For every initiative that a business takes on, there is an opportunity potential and a cost—the cost of not doing something else. But how do you tangibly determine the size of an opportunity?


Opportunity sizing is a method that data scientists can use to quantify the potential impact of an initiative ahead of making the decision to invest in it. Although businesses attempt to prioritize initiatives, they rarely do the math to assess the opportunity, relying instead on intuition-driven decision making. While this type of decision making does have its place in business, it also runs the risk of being easily swayed by a number of subtle biases, such as information available, confirmation bias, or our intrinsic desire to pattern-match a new decision to our prior experience.


At Shopify, our data scientists use opportunity sizing to help our product and business leaders make sure that we’re investing our efforts in the most impactful initiatives. This method enables us to be intentional when checking and discussing the assumptions we have about where we can invest our efforts.


Here’s how we think about opportunity sizing.


Opportunity sizing is more than just a tool for numerical reasoning, it’s a framework businesses can use to have a principled conversation about the impact of their efforts.


An example of opportunity sizing could look like the following equation: if we build feature X, we will acquire MM (+/- delta) new active users in T timeframe under DD assumptions.


So how do we calculate this equation? Well, first things first, although the timeframe for opportun...


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