Re: Most HR data is bad data (2015)
#29And don't forget that brilliant "HR says we can't assign any fives, and only a handful of fours" thumb on the scale.
Re: Most HR data is bad data (2015)
#30This is why you need to structure your review process around objectively verifiable info as much as possible. Have clear areas of responsibility for each individual, such that you can readily evaluate what they accomplished and how well it's working. They are responsible for a particular mission and set of objectives, and they either achieve them or they don't. This can't work without individual ownership, which is a…
What objective measurements are good for engineering?
You can come up with superficial ones: lines of code written, tickets closed, hours seen in office, but I doubt those are strongly associated with effectiveness. Everyone in has probably had weeks where they “did nothing” because they were working on a tricky problem or doing work outside of what was quantified.