You can follow along in this post by downloading the excel spreadsheet Demand and Profit Optimization Model
No matter what type of business you own, the laws of supply and demand will have a major impact on your success. By understanding precisely how these laws are governing your business you can leverage them to growing more revenue and maximizing your profits. Pretty much everyone has heard of supply and demand and many people have even taken an introductory course in economics. The problem isn’t awareness of these laws but rather how to create and analyze them for your specific business. That’s what this post is all about and by the end of reading this you will be able to create simple demand curves as well as pricing, revenue, sales volume and profitability estimates for your business or business idea and use them to make informed decisions to help you succeed.
Supply and Demand
First off here’s a very brief overview of supply and demand: People want things to make their lives better. These people are the “demanders.”
Other people make things (goods and services) that make demanders’ lives better. Those people are the “suppliers.”
Simple enough? Good!
How to Create A Supply and Demand Model for Your Business
To get started, lets suppose you want to open a new McDonald’s restaurant in your town. Let’s also suppose that I live in that same town and I am a potential customer of yours. Let’s now make the following assumption: my max willing to pay is $5 for a McDonald’s lunch (assume it’s a McDouble meal to be exact).
To carry the analogy further, let’s assume that if McDonalds lunches were free (i.e. price = $0), I would be willing to eat there 2 times per week (even if it were free, I wouldn’t want to eat there every day) so roughly 100 times per year. Let’s also suppose that I’m willing to pay $5 for a McDonald’s lunch up to once a year. Since $5 is my max willingness to pay, I’m not very excited about that deal and once per year at that price sounds about right. Based on the above information, we have everything we need to create a demand curve.
We’ll use the two sets of numbers above – 100 lunches/year at $0 price and 1 lunch/year at $5 price. This is a good place to start but when you look at this curve you’ll notice it makes linear assumptions about my preferences across the price range from $0-$5. For example, the chart assumes I will demand 20 McDouble lunches per year at a price of $4; 40 lunches per year at $3; 60 at $2; and 80 at $1. The truth is that this doesn’t represent my actual preferences and to get my actual preferences all we need to do is ask a series of simple questions:
- How many lunches will I buy at McDonalds per year if the lunch costs me $4?
- My answer is roughly 6
- How many lunches will I buy at McDonalds per year if the lunch costs me $3?
- My answer is roughly 10
- How many lunches will I buy at McDonalds per year if the lunch costs me $2?
- My answer is roughly 25
- How many lunches will I buy at McDonalds per year if the lunch costs me $1?
- My answer is roughly 60
- How many lunches will I buy at McDonalds per year if the lunch costs me $0?
- My answer is roughly 100 (even if it were free I wouldn’t want to eat there everyday)
Notice how easy it was to capture this data (conveniently I’m an easy person for myself to get a hold of). Now recognize how easy it could be to construct a survey of your own with similar questions to give your customers to ask them the same thing and create an estimated demand curve specifically for your business. That’s the simple beauty of creating demand curves.
Note that you can record this information in steps 2 and 3 of the Demand and Profit Optimization Template as shown below:
A quick side note to this is if you have a product that people will likely only need to buy once over the next several years (such as a computer or a new hammer) and you want to create a demand curve for it, instead of asking your customers how many they will buy in a year, ask what the probability (from 0-1) is they would buy at a certain price.
For example, if I had just invented a brand new type of hammer and I wanted to figure out what the demand for it could be, I would setup a series of survey question as follows:
- From 0-10, how likely would you be to buy this hammer (show a picture and a brief explaination of it) if it cost you $20?
- Suppose their answer is 1 – this translates to a probability of 0.1 that they will buy your hammer for that price…
- From 0-10, how likely would you be to buy this hammer if it cost you $18?
- Suppose their answer is 2 – this translates to a probability of 0.2 that they will buy your hammer for that price…
Getting back to the McDonald’s example, with the data from above we can construct a more detailed demand curve and make note of specific price points that can help drive sales. Note that this is the demand curve for myself and not representative of all McDonald’s customers. However, even though this isn’t necessarily a demand curve that McDonald’s should use to make decisions, hopefully this illustrates the process of gathering demand curve data and illustrating it. If you are a small business owner and would like to get a gut check on what demand for your product or service is, this is a great way to start.
