Constrain on speed, optimize for cost

Ecommerce fulfillment is ultimately a collection of decisions being made. Some are made simultaneously while others are made sequentially. Almost all are logical decisions.

If you want to improve your ecommerce fulfillment process, you need to make better decisions.

But what constitutes a "better" decision?

First, at Amazon, we had a strategy centered around creating operating rules. If a few rules could be normalized across all decisions, it would be easy for everyone to make the right decision. For example, if the rule was "Don't spend more than $X" then it was easy to make the "right" decision by never spending more than $X.

While that could be the "right" decision, is it the best decision?

Amazon is famous for the principle "Focus on the Customer" which is how we determined if decisions were good decisions. But that's a difficult thing to measure and manage. How does someone know that a decision being made is right for the customer? How do we know if results could be better?

Well, for operations to determine the best decision for the customer, we needed something measurable that mattered to the customer. The two best quantitative customer desires are speed and cost. Consumers want their orders quickly and cheaply.

This led us to create a simple rule which virtually all fulfillment decisions flowed through at Amazon.

Constrain on speed, optimize for cost.

One of the most important — and overlooked — tools available to operations is the act of imposing constraints. Constraints are a beautiful thing because they force objective decisions. 

With ecommerce fulfillment, constraining on speed makes the most sense.

Since customers either want things (a) quickly or (b) at a precise time, there is almost always a time constraint to fulfilling an order. A date is picked, or promised, to which all subsequent decisions should be made against. This explains the first definition of what is a "better" decision: If a fulfillment process is focused on ensuring the time constraint is met, then it's a better decision.

Secondly, since customers want their orders cheaply, optimizing for cost became the second half of the rule. It was not good enough to simply meet a promise. The promise needed to be met profitably.

While constraining for speed meant binary decisions (either the decision helped meet the promise or it didn't), optimizing for cost was a sliding scale. The goal was to continuously improve margin. Every little innovation or win helped.

In the end, if a decision adhered to the speed constraint while also found ways to improve margin, then it was indeed the best decision operations could make.

I encourage other ecommerce fulfillment programs to consider a similar rule. It's the type of approach that can unlock a customer experience that is both competitive and profitable—both critical requirements to business growth in today's ecommerce landscape.

In many ways, this rule is what governs all product design at Shipium. The platform provides services that each individually help improve decisions towards speeding up delivery while reducing the costs of fulfillment. If you are looking to upgrade parts of your supply chain, consider us a resource. I'm happy to connect.