XP Padding

Did you know that Liz and I have a total of 23 years of finance experience?  That’s pretty amazing to think about.  A family unit has over half an entire career lifetime’s worth of knowledge in an industry?  Wow!

That means, collectively, we know as much about the credit/deposit industry as someone who’s worked in it since the 1990s.  And to think that in 1998, we were in middle school.

Yes, I’m being obnoxiously sarcastic here, because this crap needs to stop.

It’s encountered more among younger managers with lower payband teams.  Some smoothskin fresh out of business school wants to make a large group of grunts feel important, so they come up with ways to make menial work sound valued with big numbers.  Now, pulling from my own career experience, a 1000 people with 1-2 years tenure in a call center have, according to this asinine logic, 1-2 thousand years experience with the company!  Big numbers are exciting and I feel like I’m actually contributing significantly to the bottom line!

No, I don’t.  I felt patronized.

I will explain why this is stupid.

Given that entry level employees share the same basic knowledge pool from their training, this knowledge overlaps.  It doesn’t compound.

Given that knowledge is dependent on the individual’s memory to be of use.

Given that memories fade after their creation.

Then a large pool of shared knowledge only increases the chance that a selection of said knowledge is retained somewhere in the group, but still fails on the individual level at the same rate.

Therefore increasing the labor pool only increases the chance that someone retains an element of training, not that the collective unit as a whole can all access this information simply because one person has it.

Therefore experience is not cumulative across a group.  It can only complement the total group’s value.  It’s part of the equation, certainly, but a different formula is needed beyond Excel 101 sum(A:A).  Something more complicated is required.


I will begin with Hermann Ebbinghaus’s oft-referenced simplified formula on memory loss.  Where t is time and S is the relative strength of a memory, then R equals the probability of that memory being recalled:

R = exp(-t/S)

For the sake of this exercise, I will assign t to the number of days since the memory was created, and S to a static value of 25–which I’m arbitrarily defining as a 25% value to the individual, because work training material is really riveting.

In this example, a person trying to recall a fact after 7 days would have a 76% chance of doing so.

Now if we scale this to a group, cumulative probability would calculate the chance at which all people with a group, P, would recall that memory (Rc):

Rc = (exp(-t/S))^P

Let’s say 3 people are in this group.  Scaling the above example would yield a 43% chance of every person remembering the fact.  The more people we add to the group, the less the chance that all members would remember the same fact.

I’m going to get crazy here and use this as a basis for my own theorem: Simon’s Theorem on Group Memory Loss Dynamic Experience Offset over Time.

And theorem’s are great, because they’re hypothetical formula extrapolated as mathematical representations of empirical observations.  As long as the math itself is correct, no one can deny what I’ve witnessed personally.  Ergo, while I can never prove my theorem to be right, no one can prove it’s wrong.  Suck it!

Ahem.  Anyway…

I’ll assign a value to the group now (Ev).  As in usefulness, not numerical.  A 1:1 would be the ideal ratio, but that’s not going to happen because of the initial premise.

Ev = P((exp(-t/S))^P)

So after 7 days, the data retention of those 3 people on a 25%-level of interest piece of information turns these people’s usefulness, as units of the whole, into the equivalent of 1.3 people.  Note how increasing the personnel further reduces the usefulness.  That’s because, again, information isn’t pooled across the group.

But also remember that increasing the group size increases the probability that any one individual will remember the information (Rg).  So we take the individual retention rate and raise it to the inverse of the group size.  Retention will never be perfect.  A data point may be lost to time no matter how many people are hired.  But it does continually raise the probability:

Rg = exp(-t/S)^(1/P)

Of those 3 people, individually there’s only a 76% chance that a specific individual will remember a piece of information, and of the group there’s only a 43% chance that they will all retain that information, but across the group there’s a 91% chance that any of them will remember that information.

This is where the group size makes an impact–on the chance that across the group as a whole, one of them will prove their use having retained the necessary information.  By increasing the group size, we increase that possibility.

