Forecasting has been a full-fledged profession, and with all the tech gizmos and new technologies coming every few months, forecasters are facing real difficulties in gauging the real potential and coming up with adoption or diffusion rates. For example, iPad, broke all the records, and became the fastest adopting non-phone electronic product. Do you think forecasters were able to predict the number? I doubt it.
Apple’s forecasting behaves in a different manner than most electronic devices.Generally, people are slow to adopt the new technology or product, which is depicted by the stretched introduction and growth phase. Once technology has been tried and tested, the mass adoption occurs, which gradually comes to a plateau. One would see a typical S-curve of a product life-cycle.
On the contrary, with any of Apple’s products, except iPod, which followed the traditional trend, the initial hype is such that their majority of sales happen during initial 1-2 years, and then immediately dry up. This whole distortion can be attributed to the huge fan following of Apple, who are not only loyal, but also want to experience the new product before others.
This distortion should be considered before making predictions or forecasts for Apple. As a result of this, it is evident that time to reach one million sales for Apple has drastically decreased from its first revolutionary product. Apple sold 1 million iPods in 1.5 years after its launch. 1st generation iPhone, on the other hand, took 2.5 months (74 days) to reach this milestone. Some statistics are mentioned below for iPhone. Try to see the trend, specially what happens from 2008, Q4 onwards.
3rd product on the same lines is iPad, which has by far beaten all records, and sold 1 million products in just 28 days. Were forecasters able to predict this?
Having said that, I still wonder how forecasters can factor in the launch of products which are providing the same functionality at half the price. Yes, you are right, I am referring to Amazon’s Kindle fire, which has prompted the industry analysts to think again about their forecasts.