Economics of Business Model Fit
Augmenting Business Model design economics frameworks
Intro
My previous post was on achieving product-market fit. I have also written previously on business models as systems. This post takes an economics lens on the value capture design of your business model. I explore three economics tools, 1) Micro supply-demand curve, 2) Game Theory and 3) Behavioral economics. Based on the learnings from the economics tools I evaluate their fit with The Grid, a tool for business evaluation.
Microeconomics Supply-Demand Curve
The limit on what you are able to capture is a factor of microeconomics and your ability to segment your customer base into various experiences. The basic supply-demand curve is used to determine a market clearing price and an expected volume that you should produce.
The classic microeconomics curve shows that we all have a different willingness to pay. At the midpoint, you’d access 50% of the market demand. This is probably the theoretical max for a basic business model. There are alternative business models that allow you to capture more area under the curve, like two-part pricing similar to Amazon Prime and Costco.
ARM Example
One of the more inventive business models I have seen is from ARM, the chip design company. They have designed a business model that captures a lot of the value created through a multi-part fee model.
They generate revenue across three moments:
- The investment phase to design chips — this flat fee covers the base costs in a micro-curve
- Upfront license fee — similar to the investment phase costs this is a fee
- Royalty for each chip produced — this provides an incentive for ARM to design products that help their customers, while also capturing as much value as possible.
The below is an illustrative example of how these fees build out the supply-demand curve for ARM’s chip design solution. ARM is able to capture most of the value under the curve through their 3-part revenue model.
It is estimated that they get paid $0.35 per iPhone shipped, which is a small % of the cost to manufacture an iPhone — 0.08% of the cost of the phone. This likely explains why Apple continues to engage ARM. Though given Apple sold ~220M iPhones in 2018 this means they paid ARM ~$80M. At $300k loaded cost per engineer, the Apple team could higher 260 engineers at the same cost, though it is very possible that to create a better chip design than ARM would cost more than the $80M per year, plus add unnecessary risk. ARM has built a strong business that generates almost 30% profit margins and has a strong recurring revenue base.
Game Theory
Most businesses are designed to have customers repeat. Game theory evaluates the motivations of consumers and businesses. To maximize retention is equivalent to using game theory for repeated games. In this instance you would optimize to ensure that the customer has enough surplus after purchasing your product or service that they felt positive about the transaction. When you capture too much value you will see the results in your customer retention rates.
If there are no payoffs to the customer then there is no value, as can be seen in the equation above. If you have a competitor then you’d want to look at your payoff vs. their payoff.
Subscription businesses often face this question given that every payment is a decision to renew. Netflix recently raised its prices for its service. Taking into account game theory and the microeconomics curves above you would expect that the increase in price will result in some subscribers leaving. It is largely a question of how important Netflix has become to consumer (ie. how elastic their demand curve is).
Behavioral Economics
The previous two models are steeped in classical economics. The reality is that your customers are not going to make decisions like an economist. After reading through many papers and books from Tversky, Kahneman, and Thaler I have an appreciation for the concept of “humans vs. econs”. There are two key frameworks that are especially relevant here, 1) Value Function and 2) Decision Weights.
The Value Function that is a centerpiece of Tversky and Kahneman’s Prospect Theory has a large impact on the way customers value the decision. The main aspect is that people are risk-averse on gains and risk-seeking on losses (as seen in the graph below).
What does this mean?
If a customer has a choice between paying a smaller amount for certain now or the possibility they have to pay a larger amount later, they will choose the riskier option. This is one reason why preventative maintenance is such a hard sell for customers. In my research, the only successful maintenance plans are required plans or no additional cost — e.g. teeth cleaning, car oil change, vaccinations. During user studies, a customer says they want preventative plans, but in practice, they don’t follow through with the purchase.
Gym memberships are an example of an irrational decision. If it costs $30 per visit to the gym and the membership costs $130 per month it would make economic sense to do a membership if you will go more than 4 times per month on average. For many people, they aspire to go the 4+ times per month, but in reality, will not go to the gym 4+ times.
Decision Weights. In addition to the value function, these two psychologists came to realize that people’s assessment of value depends on the certainty of the solution. Said another way, people aren’t good with probabilities and assessing the value impact. The difference between 99% and 100% is worth 8.8% of value vs. 1% in reality.
OpenDoor is a great example of providing certainty vs. the existing home sale process. For a typical home sale there is a probability, let’s say 2% that your home won’t sell. In this situation, as long as OpenDoor will buy your home at more than 87% of your mental value you would prefer to take that deal. OpenDoor has a little bit of room then to underprice the home to account for their risk and they can charge the 6% rate for buying the home vs. a discount like Redfin.
This “human” behavior does create arbitrage opportunities, including insurance products for unlikely, but high-cost events.
Revisit The Grid
Earlier this year I shared some materials from The Grid by Matt Wilkinson (I recommend buying this book for all strategists). The frameworks he has created are a great approach to assess the business model fit. He has also released some new tools to make it easier to asses your business, see the link below.
Here is a view of The Grid Framework.
Some of what I wanted to accomplish with this post was to assess using economics frameworks towards business model assessments. Below is how I would apply economics to strengthen my assessment of The Grid framework.
Microeconomics Supply-Demand Curve
Not surprisingly the supply-demand curve can be a large asset to accompany the “Profitability” vertical of the model.
- Revenue Model — In economics, this is about the value your customer gets (ie. their surplus). If a customer is willing to pay $1000 and you charge $999 then you have only provided $1 of surplus
- Bargaining Power — This shows up in the classic micro demand curves. If you are able to make more the more you sell then you are in a stronger position.
- Costs — Tied to the demand curve is the supply curve. This also relates to the bargaining power where your marginal costs dictate your profitability.
Game Theory
Game Theory models can be useful for assessing the “Longevity” of the business model.
- Customer Base — Most specifically retention, is the summation of the value a customer could acquire over time. Most businesses operate with some competition or substitute. Thus the value should be relative to this alternative. You have to have a positive value to have
- Rivalry — I see rivalry as a function of the value delivered by our solution less the costs relative to a competitor. Now, this is easier said than done as not all values are equal.
Behavior Economics
This section of economics helps with the “Desirability” element.
- Wants and Needs — Applying the value function and decision weights can assist in assessing the alignment of value. The OpenDoor example is a great one that shows the value that can be delivered if you provide certainty to an ambiguous situation.
While similar to Behavioral Economics, I am a large proponent of assessing the motivations of customers. I wrote about this in the product-market fit post. For reference, here is the 4 forces model for motivation that I referenced. The strength of these behaviors influences the decision beyond the basic economic argument.
In Closing
Using economics is a powerful tool to augment the use of a business tool like The Grid. The implementation of various tools from economics can help to create algorithms to power the business model of your company. The power of technology allows you to experiment with these economic frameworks to determine the best fit for your business.
I’d love to hear about your tests and discuss questions you may have. You can find me on LinkedIn if you want to keep the convo going.
