Step 1: Determine the number of fueling events in the US

(Blue Text = Input)

(Blue Text = Output)

We've determined that there are approximately 10.7 billion fill ups each year.

Step 2: Determine HOW MUCH GAS IS WASTED DURING EACH FUELING EVENT

Finding an answer range is best practice :)

A few drops are 1-2.5 grams of fuel. A unit conversion shows us that fuel is 317 - 847 millionths of a gallon wasted during each fueling event.

Step 3: Determine The size of the problem in dollars

("SWAG" = Scientific Wild Ass Guess)

Multiplying that by the price of a gallon of gas suggests that the annual problem size is between $10-30 million. If 10% of that value were captured, it would yield an attainable market value of $1-3 million... not a huge opportunity in my opinion.

But maybe the problem the problem impacts some players more than others. Let's explore that:

Step 4a: determine the problem distribution across largest players

Determine market share

Step 4b: determine the problem distribution by looking at market share

Relate back to dollars

So we see that this problem is relatively insignificant, even to the biggest players - BP's market cap is $102B, so they probably don't lose too much sleep over $7M.

Step 5: number of pumps in the us

For practice, let's keep going. If we were to create a solution for each individual pump, how many units could we sell and at what price? 

Step 6: Price per unit

Given that there are 115,000 gas stations in the US, we can see that each year between 30 and 79 gallons of fuel are wasted at each station each year, which is valued at $103 - $275.
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Each station has an average of 8-12 fuel pumps, so the solution we develop needs to have a piece price of $8 - $34 (assuming a payback period of 1 year).

Step 7: look at sensitivies

Excel's Data Tables are an excellent tool to look at the impact of different inputs.

In this case, I wanted to study how the piece price of our solution is impacted by the average number of gas pumps at a station (across the top) versus the payback period (across the side).

We can study it from the perspective of both the minimum and maximum cases. A best case for hardware is a payback period of less than 2 years, which is why those values are highlighted in red.

Unsurprisingly, as the payback period increases, so too does the piece price we can afford.
Conversely, as the average number of pumps increases, the piece price falls.

Ultimately, we see that a piece price for our solution should be less than $55 at the very most for us to just break even.

Possible? Yes.
Likely? Maybe not.