What's in an Algorithm

What's in an algorithm?

Algorithms are at the heart of data science, and a core discipline at Strategic Machines. Algorithms are pervasive, from instrumenting the financial performance of a firm, to intepreting the intent of text messages from a customer. They range from the simple to the complex, from the superficial to the profound. Behind every function is an algorithm, informing or misleading, promoting or impeding.

Consider a simple example and a pure function. If the objective of your latest marketing campaign is to improve net unit sales of a specific product by 10%, you may have established a well-defined goal for planning the budget and other key elements of the campaign.

const goal = (n = 1.1(n))

Of course, this algorithm provides little insight into what may be otherwise an overly complex demand chain requiring much greater finesse when planning the campaign. The input 'n' may represent net unit sales for a comparable period, but what do we learn about the product with more granular data by territory, store locations, weather conditions or adjacent sales. The algorithm quickly mounts in complexity, but also lends increasing insights into an essential set of requirements for the campaign. For example, deeper analytics may indicate that a goal of 10% is too modest for a specific set of stores. The campaign strategy needs to be shaped by more granular characteristics like location, zip-code demographics, audience profiles and traffic patterns.

At Strategic Machines, we build on proven foundation models to deliver unparalled conversational capabilities, and even help with quality testing of the algorithm.