Waiting Becomes Inventory in Operations Research
Featured image: Alberto Rodríguez, via Unsplash.
When an organization wants to grow, the obvious response is usually to add more.
Hire more people. Buy more equipment.
Operations researchers and manufacturing leaders learn to look for another lever:
Reduce how long work remains inside the system.
That idea comes from one of the simplest relationships in operations research, Little’s Law. In a stable process, the amount of work sitting inside a system depends on both how quickly work enters and how long each unit stays there.
A factory producing parts quickly can still become overwhelmed if those parts spend too long waiting between stages. Inventory begins accumulating throughout the plant.
That leads to a useful way of seeing delay:
At scale, time becomes inventory.
Manufacturing makes that inventory visible. Parts are physically stacked between machines.
But many organizations accumulate less visible forms of inventory.
Consider a growing software team.
A newly hired engineer may need months to become comfortable with the codebase, development environment, architecture, release process, and unwritten conventions of the team.
During that period, the engineer is already contributing. But ramp-up also consumes another scarce resource: the attention of experienced engineers.
Someone answers questions, explains architectural history, helps with the first deployment, provides unusually detailed code reviews, and fills in information that has never been written down.
Now suppose the company wants to grow faster.
The obvious response is to hire faster.
But if experienced-engineer attention is already the limiting resource, faster hiring can make the constraint worse. More people enter the ramp-up process at the same time, increasing demand on exactly the people needed to make them productive.
There is another path to growth:
shorten the ramp-up process.
Improve the development setup. Document the architecture. Make the first deployment reproducible. Give new engineers an early task that takes them through the complete workflow. Notice which questions are repeatedly answered by senior engineers and turn that knowledge into something reusable.
Those improvements may initially take productive time away from experienced engineers. But if future hires become independent sooner, the same mentoring capacity can support a larger organization.
A company trying to accelerate growth might therefore rationally spend less effort on immediate production and more effort improving how quickly future people become productive.
The same lens applies elsewhere.
A business waiting months for customers to pay has cash tied up in a pipeline. Reducing that delay can free capital for additional growth without increasing sales.
A software team with changes waiting days for review has unfinished work accumulating in a pipeline. Shortening that wait can increase delivery capacity without adding developers.
The first approach to growth is easy to see because it adds something tangible.
The second can look like documentation, automation, process improvement, or simply removing waiting.
Sometimes the fastest way to grow is to reduce.
Sources and further reading
MIT OpenCourseWare, Lean Thinking Part II — Little’s Law
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