How Does Apple Make its Money?
It’s always an interesting question: how does X plc make its money. We know its sales are £million or billion; we know that they have some excellent products and services; and so on. Which product and which service brings in the most profit though?
As they were discussing Apple’s second quarter 2015 results earlier this week I decided I would try to answer my own question: this is what I did.
Data
To answer my questioon, I not onlu needed to know sales, profit and and so on but which products they sell and how many of them. Normally, getting hold of such information in detail is a problem: it’s just not possible to get it. So it proved with Apple. That is, in the time I allowed myself to find it.
I was looking for sales units of iPhones, iPads, Mac desktops, Mac laptops and so on. I found a mixture of quarterly and annual data. As far as mac computers are concerned, I had to estimate those sales. However, I was reasonably pleased that at least I had this:
Year | Sales ($bn) | Macs | iPhone | iPad | Gross Profit ($bn) |
2007 | 24.6 | 10.8 | 1.39 | 0 | 2.18 |
2008 | 37.5 | 14.2 | 11.63 | 0 | 11.58 |
2009 | 42.9 | 20.9 | 20.73 | 0 | 13.84 |
2010 | 65.2 | 27.6 | 39.99 | 7.46 | 26.71 |
2011 | 108.2 | 33.5 | 72.30 | 32.39 | 45.52 |
2012 | 156.5 | 36.4 | 125.04 | 58.31 | 71.93 |
2013 | 170.9 | 32.6 | 150.26 | 71.04 | 71.06 |
2014 | 182.8 | 37.8 | 169.22 | 67.99 | 78.48 |
The sales and gross profit figures are in $ billions and the sales of macs, iPhones and iPads are in millions of units.
I used the Data Analysis ToolPak to provide me with the regression equation and so on and, making Gross Profit my Y variable, I generated four different models, which you can see in the spreadsheet linked to the bottom of this page: The main part of the output of model four follows:
SUMMARY OUTPUT | Sales = Y | |||
Regression Statistics | ||||
Multiple R | 0.9996 | |||
R Square | 0.9992 | |||
Adjusted R Square | 0.9985 | |||
Standard Error | 2.4609 | |||
Observations | 8 | |||
ANOVA | ||||
df | SS | MS | F | |
Regression | 3 | 29,164.5307 | 9,721.5102 | ,605.2518 |
Residual | 4 | 24.2243 | 6.0561 | |
Total | 7 | 29,188.7550 | ||
Coefficients | Standard Error | t Stat | P-value | |
Intercept | 14.0494 | 3.4576 | 4.0634 | 0.0153 |
Macs | 1.0860 | 0.1970 | 5.5119 | 0.0053 |
iPhone | 0.3771 | 0.0998 | 3.7774 | 0.0195 |
iPad | 0.9334 | 0.1864 | 5.0074 | 0.0075 |
The Interpretation
This page is just a summary page so I will assume that you understand the variables and results you see here. The outcome is, however, that Gross Profit can be said to be a function of the sales of macs, iPhones and iPads. In addition, we can see that the computers are the most significant items that are sold, b coefficient of 1.0860, followed by iPads with a b coefficient of 0.9334 and iPhones are far behind in their significance with a b coefficient of just 0.3771.
Conclusions
This is a very small study with just 8 years’worth of annual data but it does give us a small insight into the importance of the contribution of the various products that the company sells.
download my file apple_analysis
Duncan Williamson