Category: Quantitative Philosophy

Working for a large company, I often find myself in the scenario of needing information.  I therefore seek to resolve this knowledge deficit by sending a simple email to an individual who holds said knowledge.  Yet all too often my queries go ignored.  Why is that?  What deep underlying motivations have possessed this individual to turn a deaf ear to the needs of others?  What cruel, sociopathic inclinations govern this person’s actions?

I debated at length these social dynamics, but the answer wasn’t nearly so disturbing as my overly-dramatic introduction might have implied.  Rather, I conclude there are a few and very simple factors: Does the person feel they have time (an extension of job title and pay grade), does the person feel the inquirer is worthy of their time (also an extension of job title and pay grade), can the person benefit from the inquirer, has the inquirer committed some social slight against them, and does the person like the inquirer?

To distill this even further, from the contactee’s perspective:

• Are you at my level?
• Has there or will there be a quid pro quo?
• Do I like you?

Yet all reasons are not created equal, so based upon entirely subjective reasoning, I have developed a formula to weight them properly:

1. Each party’s pay grade.  The first thing an email recipient looks at when receiving an email from an unknown party is that person’s job title.  A lot of information can be instantly determined from the hierarchy.  If you’re higher than me, I’d better listen, for my future promotion could depend on it.  If you’re lower than me, well…(dismissive wave of the hand).  If we’re the same level, I should at least consider you a peer, and there’s the possibility that I might work for you one day.
2. Subjectives.  How well do I know this person, do we work together, do we have a good working relationship, and do I like you?  So much is difficult to determine from an email, but in short, if you’ve pissed me off, then you’re probably not going to get an answer.  Fair?  No.  True?  Always.  From failed experiences, I know to always humble myself accordingly when initiating contact.
3. Positive Empiricals.  Have you done good work for me before and are you a potential cardinal to my promotion?  Obviously I would want to maintain a relationship with someone who’s benefiting me directly.
4. Negative Empiricals.  Have you done lousy work for me before and have you beat me out for a job or opportunity?  Obviously I’d want to distance myself from a poor worker, but the last point does seem petty.  However, people take ego blows very seriously, and it’s no coincidence that former colleagues have severed contact when I became competition, and especially if I won.

As for probability, I’ve determined from experience that I will always get a response from a peer if every positive category is satisfied.  I will generally always get a response from someone lower with almost all of these conditions satisfied.  And I will usually get a response from someone higher with every condition satisfied.  However, if any negative conditions are satisfied, then the response rate very quickly drops.  As I stated, it’s weighted, and formerly positive relationships are always easy to sabotage since the human mind tends to remember the bad and not the good.  Here’s the formula for reference:

=IF(Their pay grade>Your pay grade,100*((1/(0.5*(Their pay grade-Your pay grade))/4)+(Do you know them?+Do you work with this person currently?+Is person within your department?+Do you have a positive working relationship?+Do they like you?)/25)+(Have you done good work for them before?+Can you get this person a job/opportunity?)/10)-(Have you done bad work for them before?+Have you beat that person out for job/opportunity?)/5)),IF(Your pay grade>Their pay grade,70+(100*(Do you know them?+Do you work with this person currently?+Is person within your department?+Do you have a positive working relationship?+Do they like you?)/25)+(Have you done good work for them before?+Can you get this person a job/opportunity?)*10)),60+(100*(Do you know them?+Do you work with this person currently?+Is person within your department?+Do you have a positive working relationship?+Do they like you?)/25)+(Have you done good work for them before?+Can you get this person a job/opportunity?)*10)-(Have you done bad work for them before?+Have you beat that person out for job/opportunity?)*10))))

Of course, that nightmarish formula is more readily understood in its natural format: a spreadsheet, so naturally I’ve provided it along with instructions:

https://moorheadfamily.net/data/Query%20Quotient.xlsx

Out of curiosity, I tested it with a recent scenario involving someone from our Legal department.  The calculator suggested a 33% chance of receiving a response, and seeing as it took 3 weeks to get any answer, this figure seems pretty accurate.  Hopefully this tool will allow you to adjust your project timelines accordingly.

–Simon

Years ago, before my employer started its regular “Great Places to Work” program, it maintained a less grandiose practice of occasionally but regularly asking employees for feedback on how it could improve.  At the time I figured this was pointless lip-service, but I dutifully responded with reasonable requests.  One of these requests was for free coffee.

I didn’t expect them to hire a barista, serving Arabica blends.  Of course, I didn’t expect them to seriously consider the request at all.  But after several years, respond they did, and by popular demand installed coffee machines.  And for a good solid month I enjoyed free coffee–nothing great, but a drinkable instant coffee blend.  Quick and effective.

Then, someone cut costs and changed the blend.  Now, I can drink some pretty awful coffee, but overnight, the coffee had turned into toxic waste.  And toxic waste is probably less bitter–you know, the glowing green kind?  Sadly, I returned to making my own.  But the years passed and the machines remained, so someone had to of been drinking it.  Upon this realization, I started more closely observing who was still getting cups of the sludge.  They all fell into a certain demographic: from Sales, tall, men, middle-aged.  I wondered why successful businessmen were less picky about the quality of their coffee.  Then, I considered my father-in-law.  He is a retired defense-contractor engineer.  He also drinks Folgers.

