But why introduce a delay in the first place? Isn't faster always better? 'Science of better' does not always mean 'science of faster'. From age-old proverbs we find that in between 'haste makes waste or knee-jerk reaction' and being 'too clever by half' lies 'look before you leap'. If we view Einstein from an OR perspective: "Make things as simple as possible, but not simpler", the reason seems clearer. We must make situation-aware and contextually-optimal decisions as fast as possible, or as slow as necessary, but not faster, or slower, i.e., there exists a nonzero optimal delay for every response decision. A middle path in between a quick-and-shallow suboptimal answer, or a slow-and-unwieldy 'over-optimized' recipe. Of course, one must work hard during this delay to maximize the impact of the response, and put Parkinson's law to good use, as suggested below:
#orms methods often *delay* product response to find superior answers. Tricky to pick optimal (delay, improvement) pair :)See this old post on 'optimally delaying an apology' to maximize benefit to the recipient, or recall the best players of every sport being able to delay their response by those few milliseconds to produce moments of magic, or Gen. Eisenhower delaying the call to launch D-Day. In the same way, a good OR/analytics practitioner will instinctively seek an optimal delay. For an example of this idea within an industrial setting, read this excellent article by IBM Distinguished Engineer J. F. Puget on taxicab dispatching that he shared in response to the above tweet. Implication: If your analytics system is responding faster than necessary, then slow it down a bit to identify smarter decision options. The 'slower' version of this statement is more obvious and is a widely used elevator pitch to sell high-performance analytics and optimization tools.
— (@dualnoise) August 1, 2014
The history of the 'optimal delay' is many thousand years old, going back to the writing of the world's longest dharmic poem, the Mahabharata, which also includes within it, the Bhagavad Gita, one of the many sacred texts of Hinduism.
The story about how this epic came to be written is as follows:
Krishna Dvaipana (the Veda Vyasa) wanted a fast but error-free encoding of the epic that could be told and re-told to generations thereafter. The only feasible candidate for this task was the elephant-faced and much beloved Ganesha, the Indian god of wisdom and knowledge, and remover of obstacles. The clever Ganesha agreed to be the amanuensis for this massive project on the condition that he must never be delayed by the narrator, and must be able to complete the entire epic in ceaseless flow. Veda Vyasa accepted but had his own counter-condition: Ganesha should first grasp the meaning of what he was writing down. This resulted in a brilliant equilibrium.
Veda Vyasa composed the Mahabharata in beautiful, often dense verse that Ganesha had to decipher and comprehend even as he was writing it down without lifting the piece of his tusk that he had broken off to inscribe, from the palm leaves. If Ganesha was too slow, it would potentially give Vyasa the opportunity to increase the density and frequency of incoming verses that may overload even his divine cognitive rate. If he went too fast, he would risk violating Vyasa's constraint. Similarly, if Vyasa was too slow, he would violate Ganesha's constraint. If he went too fast, his verse would lose density and risk becoming error-prone, and of course, then Ganesha would not have to think much and perhaps write it down even faster. Imagine if you will, a Poisson arrival of verses from Vyasa divinely balanced by the exponentially distributed comprehension times of Ganesha. Writer and composer optimally delayed each other to produce the greatest integral epic filled with wisdom ever known; written ceaselessly in spell-binding Sanskrit verse, without error, and flowing ceaselessly to this day without pause.
I can think of no better way to celebrate Ganesha Chathurthi than to recall and apply this lesson in everyday life.
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