Learn how to program a robotic car in 7 weeks
Two years ago in “Why We Don’t Have Flying Cars, Yet” I explained why automation is the next big innovation for vehicles, not alternative energy.
Standford is offering a 7 week undergraduate class teaching how to program a self-driving car. Automation improves the under-satisfied outcome of cars but it is also technologically easier to make than low-cost long range batteries for an electric car.
The Predictive Innovation report the video was based on was first offered to GM but they turned it down. European and Asian car companies used the information and are now selling cars with automated driving features.
Volvo’s XC60 has a City Safety feature that automatically brakes to prevent crashes. It’s a pure gasoline car with lots of room and power. It is priced about the same as the Chevy Volt, although doesn’t receive any of the government incentives.
2011 US Car Sales | |
Car | Units Sold |
Chevy Volt | 7,671 |
Volvo XC60 | 12,932 |
The Volvo XC60 with City Safe automatic braking sold 68% more cars in the USA than Chevy Volt. So not only was it easier to build, and thus more profitable, it sold more units. The automated car is more desirable to customers. One of the key points of the report was to offer incremental improvements with meaningful value to customers. That made sure the new features were high quality and low cost.
In addition to satisfying safety, automated cars are better for the environment than an electric car. Electric cars just shift the source of pollution from burning gasoline in the car to burning coal at a power plant. Automated cars use less energy.
First, replacing or repairing a car damaged in an accident uses more energy than the car ever will from driving it. And how can you count the cost of injuries and deaths?
Secondly, by reducing traffic congestion automated cars can save energy for all the cars on the road while reducing drive times and frustration.
Automation in vehicles is still a big innovation opportunity.
Why Six Sigma Fails Detroit
Michigan desperately needs innovation to be competitive. When Japan started using Statistical Process Control (SPC) now known as Six Sigma, it was a competitive differentiator. In other words Japanese auto makers used quality and lean process as an innovation. Detroit has been feverishly implementing Six Sigma but they are still losing ground to the Japanese and now the Koreans and soon to be China. Why?
Six Sigma is a great thing but doing it as a “me-too”? only creates commoditization. Worse yet, the entire process of Six Sigma is about doing the same thing cheaper and cheaper. That leaves you in a death spiral to the lowest priced product, and little or no profits. Does that sound familiar?
Detroit, Michigan and the USA in general need innovation. Everyone knows that but almost no one is really doing it. The main reason is they don’t know how. What if innovation could be as predictable and systematic as Six Sigma? What if a company could create practical, profitable innovations on demand? Does that sound fantastic? Impossible?!? It is fantastic and it’s absolutely possible.
Predictive Innovation makes innovation:
- Efficient
- Low-Risk
- Controllable
- Repeatable
- Competitive
- Reliable
- Just-In-Time
Rather than looking at innovation as a magical creative activity it uses the very well defined study of System Theory and new breakthroughs in Information Theory to create a step-by-step process for innovation. How systematic is it? How about knowing there are 7 specific elements to innovate in any product or service and there are 15 types of alternatives for each element? When you realize that, you are guaranteed 105 innovations targeted precisely to your business needs and your customer’s desires.
When you use Predictive Innovation you can create an innovation strategy that causes your profit margins to increase overtime, risks to decrease and eliminate the threat of any competition.
Predictive Innovation has been used to create entire families of products, increase the value of investments, and solve seemingly impossible problems. It’s been applied to manufacturing, software, medicine, marketing, security, business strategy, politics, and entertainment.