I wondered: is coffee quality preference inversely proportionate to income level?  To answer this question, I decided to waste time and put off auditing the emails I needed to send out.

To quantify this correlation, I needed figures.  I felt it was safe to assume that the cost of the coffee blend increases with its quality.  What I needed then, were some salary figures.  To graph the slope, I only needed two points.  The first point was easy: take the most expensive coffee I see regularly in grocery stores: $15 a bag; and the lowest income bracket, minimum wage: $15,080.  For the second point, I needed the cost of the cheapest instant coffee available (what I presumed was being used in the machines at work).  Courtesy of Amazon, I found it at $3.33 a bag.  Then, consulting the various online utilities designed to inform the masses that everyone’s underpaid, I found the average salary for an experienced Sales manager to be around $115,000.  Now I had two points.  It was time to calculate the equation.

First, I calculated the cost per ounce of each coffee.  Going off a 12-ounce bag, the expensive coffee was $1.25 and the cheap coffee was $0.28.  But, to make these number more manageable for a formula, I multiplied by 100 to use cents, creating nice whole numbers to work with: 125 and 28.

With standard algebra, we can calculate the slope with (Y2-Y1)/(X2-X1):

(28-125)/(115000-15080)=~-0.000970777, or if you want to follow significant figures, -0.00097.

Following Y=MX+B, we need B to be X0 (in this case, the baseline of minimum wage) to equal the $15 coffee mark.  But first we divide by 100 to bring the scale back down.  After doing so, B is simply calculated to be 140.  Final formula:

((Slope*Salary)+140)/100

Sadly, I could not find an online calculator that provides coffee products by cost per ounce.  Searching for one only yielded a number of self-righteous articles criticizing how much coffee costs and how stupid people are for buying Keurigs or going to coffee shops.  But I did plug some numbers into the calculator, and my own coffee preference: Peet’s, ranks approximately by cost the type of coffee I should be buying.  So once again, the math doesn’t lie:

https://moorheadfamily.net/data/coffee3.xlsx

Aqua Vitae

–Simon

There comes a time in every man’s life when he thinks: “Huh, this job sucks.  Why am I here?”  And it is indeed a very good question.  Blessed not are the proletariat masses who punctually arrive at work, only to question the work they do, and by extension, the meaning of life.  But rather than pass a joint and write poetry, I will continue my series on Quantitative Philosophy and instead enlist the field of mathematics to answer these questions.

Actually, I’m just going to calculate whether or not your job’s compensation is sufficient for its level of stress, and subtly suggest whether or not you should seek alternate employment.  How will I do this?  Why, the same way I compile data for all subjective forms of human existence: polls.

And don’t you judge me, all you MBAs out there.  In my experience, employers have carefully calculated just how little they can pay for a given job, and they do this well, otherwise we wouldn’t have minimum wage laws.  This is merely an extension of that philosophy, only calculated from the employee’s side instead.

We will start with a job’s variables that make it less desirable, or as I will translate: things which cause stress (Stress Factors).  Through discussion, the common complaints and therefore sources of job stress are:

1. Superiors
2. Suboordinates
3. Customers/Clients
4. Coworkers
5. Self (Internal stress, related to self-actualization)

Financial compensation is obviously the primary negator, but a broader perspective of that is what we do with the paycheck that negates the stress.  Therefore, we start with the weekly net income, and from this figure subtract the negators (or, negators from the negator–double negatives).  Again, using poll data, I have narrowed these variables to:

1. Weekly gross income of minimum wage (because you have to be making more than minimum wage to have disposable income, and this is a base figure for which we all weigh our financial success)
2. Weekly estimated cost of alcohol consumption (substitute your drug of choice)
3. Weekly estimated cost of luxury edibles (fine dining–a universal constant)

The assumption being made is that the minimum required amount of excess finances to achieve happiness with an average stress level of 65% at a weekly net income of $450.  This sets the baseline…or at least it did.  Minimum wage has gone up considerably since I made this calculator, so the explanation is no longer consistent with the math.  Now it appears that for the given salary, a job caps at about 25% the maximum level of stress a job could offer.  This is a pretty low level of stress.  In any case, here is the formula:

(0.14(net income – (sum of negators)))/0.5(sum of stress factors +1))

And as before, the formula is scaled, this time to range from 0-5 (5 being the ideal job), with each stress factor receiving a rating of 0-10, 10 being the most stress.  Inputting my own figures, I receive a 4.33.  Hmmm, I’m not so certain that this has scaled well with time, or if it’s entirely linear.  A job with a maximum stress level appears to only require a weekly net income of ~$585, and I would not be a stock broker for less than $60K a year.  But it does appear that I’m on version 6 of this calculator as of 1/7/16, so it may be due for an update.  Also, it doesn’t account for an area’s cost of living, so adjust the minimum wage accordingly.

In any case, give it a try and find out where you rank.  I can tell you with certainty that if you rank below a 1, scaling issues aside, your job sucks and you need to find a new one (I told you I would give a subtle suggestion).  Now stop reading this and get back to work!

https://moorheadfamily.net/data/Effort%20Quotient%20v6.xlsx

–Simon