My current role is focused on a construction scheduling optimization problem. The source of this idea comes from Generative Design.

From Wikipedia:

Generative design is an iterative design process that involves a program generating a number of outputs that meet certain constraints, allowing a designer to fine tune the feasible region by selecting specific output, or changing input values, ranges and distribution (parametricity).

In generative design, the designer(s) use a software program to generate many designs. Since design is a labor intensive process, requiring a lot of creativity and problem solving, using a software program allows designers to create more options than they would be able to by hand.

In generative design, constraints and rules are used as inputs, allowing a designer to explore a feasible region for designs, but without straying outside the feasible regions. A feasible region is often also referred to as search space.

The constraints and rules that are used as input to the generative design act as borders or boundaries of the search space. I often explain this in terms of “If you want to build a 3 story building, having a program generate designs with 6 stories is not very useful.”

Through DevOps, I came across Ron Westrum, a sociologist who studies how organizations work. He is the author of the Sidewinder book, about the United States Naval Air Weapons research facility that created the sidewinder missile. In the Westrum Organizational Typology, he talks about generative organizations.

Generative organizations tend to be performance oriented and focused on a mission. Everything, including how information flows through the organization, are performance-oriented, with the ultimate goal being to achieve the mission. Generative culture predicts high performance in the areas of organizational performance in technology, and is correlated with above average performance in terms of software delivery.

It occurred to me that good business outcomes, including frameworks like Objectives and Key Results, when combined with metrics and measurement allow for a similar model at the business level. When you have an objective or goal set, and some way to define success (or failure), you allow the resources in your organization to generate solutions to meet the objective. The “design” is the goal you are trying to achieve, and the “constraints” are the metrics you put in place to measure success.

By creating an organization that works through experimentation and measures how that experimentation performs against a target metric, you allow the organizational resources to generate solutions within a feasible region for the business outcome you are looking for.