When you read the quote above about Wayne Gretzky’s strategy, it seems obvious, easy, intuitive and natural. However, in practice, it is not exactly easy to execute. Skating to where the puck is going requires looking at the available data about how the puck often travels based on its size and weight from one position to the other, how certain players normally hit (hard or soft) the puck, the conditions of the ice, and the obstacles that may be in your way as you attempt to meet the puck in its future, as yet undetermined, position. Essentially, it’s hard to predict what will happen in the future because there are so many variables that can impact it.  However, those who make reasonably accurate guesses about how things will turn out are often rewarded. 

 

So, when we think about how we prepare our children for a brighter tomorrow, it becomes important as parents to make the best decisions regarding which skills we will focus on developing so that they can ultimately become successful.

 

·         In 1973, 72% of jobs required a high school diploma or less than high school. By 2020, it is expected that the number of jobs with these educational characteristics will fall to 36%.

·         From 2014-2024, computing occupations are projected to grow by 12.5% while all other occupations are projected to grow by 6.5%.

·         The average high school graduate has a lifetime earning potential of $580,000. The average college graduate earns $1.18M. While the lifetime earnings of a computer science major are $1.67M (40% higher than the average college graduate). In addition, recent studies have shown that computer science is the 2nd highest paid degree after engineering.

 

In an essay published in the Wall Street Journal entitled, ‘Software is Eating the World’, Marc Andressen says, “…..we are in the middle of a broad and dramatic technological shift in which software companies are poised to take over large swathes of the economy. More and more businesses are being run on software…”

 

He goes on to list several fast growing companies that are dominating their respective industries. However, what is important to understand is the reason why he believes software will play a dominant role going forward. As Marc so eloquently states, “All of the technology required to transform industries through software finally works and can be widely delivered at global scale.”

 

Essentially, Marc is arguing that the iterative approach of technology development has been allowed to improve itself over time. As these improvements have occurred and more people have joined the network, he sees big shifts in how future products and services will be delivered.

 

One of the clearest examples of this is Uber. Uber was founded in 2009. 7 years later it has grown to 77 countries, $70B valuation, and serves millions of customers. This technology reached global scale using a mobile phone which was widely released just 2 years before Uber was launched. In just a short period of time, Uber has disrupted the technology infrastructure and is rapidly moving us toward a path of self-driving personal transportation. This type of launch and global penetration would have been unimaginable 20 years ago. 

 

Despite a clear trend is this direction, we are still collectively not graduating enough SW engineers.

 

In fact, statistics published by code.org, state that there are currently 500,000 computing jobs that are open. These jobs are projected to grow 2X as fast as the rate of all other jobs. By 2020, there will be 1 million more jobs in computing than there are people to fill them.

 

In recent history, we’ve been fortunate to witness the impact computer programmers & technology-driven companies can have on shaping the trajectory of our world. Gates, Zuckerberg, Dorsey along with countless others are had a vision for what they wanted the world to become and utilized technology to accomplish that goal.  The nature of technology development creates operating systems (Windows), social networks (Facebook), and hardware/software products (Apple) that touch millions and sometimes billions of people.

 

Computer programming is fundamentally about developing the capability to give a machine a set of instructions to follow. In essence, the development of computational thinking requires a foundational understanding of how computers work. Once this skill is developed, learning a new language is relatively straightforward. There are currently several languages that developers have a preference for. From Java to Ruby on Rails to Python, current applications quite often require a decision to be made on what the best tool for the job. However, languages that are popular or have great utility now aren’t necessarily what will be in demand going forward. Since it is hard to predict which computer language will be in demand in 10,20 years, it is more appropriate to focus on the development of understanding algorithm design & logic. And because we know that technology based solutions will become a larger and larger portion of the automation economy, the ability to solve problems using technology is where the puck is going. Make sure your kid is headed in the right direction.