Traditionally, there are two main methods organizations use to develop new business lines, products, and services: internal and external innovation. Using internal and external innovation to fuel your business’ data analytics and strategy can give you a competitive advantage.
In this blog, we’ll dive into the difference between internal and external innovation, provide real-world examples, and explain how Futurety can help your organization innovate with data.
Internal Innovation
One method to develop new products, services, and strategies is through internal innovation. With internal innovation, a company acquires funds, then sends a group of highly-qualified people to a deep, dark laboratory for the development phase. The development phase focuses on research, whiteboarding, building, and testing their inventions and hypotheses until they have a working product, service, or strategy. Then it is passed on to the organization’s marketing and sales teams to form the best strategies to take the innovation to market.
External Innovation
The other method to develop new products, services, and strategies is through external innovation. With external innovation, the developing company works directly with consumers outside the organization, and they continue to develop through the proceeds of limited or unfinished versions of the final vision. External innovation allows the end-user to participate in the development process from start to finish and allows for constantly evolving development, marketing, and sales cycles based on public interest in the innovation.
What are Examples of Internal and External Innovation?
Two great big-picture examples of internal innovations are cars and phones. Scientists sit in laboratories and do their best to innovate vehicles with the safest crash-test ratings and smartphones with the most foldable screens. They’ll continue testing and innovating as long as the funding organization keeps cutting checks.
Examples of external innovations include flight and the internet. The Wright Brothers used the proceeds from their bicycle shop to effectively develop the most advanced bicycle of the time, one that could even fly. Similarly, the internet was initially developed through the proceeds of academic and big business organizations interested in cataloging and communicating at expedited speeds. Internet innovations and infrastructure continue to be developed as long as the consumers that use it keep cutting checks.
How Can Innovation be Used in Data Analytics?
Both methods of innovation have worked in the past and will continue to work in the future, but one of the most exciting internal innovation vs external innovation competitions happening today is between Google and Tesla and their race to develop better-than-human self-driving vehicle technology. Both Google and Tesla are light years ahead of any other competitor in regards to total data collected, but they have gone about collecting that data in very different ways.
Google’s self-driving technology began development in the labs and parking lots hidden away on Google-owned property. The company’s self-driving technology depends on lab-developed innovations in three-dimensional space mapping, as well as limited real-world vehicles on public streets. As of 2018, Google has used this and other technology in their labs to simulate over 5 billion miles of autonomous driving.
In comparison, Tesla’s self-driving technology began development on public roads and streets across America. The company’s self-driving technology depends on monitoring real-world drivers and driving habits. Each and every customer-owned Tesla on the road is sending data back to Tesla HQ, and with each new car sold, there’s yet another source of data. As of 2018, Tesla drivers have logged over 5 billion fleet miles driven.
Will Google’s internal innovation strategy and brilliant laboratory minds carry them to the top, or will Tesla’s external innovation strategy and growing feet of consumer drivers beat them to the punch? Only time will tell.
For more reading on Google and Tesla’s very different approach to self-driving car innovation, check out this article from the Verge.
How can Futurety help?
At Futurety, we use external innovation to develop full-functioning automated marketing strategies for Fortune 1,000 companies and public organizations that want to be the first.
Combining advanced data analytics and visualization with key audience insights, we are able to help organizations better understand how their consumers want to be engaged with, when they want to be engaged with, and on what platform.
If you’re interested in learning more about Futurety’s data strategy including analysis, visualization, and engineering, contact us today.
