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Gregory Taketa

Gregory Taketa

Gregory Taketa is the Data Decanter, serving refined, well-breathed data analysis while keeping out the sediments.

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21st Century Discrimination

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From time immemorial, we have witnessed the battles of the sexes and the battles of the hues.

In the 21st Century, a new –ism emerges: the Battle of the Q’s.

Qualitative or Quantitative? EQ or IQ? Paper or Plastic?

People often ask me, “Gregory, you have a Bachelor’s degree in Comparative Literature from [the University of California] Berkeley, correct?”

I respond in the affirmative.

“Then tell me,” they continue. “How could you do so well at data analysis for the MBA at Santa Clara University?” [I have a general MBA but mostly excelled at analytics].

For those who (understandably) cannot read tones from a text (a facet of a Literature major), their tone is quite skeptical. My current tone is livid.

You might guess my source of fury lies within these:

  • Anyone who knows anything about Cal (my beloved undergrad alma mater) knows that being admitted in the year 2000 required an insane amount of well-roundedness. My then pot belly aside, both integrating literary tropes and integrating continuous functions were a must.
  • Cal and my teachers’ assessments were not alone. I have consistently scored highly in both Q’s across the SAT, ACT, GRE (slacked off slightly then), and the GMAT (if you’re a Type A personality, my scores are published on my LinkedIn profile). The metrics are on my side.
  • As a data analyst, my personal mission is to dispel the confusion between “because of” and “in spite of.” My critical reading and free-fall thinking leveraged me above most rote-thinking engineers at their own game. Fields can be pie-expanding rather than pie-slicing.

Mental Segregation is as Ignorant as any Other Segregation

The belief that one can only be good at 1 or 2 things is completely backwards. Yes, we do learn some fields faster than others, and tradeoffs exist. However, polymaths exist, too. Centuries ago, the Greek word phusis (from which we have “physics”) meant “nature” without any distinction between mechanical nature or human nature. The word dilettante, now considered pejorative (it is synonymous with “amateur”), was once considered classy because only the wealthy could afford to acquire tutelage in multiple fields while most folk learned 1 trade through apprenticeship.

The tendency to pigeonhole a person’s skill sets not only displays empirical ignorance but also reveals a self-weakness. In psychology, there is a concept called projection: “If I can’t do it, I assume by default that you cannot, either.” I find that those who narrowly categorize others might be very parochial in terms of their own self-efficacy.

Mental Segregation Leads to Real Segregation, Even by Gender and Race

  • Kobe Bryant and many African-Americans are above-average polyglots. Shall we assume by default they must be bad at math? Ridiculous! What genetic argument supports that? Sickle-cell anemia is one thing; Mathanemia is another.
  • Women have proven excellent at humanities and historically have not outperformed men at quantitative fields until recently, some think. Ridiculous! Ada Lovelace (a woman) wrote the first computing code in 1842.
  • Men possess the assertive upbringing needed to make effective salespeople. Ridiculous! Women comprise the majority of buyers today! A savvy manager should hire those who best win a female buyer, possibly women? Most of my past clients to date were women (in a theoretically male-dominated market, mind you), and I don’t think I won them over by sheer sex appeal…
  • “Asian-Americans belong in IT or Finance.” Ridiculous! Jack Ma, founder of Alibaba Group and now the richest man in China (granted, he’s not Asian-American, but…) was an English major and later English teacher. He later learned business skills and created his empire. Up to 2010, he never wrote a line of code. Now if someone in so-called restrictive China could make that kind of career, how much more an Asian-American in the “land of the free!”

We have to stop believing that a member of any so-called faction can only be good at one thing and that excelling in one field necessarily crowds out another.

Glass Ceilings, Glass Walls, and Now, Glass Desks

I’ll assume that you already know what a glass ceiling is (and not that your expertise elsewhere has prevented you from knowing this term).

In more recent years, business experts including famous consultant Alan Weiss (i.e. author of Million Dollar Consulting famous) observed that “glass walls” were a much greater threat. In a 2011 article in Human Resource Executive Online, Weiss writes that women and minorities have been placed into HR and “interstitial” departments as a mere guise of diversity, since management is reluctant to represent them in more central or frontline roles. Although NWONMs (Nonwhite Or Nonmales) can be promoted upwards to VP of HR, the honor is as utile as Robert Frost’s honorary doctorates (HR execs rarely ever become CEOs at Fortune 500 companies). Given Weiss’ long history of being very harsh (and very accurate) about HR, it means something when an HR publication actually publishes this.

I think we face a new problem with Glass Desks, with which we believe we are free to walk about a room but are actually compelled to sit and handle a specific task-set.

Shattering the Glass Desks

  • Only engineers should be involved in design? Have we learned nothing from Steve Jobs?
  • Extensive auto industry experience needed for success in Detroit? Alan Mulally, recently retired CEO of Ford, came from a lifetime at Boeing only several years prior. In spite of not knowing how to make the hottest cars himself, his leadership in the field was par for the course (in his tenure, Ford alone of the US major auto makers avoided the government bailout fund).
  • Patricia Fripp, the world’s greatest authority on public speaking, started out as a hairstylist. Speaking was originally a peripheral opportunity to promote business until she found both passion and excellence at the National Speakers Association and became its first female President.

