I liked math; solving equations was kind of fun, not so much the struggle to figure it out but rather the high when I got it. I am talking about relatively unsophisticated math and statistics. I enjoyed statistics throughout graduate school courses for my advanced degrees. But for my PhD dissertation, I went all qualitative. Not only did I learn the beauty of qualitative methods, I came to respect their nuances and challenges. If I may brag, my one and only (qualitative) methodology paper won me a prestigious award.
There is a widespread assumption that quantitative descriptions are more rigorous and “hard” than are qualitative descriptions, which are often referred to as “soft.” Amusingly, qualitative descriptions are seldom referred to as “easy,” and many of us have come to realize that understanding math is much easier than grasping the moving targets of human intentions and behavior. The bottom line is that understanding life requires both quantitative and qualitative analysis.
But organizations are obsessed with “hard” numbers: quantifiable indices, scales, measurements, volumes, etc. Organizations pay less attention to the “soft” aspects of organizational behavior: relationships, emotions, nurturing, empathy, sympathy, understanding, non-verbal communication, thinking, reflections, etc. It is as if the “soft” aspects are dismissed as “easy” by organizations, despite our individual realization that they are not and that managers-at-large keep messing up in these aspects (thereby keeping Dilbert in syndication).
One of the valuable principles of social statistics is that while the aggregate information is useful and important, it can not help us predict an individual behavior. We can predict that at 5PM on a 5-lane highway in California, there is a very high probability of heavy traffic or a traffic jam, and that most people would be impatient and annoyed. But we cannot tell how each of them will react to this highly probable event. Many will simply be resigned to the inevitable, some may be swearing and trying to weave in and out of lanes, some may switch radio stations constantly, and one or two may zen into contemplation of life. So, numbers can inform but they only paint a limited picture, and it’s a picture of probability.
Of course, organizations do need numbers for guidelines, for aspects such as employees’ performance, promotions, and salaries. But even here, numbers do not help a manager deal with frustrations over budget shortfalls or when one of her employees can only get a promotion if there is no salary increase. Similarly frustrating is an institutional cap on promotions to less than 1% of the workforce per year, while at the same time the institution drives its workers to develop themselves according to at least 3 promotions per 30-year career. (Yes, the math is easy; at this developmental rate 10% of the workforce should be promoted per year. Every year.) And if promotion caps weren’t enough to destroy organizational credibility, many institutions go on to adopt the forced curve in evaluating performance, thereby setting up an unhealthy competitive environment and pitting against each other people who should be, and would like to be, colleagues. (Please refer to my earlier entry, “Acting on Knowledge,” posted on 10/31/10, for a more in-depth analysis of the harm of competitive environments.) I absolutely detested this practice when I was teaching. Some semesters, I felt that more than half of my students were performing below average expectations and I had to bump up the grades for some in order to meet the curve requirement. One semester, I rebelled, as I had an unusually diligent and creative group of students; it would have been unconscionable for me to artificially lower some students’ grades just to meet the idiotic forced-curve requirement. Fortunately my supervisor was able to back me up.
Numbers alone carry little meaning; not only do we need to learn how to interpret the social meaning attached to the numbers, but more importantly, we need to be mindful about whether the questions behind these numbers are pertinent, relevant, central, and adequate.
We are easily impressed by big numbers, and especially in money, accounting, or economic growth. According to the New York Times op-ed columnist, Bob Herbert (3/25/2011), GE pulled in $14.2 billion in profits last year, without having to pay one penny in tax. Impressive, isn’t it? Both the profit and the zero tax payment; an enormous distance between the poles. The reporter in the original article for the Times wrote, “Its extraordinary success is based on an aggressive strategy that mixes fierce lobbying for tax breaks and innovative accounting that enables it to concentrate its profits offshore.” Based on what measure is this deemed “success?” For GE, certainly, but for the whole economy, especially for this country at this juncture? Aside from politics, what has GE contributed exactly? This conglomerate is definitely huge, but has it created anything? Especially in innovation and creativity?
