August 2020
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Photo by Jonathan Borba on Unsplash

Or, looking for data and boundary conditions

📊 Find the data

The first thing to strip out of a potential problem is its data. In the fluid mechanics example, we have several fixed variables:

  • The density and viscosity of the lower layer of saltwater
  • The width of the channel
  • The height of the channel for each layer of water
  • The volumetric flow rate of water of the upper layer
  • Customer churn is 3% per month.
  • Support calls are up 7% this quarter, and the average resolution time has increased to 3 days.

When you don’t get data for free

If you think there’s a problem but don’t have much hard evidence, hit pause. A lot of “problems” are hypotheses (generally of two flavors: if we do a, then b or x is happening, because y), informed by common sense, observation, or accumulated experience, but little data.

  • How many snow days specific cities have, on average, per year, and what is the probability of snow falling (e.g., prompting people to think of snow tires) at different times of the year
  • How many service centers are within a 10-minute radius of a given neighborhood
  • How far people are willing to travel to get their tires changes

🔒 Define the boundary condition

The next thing you need to do after identifying available or easy-to-acquire data points is to identify your boundary conditions—or constraints. Every problem has constraints, and without them, you probably won’t succeed. In fact, with them, you might thrive.

The stress at the surface of the water, at the boundary with the air, is zero (Wikipedia)

The flow velocity profile in the channel (Source, p. 9)

Scanning your problem for constraints

In the Donlands subway station example, we’d face many constraints. For example:

  • Soil conditions on the site may require remediation
  • The deadline for construction to begin to qualify for provincial funding


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