The idea came from the wrong field.
That was why it worked.
Years ago, I was working on a preschool master-planning problem for Los Angeles Universal Preschool involving a large and diverse group of stakeholders. There were questions about locations, services, funding, tradeoffs, access, feasibility, and what different communities needed.
We did not have a shortage of opinions.
We had a problem turning them into a decision.
The disagreement was not irrational. It was difficult precisely because many of the competing priorities were legitimate. Teacher qualifications mattered. The length of the preschool day mattered. Which children to serve first mattered. Geography mattered. The pace of expansion mattered. Cost mattered.
Discussed one at a time, almost every feature sounded essential. But a real system could not maximize every desirable feature simultaneously.
More of one thing could mean less capacity somewhere else. Faster expansion could create different tradeoffs from slower expansion.
A configuration that looked attractive from one perspective could look very different once cost, access, or feasibility entered the picture.
The problem was not a lack of values. It was that values had to become choices.
The discussion could easily have stayed inside the language of education and public policy. But another problem kept bothering me.
How do you learn what people actually value when they want several things at once, but cannot have every combination?
Around that period, I was taking a UCLA Anderson marketing course that included product configuration, preference tradeoffs, and conjoint analysis. The LAUP planning problem was already active in my mind. I remember the correspondence becoming hard to ignore.
In the classroom, people were choosing among bundles of product attributes. In the planning work, stakeholders were choosing among bundles of program attributes. The nouns were completely different. The decision structure was not.
That was the moment the outside dot became available for use.
Conjoint analysis is used to understand how people make tradeoffs among bundles of attributes. A customer might prefer one feature, another price, another configuration.
The point is not that public policy is a product.
It is that both settings can contain a similar decision structure: multiple alternatives, multiple attributes, constrained choices, and preferences that become clearer when tradeoffs are made visible.
That distinction mattered.
The field was different.
The structure of the problem was similar.
We adapted the idea. Public preschool planning brought obligations that consumer research did not: equity, geography, finance, public purpose, feasibility, and service responsibilities. So we could not simply copy a marketing method and declare the problem solved.
Some of the planning became clearest when we stopped adding words and made the tradeoffs visible.
I remember plotting two cumulative lines over time: revenue and expenditure, or burn. Different pre-K configurations and ramp schedules changed the shape of those lines. A configuration that consumed limited resources too quickly became visible before anyone had to work through every assumption underneath it.
We also mapped the gap between preschool supply and demand by ZIP code. Supply came from registered providers. Demand came from census information about preschool-age children and changed depending on whether the system was designed to serve four-year-olds, five-year-olds, or both.
The map turned an abstract planning question into geography.
The numbers had not become more true.
The pattern had become easier to see.
Years later, when I revisited that work with Dr. Karen Hill Scott, she described something I had not named at the time.
She remembered the work as a meeting of the hard and the soft: numbers, mapping, mechanics, and precision woven together with a human purpose.
Her memory is one perspective, not the whole historical record, but the description stayed with me. [7]
The deeper transfer was not only from marketing into preschool planning. It was also from precision into purpose. The method had to become more exact without becoming less human. In public service, what we choose to measure—and what we refuse to reduce to a number—matters as much as the technique.
That was where the analogy stopped.
We had to keep what transferred and rebuild what did not.