Now notice the following about my demand curve… From $5 down to $3, my demand is relatively inelastic – meaning that if the price of the lunch is between $3-5, my demand for lunch doesn’t fluctuate much (between 1-10/year is all). However, once the price drops below $3, my demand for lunches from McDonald’s dramatically increases to anywhere from 10-100/year. Because my demand for McDonald’s lunch changes dramatically at $3, this means $3 is what economists call a price point. Some marketers use price points as a marketing strategy for optimal pricing. However, blindly choosing a price point to price your product without considering the costs of production and profitability is foolish. To make good price recommendations, you need to account for all those variables and later on we’ll explore how to do this. But before that I want to briefly explain shifts in the demand curve and how as a business owner you can shift the demand for your products to be higher.
For example, let’s suppose I see on TV an advertisement for the McDouble lunch that illustrates a study proving McDouble’s are not as fattening as they once were thought to be. Because fat is a non-monetary cost of eating a McDouble, knowing that the cost is lower than I previously thought makes the McDouble lunch slightly more valuable to me and increases my demand.
Let’s suppose for the sake of argument that I become convinced McDouble lunches are just as healthy as subway sandwiches. In this scenario, my demand for McDonald’s lunches will increase by 20% as illustrated below. Though this model only represents my specific demand characteristics, it can fairly easily be scaled to represent the demand characteristics of a larger population.
For example, if McDonald’s first opens a store off the interstate and uses only a tall sign to attract people, a certain percentage of people driving by will notice the sign and decide to exit and go to McDonald’s. That could be considered the first or baseline demand curve.
Now suppose McDonald’s were to use the results of the study and place them on a billboard 1 mile before the exit. Now two additional factors are being used to increase demand – a billboard to improve awareness and a message on the billboard that increases the value of McDonald’s lunch to health-conscious consumers. Both of these will help drive demand to your business.
How to Price Your Products or Service Now that we have established a basic demand curve, the next step is to create a simplified profit optimization table. To do this, the only additional data we need is the actual cost to produce the lunch. For the sake of argument and because I have no idea what their actual costs are, let’s go with $2.50 as the actual costs McDonald’s incurs to make a McDouble lunch. Since we only care about variable costs, not total costs which include fixed costs such as rent and building expenses, calculating this for a business should be fairly straightforward. Once we have the cost data, we need to enter it into the following table: The great part about this table is that it combines the price, demand and cost data into an easy to analyze table for finding maximum revenue (remember this is just one person’s demand over the course of a year) and profits. In this case the price that maximizes profits is $4 which creates an estimated $11/year in profits. When I think about how often I eat at McDonalds every year, I think this is about right. From McDonald’s perspective, they probably make a total of $11 in profit from me every year – if the cost assumption is accurate.
But since this is only one person’s demand, what if we wanted to estimate our total revenue and profits over the course of a year at one McDonald’s restaurant location? To do that, all we need to do is survey a representative group of potential customers, average their demand profiles and make an estimate of the annual traffic we might get. For purposes of this post, I’ll just assume that my demand curve is representative of all the potential customers for my local McDonald’s restaurant.
Next what I need to do, speaking as if I were the owner of a brand new McDonald’s location, is estimate how many customers I expect to come in each day on average. To do this, I’ll use the following logic: Every time I go into McDonald’s there are usually about 10 people who order inside while I’m there. I’m usually there for 30 minutes per trip. Also I usually see at least 5 cars go through the drive through. Since I only go during busier times of the day (breakfast, lunch, dinner), this only applies to those times and not to the off-peak times. But let’s assume each of those peak times lasts 1 hour. This means that 30 people come during mealtime and since there are 3 meal times per day, 90 people come per day during meal times. Let’s also assume that during the off-peak times, 5 people come every hour from 6a-midnight. Since we already accounted for 3 of the hours of the day, I’ll multiply 5 by 15 hours to get 75. 75 plus the 90 who come during peak hours gives us 165 people per day on average. Multiply 165 by 365 and we get 60225 people per year coming into McDonald’s. Since this is just an estimate, let’s go with that.
On the spreadsheet I made, this number can be entered as step 4 – as shown below: Once that number is entered, a new demand table will be generated and shown in step 5 of the worksheet as follows: This new table then generates a new demand curve on the next tab in the worksheet, as shown below: After doing a quick Google search I found this Forbes article that shows the average revenue per McDonald’s location is actually $2.6M – not too far from the $2.4M I made up!
I hope this illustrates quickly and easily how to create demand curves for your business and set profit maximizing prices for your goods and services.