But let’s go even further.  Because if you’re still reading, I feel we’re now on a journey together and I don’t want to disappoint.  I’ve grown fond of you, dear internet reader.

And because, if you’re very attentive, you’ll note that time will still gnaw away at the group recollection chance.  More people will increase the chance, but that’s not scalable.  What we need is a third way to increase value, since we can’t ever reduce time, and staff size always has a limit.  We need another variable.

That’s right!  We increase the number of informational items, which we have to do over time, else memory loss will still degrade the total usefulness at the same rate.  So we increase the total number of informational points learned per day.

I offer one final formula: the ultimate value of the group (Uv), which incorporates the logic of the prior formulas, quantifies the equivalent value of the group based on the equivalent value of people as units, but taking into account the chance of any one person remembering a select piece of information, and increases the value based on the number of information points presented per day (I) for the duration of t:

Uv = exp(-t/S)P((exp(-t/S))^P)tI

As mentioned, this value degrades with time, but can be increased with additional information points.  Also known as experience.  Ah, we’ve come full circle finally.


The value of a group is more complicated than its collective time.  If we base the value on total information, we can’t assume that all members of a group retain that information, and a linear function doesn’t apply.  We can increase the value of the group by increasing its number, which in turn will increase the chance that information will be retained by an individual, but to ultimately avoid group value loss, additional information–or novel experience–must find its way into each individual of a group on a continual basis.

And this is why we can’t just add up everyone’s tenure.  Experience isn’t cumulative.  It’s one variable in a probability function that someone in a sample size will increase group value through novel experience recollection.

Maybe lower management should cut back on the 3 martini lunch team building.


  • t = # days
  • S = strength of memory (25%)
  • P = total # of people trying to remember
  • I = items of value learned per t
  • R = probability of memory retention
  • Rc = Chance of all people remembering
  • Ev = Equivalent value of total people as units
  • Rg = Chance of any one person remembering from total # of people
  • Uv = Ultimate value of group

2021 Lights

There’s a story I like to share, because it’s a fantastic example of an old couple argument.  It went something like this:

Once upon a time, LED lightbulbs weren’t a major player yet, and it was in that brief period where the world was adjusting to CFLs, and old conspiracy theorists everywhere were collapsing from ruptured aneurysms after the government started mandating energy consumption limits on illumination.  Of all the things to worry over, and it took an NSA defector to get the general public to even acknowledge the government’s wholesale data mining of citizens’ digital lives–which, I might add, ended with the general public retaining their complete indifference.  But those lightbulbs!  The government’s up to something and we should be angry!

Don’t step on rattlesnakes. They bite.

A more rational complaint with early CFLs was their color spectrum.  Bright white lighting is but one source of the eternal migraine hell office workers must endure (a close second to bad bosses), and people were understandably reluctant to replicate those conditions at home.  And so began the lightbulb stockpiling (and, you know, because of whatever the government was up to).

Now, as an aquarium keeper, I wondered why no one would make a more yellowish bulb, for the variety of different colored fluorescent T8s I’d kept in my tanks over the years had clearly demonstrated that the problem was already figured out.

I didn’t have to wait long.  Manufacturers started making CFLs in more pleasant shades, and even printed the Kelvin rating.  But the damage was done.  It seemed no one trusted them, nefarious government plans notwithstanding.

Liz was one such slow adopter–not that she ever suspected crazy government plans.  Rational suspicion of plausible evil government plans, sure, like what most normal people have.  Nay, it came down to bad experiences with the early bulbs and the fact that the choice to use incandescents still existed, so why change?  The only reason I cared myself was because the old bulbs burnt out so damn quick and were expensive to replace.  There was a lightbulb cartel you know, which mandated an artificial lifespan of a maximum of 1000 hours.  Not a government conspiracy maybe, but certainly mafia-corporate shenanigans.

You want me to extend lightbulb life on this–the day of my daughter’s wedding?

To further place me into illumination cost woes, apartment wiring was generally limited to one switch-enabled outlet for a living room.  One lamp on one switch.  Turning the home from perpetual twilight into something by which one could actually read required a 250 watt bulb.  These bulbs were not cheap, and as mentioned before, burnt out quickly.  So I explored those new-fangled CFLs–a higher upfront cost, but a much longer operational  life.

