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28 Apr

But why, Mr. Parkinson?

The contemporary obsession with productivity, coupled with the demonization of sloth has manifested in a cultural movement, one that defaults to framing almost everything in terms of the units of capitalism, i.e. work and money.

Money is a system to capture value and is mediated through work. Work is meant to represent a system through which value is created, distributed, and ultimately exchanged. But what is work? How do you measure it?

Cyril Northcote Parkinson, the granddaddy of satirical workplace humor, took to penning his thoughts on the bureaucratization of the British Navy and made a slew of observations about the nature of work in an article for The Economist in 1955.

His ideas went through the compressional effects of time and today, we only remember the first line of that article, which is:

“It is a commonplace observation that work expands so as to fill the time available for its completion.”

More popularly known as Parkinson's Law.Thousands of hours of video and reams of articles have been produced to convince productivity–maximizers about the life–changing effects of this law. Most of it comes down to a simple, actionable, but ultimately useless platitude: set shorter deadlines so you don't waste time.

Implicit in this recommendation is that you, as a person, are capable of estimating the amount of time it takes to complete a task. It also assumes that you can better at this with time and can actively extend this to other facets of your life so you can get more done.

Faulty assumptions notwithstanding, why does work even expand in relation to the time available in the first place? Understanding this question could yield more insights into the nature of work than merely forcing shorter deadlines.

When work becomes exclusively noetic, productivity starts to become non–linear.

When I say non–linear, I mean that it wouldn't make sense to look at it in two–dimensional terms. The usual time versus productivity framing is not useful. Part of the reason why this isn’t useful is because no one even seems to agree on what knowledge work is.Richard Florida’s definition, albeit quite narrow and defined, offers a good starting point:

“The direct manipulation of symbols to create an original knowledge product, or to add obvious value to an existing one.”

Even if we choose to work with a rudimentary definition like this, one thing becomes clear: there are no guardrails and structure is all but non-existent. A good chunk of a knowledge worker’s time is devoted to assembling information and utilizing their past experiences and specific skills (along with dollops of creativity) to produce intellectual capital.

When this becomes the dominant method of value creation, mapping input to output becomes a tedious affair. Take the example of China, and its evolution over the years. China has long been viewed as the world’s sweatshop, but never a major technological innovator (as evidenced by exports of complex goods). Take a look at this chart of China’s Auto exports:

Multiple decades of painstaking engineering efforts seemingly yielded no effort, until suddenly it takes off into the stratosphere. You can’t even call this a hockey stick curve, it’s more like the base of a mountain.

There are numerous examples in software, where hypergrowth is the hallowed phenomenon that dots many an investor’s minds. Barring truly innovative software (like ChatGPT) for instance, a well-architected convenience application can work in much the same way. Here’s a graph of GO-JEK’s completed orders over a 1-year period:

Over a 3-year period (2015 to 2018), GO-JEK managed to scale from 15,000 orders a month to over 100M per month, all while its engineering team never crossed the 300. As of early 2018, there was 1 engineer for 600,000 monthly orders. To put that in perspective, that’s a 6666x growth in completed orders, <20x growth in the number of engineers.

These examples are the stuff of dreams (and nightmares) and illustrate how the “direct manipulation of symbols” can produce record-breaking efforts in some cases, and absolute hogwash in others.

Now I don’t claim to know the secrets that drive growth patterns of this sort, but I’m reasonably certain that it goes beyond setting ‘aggressive deadlines’. Any complex endeavor that involves multiple moving parts requires the leaders to meditate deeply on what to focus efforts on, and how to go about executing while mitigating unnecessary forms of complexity.

More often than not, the only variable that can affect this directly is the number of people involved in any given project. Be it politics, software development, hardware engineering, or business consulting, the adage “too many cooks spoil the broth” holds true.

