Logic and Memory Building Blocks
Technology and Product Life Cycle Stage
Computing and Storage Capacity
Upstream Layer: Logic and Memory Building Blocks
As Moore’s Law defines the path by which the technology industry evolves, it is important to consider what types of technologies we should spend our money on developing. As time goes on, these investments will become more expensive with diminishing returns per dollar spent.
This leads us to a concept where we start investing in either downstream processes or upstream elements of computing technology. Obviously, most people would agree that spending money on any type of research is better than none at all; however, as a society, we need to determine if this is actually worth it anymore. A product life cycle has been defined for this very purpose.
If you look at the product life cycle, you’ll see that they follow a general pattern of introduction, growth, maturity, and decline. When introducing an innovative product to market (such as any smartwatch), there is limited competition and most consumers are interested in what they have to offer. This means that they can charge higher prices per unit than they likely will in the future years. Many companies choose to take advantage of this high price point by investing more money into research than they would otherwise need to if they waited until later stages of the product life cycle.
This very act alone is not bad; however it becomes detrimental when this trend continues for consecutive products or projects before generating from new technologies or old ones that work better. In the case of smart watches, it is now known that there are more efficient methods to power a wrist-wearable device as well as integrating things such as GPS tracking and cellular connectivity into one unit. The latter being something that was too cost prohibitive for many companies just a few years ago.
In this particular stage of the product life cycle, it is important to utilize your existing technology instead of spending time and money on new research. Examples include turning off sensor data collection from old projects where you have already gathered the necessary data or utilizing certain pieces of hardware because they perform specific tasks better than their newer counterparts. This can be difficult at times; however, you should always strive to make quant improvements whenever possible.
If you choose to continue on the previous trend and invest in more upstream processes, you may eventually arrive at a point where one or two technologies dominate this layer of development. Unfortunately, it is extremely difficult to maintain momentum once every company worldwide has decided to make the same investment as you did previously. For example, if you were able to develop some type of holographic display technology before anyone else, you likely would be able to corner this market for quite some time; however, there are several issues that can arise from this strategy.
Perhaps someone does end up developing the same technology as you do which immediately negates your advantage over competitors. Generally speaking, a prime example of this would be Microsoft’s decision not to release their Kinect product until almost four years after they had developed it.
This meant that they were unable to capitalize on a market that was just recently introduced and already fairly competitive. Had they been able to release their product before anyone else, things could have ended differently for them.
Beyond the factors mentioned above, there is also a general lack of desire from consumers to purchase technologies at this stage of development due to the high costs associated with newer technology.
In addition, people are not always willing or able to migrate from older products in order upgrade. As a result, companies have started offering upsells or cross-sells as an alternative strategy. Essentially what people mean when saying this is using old products as leverage in order to gain profits from new ones through something like subsidized pricing (loss leaders).