The Pricing Team at Clipboard is the division of our product team responsible for pricing each shift in the marketplace. We adhere to the Company Values and the Product Team standards, but also emphasize certain additional team-specific values. In the Pricing Team, we:
Build, rebuild, and rebuild again
New innovations destroy old innovations. In his theory of Creative Destruction, Joseph Schumpeter argues that when something valuable and innovative (like electricity) comes into existence something old and staple (like the lamp-lighting industry) fades away. Schumpeter was speaking from a macroeconomic perspective, but the principle holds at a smaller scale.
We believe that unless we have uprooted something and replaced it with something much, much better, it’s certain we are not innovating in a meaningful way. Building from there, we actively strive to make bigger step function improvements faster.
Where some might settle for value-creation charts that look like this:
We want our value creation to look more like this:
This isn’t just idle talk: we’re already on our way to the fourth version of pricing as a company, and the third version this year.
Know our math
We are familiar with the math behind what we are doing. Without checking, any member of our team can accurately explain the math they use in a variety of ways.
- We can explain the limitations, trade-offs, and assumptions of the math we use in such excruciating detail that we can start talking about them during lunch and not finish until morning the next day.
- We can explain the implications of specific limitations, trade-offs, and assumptions in specific business contexts
- We use the new business context we’ve gained to refocus on which limitations we should try and overcome, which trade-offs we should optimize or change, and which assumptions we should revalidate
- We can explain how this newfound context is changing the way we think about the world in such an engaging way that even a fifth grader could then ask helpful questions to figure out what we should do next
We consider the last category of explanation especially important because we’ve found that it’s always possible to simply summarize a concept we truly understand; we don’t really understand how something works until we can explain it to a fifth grader.
Judge solutions based on strongly held beliefs, not fit
Imagine that we want to make a four-data-point graph modeling the behavior of an object dropped from a plane. We might naively fit a line through them. If our model of the world is something as simple as “when we drop things from planes, the distance decreases proportionally with time”, we might end up with a graph showing a consistent slope, like this:
But that graph would be wrong, and if we had taken two minutes to look up basic kinematics, we’d know that at a glance. In the real world, the speed of the falling object would increase over time, and the slope of the line would gradually become steeper. If we were a bit more curious, we’d eventually learn that air resistance eventually makes falling objects reach the “max falling speed” of their own terminal velocity and stop accelerating. At that point, the slope of the line would become constant.
If we thought for a little bit longer, we’d realize that we’d also have to model the dampening role of air resistance on the object before the terminal velocity, and our graph would get a bit more complex. If we thought even harder, we would even realize that the shape, size, and other properties of the object are a large determinant in the air resistance it faces. Every piece of information learned would introduce new complexities that brought us closer and closer to correctly modeling the reality of how our object would behave as it fell.
Just because the regression thinks that we live in a world where distance increases proportionally with time, doesn’t mean that we live in a world where that’s true.
In the Pricing Team, we don’t just judge our models based on the fit they provide. We ensure that they represent the reality we know to be true.
Go down rabbit holes
The world doesn’t offer much guidance on how we should solve the pricing problems we face. There are no off-the-shelf models, stacks of academic literature, or blog posts on pricing per diem labor markets that come close to solving our problems for us. Yes, there are some helpful generalized economic concepts we use, and some principles we’ve been able to refine from our customer conversations and data. But for the most part, we’re on our own; almost every new problem we solve requires an individualized solution.
How do we solve our problems? We go down rabbit holes.
When we have an inkling something is happening in our data, when we find a clue that we might have an opportunity to learn or improve, or we are struck by random inspiration, we get very excited. We jump at the chance to uncover new patterns and discover better ways to do things. We always go down the rabbit hole. Most rabbit holes are dead-ends, and that’s fine: we know that the trick to moving fast isn’t spending idle time waiting for a sure-fire bet.
We go down as many rabbit holes as we can as quickly as we can to give ourselves as many chances at finding unexpected impacts as we can get.
Deliver value really, really quickly
The Product Team standards already emphasize this, but it’s worth noting that the Pricing Team works extremely quickly. It’s not because we put in more hours, but instead because:
- The way we think provides a lot of leverage. Solutions to critical customer problems are often as simple as ten additional lines of code, and we are great at finding those kinds of solutions.
- Our work is quickly measurable. We know whether or not we’ve solved a problem within a week, and it takes two weeks at most to get a sense of how well we’ve solved it.
- Our infrastructure is built for experimentation. If we have an idea and we’re not sure how well it works, we can deploy it to a few markets of our choosing within hours.
It’s because we’re positioned so well to go incredibly fast that we emphasize speed even more than other parts of the company. Speed is our biggest strength and our greatest opportunity for impact.
Obsessively mitigate risks
We preemptively identify and address risks. At any given time, we have a portfolio of risk mitigation work that’s separate from the customer problems we’re working on.
We face three main risks:
- Bad code.
- Solutions that help customers along one dimension but create a poor customer experience along another.
- Systematic points of failure in the pricing infrastructure.
We continuously innovate our tactics for mitigating each of these risks while maintaining speed and flexibility.