That was an example on a colossal scale. A much smaller scale personal experience: This week I had a major quarrel with a rental DVD disc, an experience I am sure shared by many of you. (By the way, do people skate on them? or use them as Frisbees?) So, finally I talked to a Netflix agent. He was pleasant enough, but of course, there weren’t any long-term solutions. (Sidebar: To the potential competitors out there: if you can figure out how to solve this problem, you may get a lion’s share of the DVD rental market.) But we got an “extra” DVD allotment, whoopee! I then consented to take a short survey after our conversation; it was a one-question survey asking me if I was satisfied with the service. Seriously? I was absolutely flummoxed by how to choose the number on a scale of 1 to 3. And what can Netflix do with this data? I do like the concept behind Netflix; they are very good with the distribution system, and the occasions that I have talked to real agents, they were pleasant and decent. BUT… I think Netflix would be much better informed if they spend a little more time (quantitative) actually talking to a fewer customers (quantitative) for in-depth understanding (qualitative) than this 3-point-one-question-survey (quantitative) that’s essentially useless.
“Communications problem” is a lovely catch-all label for all kinds of organizational ills. Most of the time, the so-called communications “problem” is just a surface manifestation of deeper and knottier problems. An organization survey asks employees if they understand certain policies, without (probably deliberately) giving the employees opportunity to assess the quality of these policies. It is fairly typical of top management to assume that policy making is strictly their purview; they then convey these policies downward. When encountering some resistance, their first reaction is usually “we need to better communicate these policies,” and usually by reiterating these same policies, LOUDER and more slowly. A colleague of mine once asked some engineers “what do these specifications mean?” To which the lead engineer literally read back the specifications, very s-l-o-w-l-y! My exasperated colleague responded, “I know what they say, but what do they mean?” Only then could the real conversation begin.
Organizations frequently use employee surveys for feedback, but the wording of the survey questions is usually about conveying the what, not the why or how. And it rarely allows employees to respond to the validity and quality of the specific policies. This is a colossally screwed-up logic. It’s as if organizations are saying, “I am going to hire only people who don’t want to think for themselves.” ALL organizations claim to want to hire the brightest. So, why when the management encounters push-back on new decisions, rules, or policies, they assume it’s because employees haven’t understood the policies or rules? And then, they’ll “explain” these offending new rules with new training that repeats them, slowly and loudly. It’s maddening; it’s insulting; it’s stupid.
I can be very patient with people who genuinely don’t understand or can’t quickly grasp certain lessons. It’s willful ignorance and stupidity, compounded by arrogance, that drive me batty. Our organizations, and their senior managers, seem to have confused authority for authenticity. The playwright, Robert Bolt, wrote eloquently in “A Man For All Seasons,” in the voice of Sir Thomas More (formerly the Lord Chancellor of England for Henry VIII),
“Some men think the Earth is round, others think it flat; it is a matter capable of question. But if it is flat, will the King’s command make it round? And if it is round, will the King’s command flatten it?”
Numbers can be useful and powerful, but without a sense of context, or sensible judgment, we can easily get mislead by authorities who may speak loudly but with little authenticity and no credibility.
Finally, zero data or the absence of data can carry considerable meaning. Zero tax paid by a giant conglomerate speaks volumes about our system. Sherlock Holmes famously drew great significance from the observation that the dog didn’t bark at night. Context, context. Lewis Thomas said in “The Lives of a Cell,”
“…a good way to tell how the [scientific] work is going is to listen in the corridors. If you hear the word, ‘impossible!’ spoken as an expletive, followed by laughter, you will know that someone’s orderly research plan is coming along nicely.”
Challenge to senior managers of R&D organizations: Quantify this! And think of the potential calamity if the same word “impossible” was uttered on the stock exchange floor or in the courtroom.
Until we realize and materialize more possibilities,
Staying Sane and Charging Ahead
Direct Contact: firstname.lastname@example.org
copyright taso100 © 2010 – 2015 all rights reserved: no photos or content may be reproduced without prior written consent