When the medium you work in is abstract, complexity is inherent to your work. All knowledge work is ultimately rooted in the mind. In the absence of direct physical representations, there are a lot of unknown unknowns that you simply can’t account for. Consequently, knowledge work is thus beholden to a strange mix of objective and subjective measures that make it incredibly complicated to measure.

Abstraction ad infinitum

A lot of success in the contemporary internet economy can be boiled down to learning how to employ abstractions in thinking. This doesn't have to be limited to software, it works in much the same way for any sufficiently complex service role — be it vanilla business consulting, marketing, sales, or organizational design.

Let's take the example of a simple deliverable — a 5,000-word white paper whose purpose is to market an IT services product. Normally, these things are outsourced to agencies, who in turn outsource them to freelancers, many of whom are young twenty–somethings with no inkling of the IT services industry.

When you are two layers away from the actual source of work, you are effectively driving blind. It becomes incredibly difficult to know what to write, how to go about conducting research, and what level of detail to exercise. All you have to go by are representations, most of which are echoes of projects from times past. It also doesn't help that the project managers who are put in charge of such endeavors have little to no experience with the craft of writing.

Young writer–marketers at this point work with a few incentives. The first is that they want to do a 'good job' so they can keep getting more jobs (and ultimately more money). The second is that they want to minimize the amount of time it takes to do a 'good job' so they can maximize their hourly rates.

What is a 'good job'? Who defines the benchmarks against which effectiveness is measured? Industry insiders know that most of the revenue that IT firms make comes from repeat customers, with some estimates pegging this number to be as high as 97%.

If only 3% comes from new customers, the marketing teams in these firms effectively have nothing to do. Unfortunately for them, they are still held to the same 40–hour workweek pattern that requires them to show up day after day and produce “results” so they can justify their salaries, both to themselves and to their employers.

On one hand, you have career marketers with very little work, and on the other, you have fresh–faced writers with no prior knowledge of the kind of work that they are expected to do. These writers are usually not trained in the discipline, they are expected to be effective from day one and those that don't “hit the ground running” don't get more work.

At this point, there is a subtle form of existential dread that is constantly looming around both writers and marketers. If their work is ultimately nothing more than an embellishment, how are they to work seriously, with an aim to improve their craft and effectiveness?

This is where knowledge workers choose to operate at levels of abstraction that are completely unnecessary, save for portraying the illusion of “hard work.”

In the absence of concrete feedback loops, the writer initially devotes a lot of time to reading voluminous reports and dense research papers to produce a spectacular whitepaper. The full–time marketer on the other hand begins to loop in members from senior management and the engineering team to get “expert approval” on these seemingly complex and important topics.

Over time, the modus operandi of both these groups can be modeled as a direct function of the arbitrary deadlines that come from above the pyramid. Shorter deadlines will lead to the writer half–arsing their research and writing process. For the marketer, it'll mean fewer meetings and people involved in the whole cycle.

Saying no to Individuality

Instances like these make me surmise that work can almost never be standardized if it has even the tiniest human component involved in the execution. The work we do is an extension of our own selves, and each of us is incredibly unique in the way we think, operate, and handle tasks given to us.

Operating within the prevailing economic machinery means that these individual quirks are often deliberately sacrificed in favor of predictability.

Work becomes amorphous because the people undertaking them are dynamic. These very people tend to keep oscillating across a wide array of emotions, moods, and health, which in turn affects the way they perform tasks. Even something as simple as stamping envelopes can be done in wildly different ways.

Much has been written about combating inefficiency and low productivity, but the lack of understanding of the nature of work causes most people, especially managers to commit egregious errors in delegating and managing responsibilities.

Work takes up the amount of time allotted because few understand how much to do, what to add, what to subtract, and where to stop. No amount of theorizing or pontificating can change this. It's an unintended side effect of taking a concept like comparative advantage to its logical conclusion.

The best we can do is recognize this and model our workflows accordingly. Not setting aggressive deadlines and weeding out non-performers because they “didn’t make the cut.” That’s a one-way ticket to corporate purgatory, and not many companies can survive that.

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