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Uber Financial Analysis

2428 words | 6 page(s)

Uber is a child company of Google, and it seeks to provide an innovative new way for people to get around in the world’s cities. With a tremendous amount of funding allowing the company to pursue an aggressive expansion strategy, Uber has been able to gain market share throughout the United States and in many parts of Europe. It is an app-based ride-sharing platform that seeks to compete with private car and taxi services. In essence, Uber allows its users to sign up through an easy web app, linking a payment method to their account. When they need a ride, they can simply request one through the app. The Uber driver that is closest to them will then be summoned, and the payment will be made automatically. Rather than being a traditional taxi service, Uber allows individuals to ride with other individuals. Uber drivers are average people equipped with Uber cell phones. What this means is that Uber is able to provide ride sharing service for cheaper, and users are able to ride in nicer, cleaner cars with drivers who know their name and may be friendlier, as well. The service is designed to be more convenient and usable than the traditional taxi model.

In order to measure the demand for Uber, one will need to measure it in terms of number of rides solicited. This is an easy measure of demand, and allows for more effective data analysis. Because Uber has expanded to almost every major American city and currently exists in 45 different countries, the geographic reach of this service is extensive. Narrowing the scope to San Francisco will make analysis much easier. This paper will outline some of the elements that impact demand for the product, taking a look at its competitive environment, as well as internal and external factors. It will discuss price elasticity, the company’s cost profile, and the leading indicators of the product’s would-be sales success.

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Demand Model:
The measurable demand factors that tend to influence demand for the company’s service include, most principally, the price of taxis in a given city on a per mile basis. Demand, as well, is influenced by the price of Uber. The ride sharing or taxi industry is heavily price-sensitive, with individuals often making choices on the basis of the most affordable option (Yang et al, 2002). Uber’s price per mile will heavily influence demand for its service. Demand will also be influenced by the number of dollars Uber spends marketing in various cities. The company has engaged in a guerilla marketing campaign to this point, and its service has a very grassroots feel. The number of bars in a specific geographic area will also influence the demand for Uber in that area. In addition to the number of bars, the number of restaurants will have a distinct impact. One might measure the number of bars by finding out if there has been an increase in the number of liquor licenses issued in San Francisco. Likewise, demand might be impacted by the price of a competing ride-share service, such as Lyft. In addition, another demand factor might be the average wait time for customers.

There are some demand factors that are difficult to quantify. For instance, the cleanliness of Uber vehicles will influence demand. In addition, there may be political factors that influence demand. There are going to be protracted political battles between Uber and the taxi lobby – like the one that is taking place in Charleston, South Carolina right now – and it will be difficult to quantify how this influences the demand for the product.

This section is devoid of any mention of demographic factors. That is because Uber, being something of a common carrier, has a product that can and does appeal to all different kinds of people. It stretches across demographics, and thus, that factor will not impact the demand.

Demand Model Expectations:
Limiting the scope of the inquiry on Uber just to the city of San Francisco, and assessing demand in terms of the number of rides, one can assess the expectations of each demand model criterion. The first demand factor is the price per miles of traditional taxis within San Francisco. If the price of taxis per mile goes down in San Francisco, one can expect the demand for Uber to decrease in kind. Generally speaking, Uber customers are not particularly loyal to the service, at least not yet. While there is some differentiation with rides, people are generally just looking to get from Point A to Point B, and they do not spend much time within a taxi. This suggests that a reduction in the price of taxis will cut into some of the demand for Uber rides. Similarly, a reduction in the price of Lyft, which is a direct competitor, will cause the demand for Uber to decrease, as more people will switch to Lyft.

Uber’s own price per mile is another element that will influence demand. As the price of Uber’s service decreases, demand for the service will increase. Experience suggests that people care to some extent about price when they are enlisting the help of a taxi or ride-sharing service, so an increase in the price of Uber’s service could cause customers to seek another option, either driving themselves, using a different company, or not going out at all. This can decrease demand for Uber.

Uber’s advertising will have a direct impact on demand. The more the company advertises, the more people will learn about the service. At current, Uber is not very well-known, which means that many people who might use Uber just do not know about the service yet. An increase in advertising is likely to produce an increase in demand, as well.

Finally, the number of bars in San Francisco will increase demand for Uber’s service. More bars means more opportunity for people to go out and have a good time. It also means more people needing a ride home if they are drinking. The impact will not be direct, of course, as one person of extra capacity will not produce an in-kind increase in demand. This factor can be expected to increase demand slowly over time, however.

Average wait time for an Uber ride will have an impact on demand. If average wait time goes up, then demand will likely decrease. If average wait time is cut, then Uber’s services may become more popular, or more in-demand. These things could become potentially problematic for Uber because an increase in demand will lead to more people using the service, which, if not coupled with an increase in supply, could lead to an increase in wait times.

The factors that are difficult to quantify – including the cleanliness of Uber vehicles – will have an impact, either positive or negative, depending upon which way those factors go. Cleaner vehicles will be expected to produce increased demand, as people will likely respond to the improved service at the same price. They will, in essence, be getting more value. Worse cleanliness helps to make the Uber service more like taxis, which will decrease demand for the service.

