There is a common cycle when developing technology:
And the cycle begins again.
However, many products in the “experience” phase are met with a resistant market or the response is significantly different than anticipated—the technology isn’t accepted by the market and the product flops.
Instead of going back to the drawing board,
What if products didn't need to "fail" in order for us to learn how to make something better?
Initially, technology researchers, driven by curiosity, break the molds of what we believe is possible. They experiment without being bound by the application of a finished product, pushing the limits of assumptions and capabilities in order to drive us toward a future that wasn’t previously possible, or even conceivable.
After refining these experiments over months and years, their findings are presented in academic journals and at conferences, inspiring real-world applications and offering a prescient view into things to come.
Then, with new capabilities to explore, tech companies continue the cycle, becoming the veritable archeologists that take those initial innovations and apply them based on consumer needs.
We're collectively enamored with new technology, which can be seen in the programming of tech conferences like "Human Factors in Computing Systems" (CHI):
But life isn't something to optimize, it's something to experience.
The next set of learnings occur because something goes wrong. For instance, the cost of not fully understanding the impact new technology will have on users can be seen in the privacy and data-ownership problems that Facebook could have proactively addressed while the platform was emerging, rather than only now in retrospect.
After the issues arise, academic researchers return to the drawing board, investigate why something failed and what was learned and how to do things differently in the future. And the cycle begins once more.
This is where design strategy comes into play.
As we build toward the future, the key piece that is often missing in this cycle is the qualitative research needed to understand the relationship between the invention (academics), the application of those innovations (technology), and what is presented to the real world (users).
Running in parallel to the research on emergent technology are investigations into how real people respond to these new technologies—and how culture adapts to new technology-driven behaviors. These research findings focus on understanding how a product will exist in real life and what the potential impacts will be, positive and negative. Topics from the same CHI conference show this shift in perspective, even in the titles of the presentations:
Between the academic language and inventions based on innovation for innovation's sake, there’s a sweet spot where technological advancements can fit into behavioral norms and cultural expectations.
While studying the existing academic and technology research, design researchers and design strategists can simultaneously look forward to the likely cultural acceptance or fallout from the things we are proposing. If a product is too different, an anticipated need isn’t there, or the assumptions were incorrect, there is a collective “uh-oh,” which can be fatal for an emerging startup like Juicero.
By challenging companies to see humans first and shaping their technological advances to meet real needs, iterating and evolving based on behavior patterns, we can predict the social fallout that's often inevitable with large-scale behavior change. These “predictions” require slowing down the process and focusing on ethnographic research as the foundation for new creations.
Yes, the future is here, and the world is spinning ever more wildly to develop technology that transforms our lives. Imagine for a moment how those evolutions might look if there were more successes, fewer failures and a more rapid, and relevant, iterative process when developing valuable, applied, technological solutions. Now imagine making that a reality is as simple as including real human insights—design research—in the design and development process.