(Over)specialization is the hallmark of a mature (old) company. Startups (young) require many hats for each person. While tradition says that a startup ceases to be a startup when it is acquired, I believe that startup ceases to be when its members ossify and “fuse their ends” (close bone growth) into departments and lose that cross-functional flavor.

Google is now the #1 brand in the world (yes, someone had to finally beat Coca-Cola). Google is also considered “amorphous.” Coincidence? I think not. It has no bone growth end. It is not calcified (yet). There is likely more freeflow than we think.

We need Mental Integration, not Mental Segregation. Scientists have recently dispelled the utter BS we call “left-brain / right-brain.” We have 1 brain and do not function with a split personality.


Weight Loss (Regression – Cumulative, Lag Variables)

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A fictional case study by Gregory Taketa. For non-data Managers, this case illustrates that your analysts will not be able to solve anything as complicated as weight loss using typical linear regression methods. Regression practitioners can use a MS Excel Data Set to approach this problem by transforming the variables with respect to growth and time.

I’m sure you or somebody you know has an interest in a healthier diet or lifestyle (I’ve lost 25 lbs. in 19 months by the time of this writing).

A friend of mine has a fantastic web site for those of you who are interested in low-carb recipes:

This site has many visitors, and you gotta visit at least once just for the clever name!

Weight Lifting

As you know, weight lifting is very helpful for weight loss because an increase in muscle mass, all else equal, yields higher fat burn. This burn happens even when you are not actively exercising, so in the diet world, this is comparable to passive income!

The Case: Estimating the Impact of Weight-Lifting

Our subject weighs 200 lbs. at the start of a diet. At the end of each week, he marks his weight and whether he did a diligent amount of weight-lifting (according to his health advisor) that week. As typical of any binary (dummy) variable, “1” indicates “yes,” and a “0” indicates “no.”

Although many other variables, including calorie intake versus metabolic requirements, influence body weight, we will assume for simplicity that these variables have remained fixed.

Key Case Facts

  • For the first 8 weeks, our subject has lifted weights but notices no weight loss.
  • After the 8th week, he gives up on lifting weights (he perceived no weight loss earlier).
  • He exhibits some weight loss from weeks 9-16. This is because his gain in muscle mass takes time, about 8 weeks in this case.* He does not know about this.

*Disclaimer: I am not a fitness expert of any sort, and this case is simplified for the purpose of quick practice. I do not have factual evidence and do not suggest that 8 weeks is required to develop muscle mass.

Did the weight-lifting help our subject lose weight? How could you demonstrate it? What was the rate of weight loss for the given effort?

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Eis Igian!


What to Stop – When Coaches Trump Analysts

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“Half the leaders I meet don’t need to learn what to do. They need to learn what to stop.”

-Peter F. Drucker

Chris, a sales representative, asks you for advice on how he can close higher revenues for the rest of the year. He sells health food and exercise equipment. He is also quite portly (don’t ask how he was hired – long story).

As an analyst, you believe that prospects would more likely buy from a healthy sales rep, all else equal. Your market research data also indicate that Chris has not yet done sales calls with a few high opportunity prospects in his territory because the decision-makers have tough spec requirements. Tailoring the presentation materials and offerings would require some new skills on Chris’ part before he visits them.

Do you, between 2 mutually exclusive options, choose to:

A) Tell Chris he needs to learn how to integrate these new specs and concerns into his sales presentation. The time investment is 100 hours and should get $30,000 Net Present Value (the higher, the better) from selling to these big buyers.


B) Tell Chris to stop eating so much and exercise. The time investment is 100 hours and should get $30,000 Net Present Value from higher closing rates with all buyers.

If you are an analyst, you probably picked A. If you picked B, I wonder how likely you’d actually tell someone like Chris that in real life!

Why Pick A?

I have rigged both options so that their economic costs and benefits are the same. Some of you may lean toward A because it makes you “sound smarter.” I think there’s a much bigger driver:

Telling people what to do seems positive and analytical (Do This), and telling people what to stop seems negative and confrontational (Stop That).

The advisor, whether average or absent-minded, has an incentive to tell people to “do more/new” because it might not hurt the ego. To tell people to stop means to negate prior decisions and ego, “I’ve been doing this for years. Are you telling me I don’t know how to run my life?!”

“The default response is never improvement but inertia.”

-Marshall Goldsmith, Mojo

WTD is Analytical. WTS is Attitude

We both know deep down according to stakeholder theory (i.e. being a respectful human being) that Option B is the right choice for Chris. His long-term health is an important peripheral (if not central) benefit. But since our own egos (or fears) get in the way, we have to stop being analysts here and start thinking like coaches (or giving Chris a referral to one).

360-degree Feedback Isn’t Crop Circles

One problem with being an analyst is that:

  1. You’re usually the only advisor (will Chris even accept my feedback?) OR
  2. If there are multiple analyst opinions, they are given in series, not in parallel (if I tell the truth, will the next person agree with me, or will the next person withhold to flatter, making me look bad?).

360-degree feedback’s benefits rely not so much on space (all key stakeholders around) but time (simultaneous, aggregated feedback requires anonymity to promote truth-telling). Chris could potentially knock down one critic at a time, but knocking down dozens of people at the same time is not so likely (such is the power of normative pressure).

Here, a coach employs confidential feedback from multiple stakeholders to inform Chris about his weight problem and the benefits of changing. Once Chris has buy-in, he can begin his diet.

Sometimes in order to help the most, we have to stop thinking like analysts (the power of information) and think like coaches (the power of key people).