The serendipity algorithm

This is an excerpt of the original article. It was written for the March-April 2021 edition of Supply Chain Management Review. The full article is available to current subscribers.

March-April 2021

Last night, my wife and I shared a socially distanced bonfire with a few friends. One was a retired physician who is spearheading the vaccination effort in the small New Hampshire city where I live. New Hampshire has had its challenges getting needles into arms like everywhere else, but it seems as if we’re breaking through the log jam. For example, between week 1 and week 3, they’ve tripled the number of people they can vaccinate in a day, and they’ve expanded from five days a week to seven days a week. At least for now, there has not been a shortage of vaccines. I know there is a long way to go, but you can feel it picking up speed. Call me…

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ser·en·dip·i·ty /,ser n’dip de/ - The occurrence and development of events by chance in a happy or beneficial way. “a fortunate stroke of serendipity”

The intersection between the demand creation (R&D, marketing and sales) and demand fulfillment (sourcing, production and logistics operations) has long been the source of variability and uncertainty in planning and execution. Operations planning accuracy has long been the result of chance and art rather than of science. While sales & operations planning (S&OP) and integrated business planning (IBP) processes seek to reduce the dependence on serendipity, or luck, to improve planning accuracy, very few operations managers rely on their output when making daily execution decisions. My colleague, Rich Sherman, likes to say: “Forecasts that rely solely on historical data most often produce hysterical results.” Planning focused on history does not account for marketing’s objective and initiatives to cause history to change.

Harmonizing planning and execution with AI Online sellers, retailers and, increasingly, B2B vendors employ “offering analytics” to determine the sales offerings that will most cost-effectively drive sales performance above past performance. In this context, the sales offering consists of the core offering (the primary product or primary service) and the extended offering, including fulfillment, warranties, pricing, promotions, payment terms and other services. Offering analytics techniques include the following:

Attribute analysis. Attribute analysis determines customer preference based on product and offering attributes such as color, price point and application.

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