Cars as a platform for technology

Phones got a lot smarter in the last 10 years – now its time for cars.  Dumb Feature Cars, will become smartcars in the next 2 years.   I say Cars will become a Platform for Technology, because there are so many options.  From self driving, to touch wheels, to sensors that have yet to become developed.

 

Lets consider cars the most beautiful and fast computer that happen to sit in – what would you want it to do.  Let’s go beyond satellite radio and an iphone dock.   Mini is making some great strides, apple too with CarPlay, and lets not forget Tesla who has the largest display of any manufacturer and their system is a full operating system, not just an entertainment kiosk.

The larger trend here is that the internet of things will continue to innovate on top of analog machines, and technology ecosystems will continue to overlap – leading to some exciting user experiences and great uses of contextual data. 

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Google Moves Forward with Modular Smartphone

Project Ara is coming soon, and dev kits have been released.  I am very excited to see the modular and flexible systems of software and UI move info hardware for easy customization.

Drinking and (self) Driving Cars – Policy & Wearables

 

Within the decade, I think self driving cars will be the norm.  It will be a “why would you take the risk driving yourself” type of situation.  Not to mention some really interesting side effects such as lobbying from alcohol brands and insurance companies.  Imagine your car is its own designated driver – wow.   After all, this is a kit that can be applied to any car, not just google cars.   They are on the road, being used, and really no one is excited anymore – this baffles me.  Plus, there is a very interesting scenario where this allows cars to be turned into offices or 3rd places, where no one needs to know how to drive anymore.  Driving will only be a recreational sport.   But I digress…

At the same time, google glass is making a fight to not be banned by key states for use while driving –
http://www.bloomberg.com/news/2014-02-25/google-glass-faces-driving-bans-as-states-move-to-bar-use.html

What a dichotomy :
Partial cyborg = scares the public
fully automated robot that completely takes over = okay, I want one.

So in a sense, it seems that humans are scared of the human element. 

Who will get to decide how much we allow machines to help us.

12 mins. – pd 

 

 

Why Data can Often be Answering the Wrong Questions

 

Data is always historical.  However our goals are always future focused.

There is a science and art to data and strategy.   One part is very rational, and another is emotional.  Knowing how to merge the two, and depart from the obvious is where true innovation starts to occur.  

People turn to analytics to measure performance, determine data driven insights, and establish strategy based off the summation of all of this.  This type of thinking is great for identifying outliers, becoming aware of existing behavior, and a several other types of insights.  For the most part I personally think this can be incremental.  This has a place. I am not saying its good or bad. It just shows you exactly what you went looking for. 

Now lets consider another part of this equation.  Where do you want to be in x months? Could it be that we need to incorporate an entirely new way of thinking that is not currently being measured. Something that no one is looking for.  If we need to make leaps, instead of incremental milestones in progress, sometimes we need to step aside from the data and set our own goals using new tools and create new data sets.

The issue with ONLY relying on historical data is that innovation does not always show up in a data set.  Even if you crowdsource popular opinions of what people want, they can only think so far ahead.  And sometimes the true disruptions and innovative outliers are overlooked to make a prettier graph.  This is an common issue in social media.

These outliers could be the next ipad, tesla, or facebook.  Reference here to the famous Henry Ford quote ” If I had asked people what they wanted, they would have said faster horses.”  Sometimes the data was right, but to grow and move ahead, one needs to assume the data could be wrong if you could see what the future data would look like.  Things change.

There is a science and art to data and strategy.   One part is very rational, and another is emotional. Knowing how to merge the two, and depart from the obvious is where true innovation starts to occur.  

Data can always show you where you have been. But it cannot always show you the best path forward.

pd –   18 minutes.