Price Elasticity of Demand Expectations:
Elasticity refers to just how sensitive demand is to certain changes. Price elasticity, for instance, refers to how demand will change according to changes in price. If something is elastic, demand will go up when prices go down. Likewise, demand will go down when prices go up. Some items – like food, for instance – must be purchased by people for survival, so people tend to still buy them regardless of price. These things are said to be price inelastic.

Uber’s service is mostly a luxury, except for people who may use it for work purposes. In general, however, it allows people to go out and enjoy themselves, and helps to facilitate the entertainment process. Because it is not something that people need, the service will tend to be elastic.

There are a few available substitutes for this service. For instance, one could choose to use taxis, which are not direct competitors like a company like Lyft might be, but provide roughly the same thing. People could also drive themselves, or in some cases, they could walk. The high availability of substitutes makes this service more elastic because people have options. They are not tied to the service at any price.

On time dimension of the purchase decision, people tend to act quickly. This is mostly due to the nature of the service. People are generally not planning these purchases. This tends to make the service more inelastic, because people do not want to spend as much time looking for alternatives.

In terms of sale price as a percentage of the consumer’s overall budget, Uber represents an extremely low percentage. This tends to make the service inelastic. When the extra dollar or two spent on a product do not hurt the consumer, the consumer is less likely to be concerned about that price.

Ultimately, this service will tend to be inelastic to some extent. While there are substitutes, and while the service is more luxury than necessity, the time dimension of the purchase and the relatively low purchase price indicate that consumers will be less likely to invest time into tapping into those substitutes. The small prices changes will have less of an impact overall.

Cost Profile:
All businesses incur some costs in the course of conducting business. Those costs can either be fixed costs or variable costs. Fixed costs are those that remain the same no matter how many units of good happens to be sold and no matter how often a service is used. Variable costs are those that are dependent upon the quantity of goods or services sold.

In the case of Uber, some of the fixed costs are tied up in the creation of Uber’s phone application, which is necessary for the use of the service. There were costs involved initially in creating the application, and there are continuing costs in running the application or offering it through the popular smartphone providers. Likewise, Uber has fixed costs related to its offices and staff. These are often called “overhead” costs because they do not tangibly change according to how many rides Uber is able to sell in a given city.

In terms of variable costs, there are many for Uber. Uber has a strange model in that it passes some of its costs on to its drivers, but one of the primary costs is gas. The more rides a driver provides, the more fuel he/ she will use. The same is true for vehicle maintenance. Ideally, a vehicle will have more maintenance costs the more it is driven. Insurance may also be a variable cost. More driving equates to more risk, which leads to higher insurance rates. In addition, one of Uber’s primary costs is now ticketing. With many cities handing out tickets to Uber drivers, this cost increases with the number of rides Uber hires.

One positive externality of this service is that it will lead to less drunken driving. As people have more options for cheap ride sharing, they will likely head to the bars and restaurants in something other than their own vehicle. This can lead to reduced rates of Driving under the Influence (DUI) crime.

Leading Indicators:
Bar and restaurant wait times might be a leading indicator for Uber sales. If bars and restaurants begin to have longer average wait times, then this suggests that the demand for bars and restaurants is rising in a given city, or San Francisco in this example. More demand for bars and restaurants would mean that more people will end up needing rides, so when one sees these wait times increase on average, then one might suspect that the demand for Uber services is going to rise soon after.

Because the service is something of a luxury, it will also be dependent upon people continuing to go out and enjoy themselves. This means that bigger, macro-level changes to the economy will be bad for Uber in some respects. People might turn to Uber because it is a cheaper alternative, but overall, there will be less demand for the entire ride-sharing or taxi service. This means that any number of overall economic indicators might be a leading indicator for this particular service. One might use unemployment rates both nationally and in San Francisco to predict decreases in demand for the service. If unemployment rates begin to rise, then fewer people will have the money to go out and enjoy themselves, which will reduce demand for Uber. Keeping an eye on unemployment rates can provide a picture of where Uber’s service will be shortly thereafter.

Conclusion:
Uber figures to be a more mature company in five years. At that time, the factors that influence Uber’s demand will still be roughly the same, except for the addition of more competitors in the direct market. At current, the activity of actual taxi companies is a major demand factor, but in the future, there will likely be more companies that seek to compete on a direct basis, offering web-based applications and more convenient ride sharing. Being at the tip of the spear, Uber currently benefits from the fact that it is largely alone (with a couple of exceptions) in offering its service. Moving forward, the market will be more competitive, so Uber’s demand will be influenced much more by its direct competitive environment. At the same time, the demand model expectations figure to be roughly the same for Uber moving forward. The factors that influence demand should shift demand in the same way heading forward.

It is possible that the service could become more elastic moving forward. Already, alternatives like Lyft have eaten up some market share. This could continue heading forward, causing more competition, and thus, a more elastic environment for the company.

The costs of providing an Uber ride will almost certainly change, but it is difficult to know how much. Gas prices are variable, and while they will tend to rise as a product of inflation, they are also prone to downswings depending upon the politics of the Middle East and a number of other factors. It is possible that fixed costs could go down as Uber becomes more efficient in its operations. The leading indicators figure to remain relatively constant over time, as the way in which Uber success interacts with the success of the overall economy should remain relatively static.

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