Being sure to buy a low-K bulb, I installed a CFL of the same lumen rating the next time the incandescent burnt out.  Liz complained–when I suggested a CFL, when I was buying the CFL, and after I had installed the CFL.  I couldn’t tell if the difference was significant or there was bias.  So I hatched a plan: use the complainer as a test subject in a very brief blind study.

I ran back to the store and bought another incandescent, and swapped it when Liz wasn’t looking.  I then waited, and when she again complained about the bulb I triumphantly removed the lamp shade to reveal the same type of incandescent which had been installed previously!  Huzzah!  Turns out no one could tell the difference.  And all it took was a little bit of reverse-gaslighting my most trusted loved one.  A small price for the sake of finances.  She’d forgive me eventually.

In the meantime, I was cleared to finally start buying CFLs as old bulbs died.  And when CFLs lost their popularity to LEDs (which applied the CFL spectrum lesson immediately), there was no argument.

But…LEDs didn’t take this lesson to heart in all products.  Christmas lights were not given such discerning treatment.  And while I argued for their merits, such as longevity and more robust construction (they didn’t burn out or fail catastrophically after being put up…usually), I had to concede that they just didn’t look as good as classic incandescents.

But then Liz found a style of LEDs that resembled them.  So we switched over.  But every year she fears a return to the olden days, and buys more of that type, on the chance that the manufacturer will discontinue them.  And with more lights on hand, I put them up.  And the following year she buys more.  And I put those up too.

My point?  Well, I just find it an amusing story in marital disagreements regarding changing illumination technologies.  But she got her revenge.  Each year I spend more time crawling around on the cold roof.

Look at those classic-style LEDs. LOOK AT THEM!

May your days be merry and bright–with 2700K spectrum LEDs.


Let’s Get Ready to Roomba!

Appliances are the servants of the masses.

How badly can that Marx quote be parodied?

Still, it’s a relevant modern take.  Appliances, created to save labor, instead become the baseline expectation.  And while they may start as a luxury for the elite, they’re soon reduced in cost and made accessible to all.  They may save labor, but do they really save us any time?  Once everyone has them, they’re no longer life hacks.  Appliances don’t give us leisure, they just provide more time with which we’re expected to do more productive tasks.  And spend more money on the appliances’ maintenance.

But for that brief period of novelty, they’re great.

I had long considered robovacs to be a novelty, for how effective could they really be?  I distinctly remember the useless Dustbuster my mother had in the kitchen–designed to quickly and cordlessly clean up isolated crumbs.  And I also remember picking the crumbs up by hand and dropping them into the unit, because it lacked the power to do anything close to vacuuming, and manually removing the debris was simpler.  And of course there was the spite factor, because mom made me use the stupid thing, and I knew those crumbs would fall out the moment she went to use it herself.

The point: battery-powered devices were simply underpowered in the 90s.

But last year a Dyson cordless was gifted, and with it the realization that technology had indeed reached the point where battery appliances were now effective, provided the user had patience with charging times.

And so, with daily sweeping required in our house due to the dog situation, and some nice Amazon gift cards in my possession, why not?

Sebastian 1.0 does a better job than I expected.  He’s sadly impervious to verbal beratement, unlike my future baby-boomer-who-can’t-retire-because-he-never-saved-for-retirement-and-social-security-went-bankrupt-Sebastian-butler/manservant, but on the other hand he’s a lot cuter.

He even drew a up a nice map to provide as a progress report.  Well done, Sebastian!  Take the rest of the day off.

Perhaps robots are the new proletariat, at least until they rise up as one and slay us.  But such would be the necessary end to any exploitative social system.  For now, they save us labor, for better or worse.  For now, they serve us.  For now, they help us maintain our superiority.  And while one day the status quo may violently crumble, when the appliances upon which we depend withdraw their labor and we’re left with little time to ponder such thoughts; I shall at least for now have very clean floors.