It’s an exciting time for those of us who make new things.
Digital sensors have become cheaper, smaller, and more readily available. Network connectivity is so ubiquitous that it’s practically considered a human right. With wider adoption of IPv6 network addressing, we have the means to allocate trillions of independent IP addresses to every living soul on the planet. The Internet of Things is a current reality that lets us gather data from almost any object we can imagine.
It’s easy to see the draw of adding sensors and feedback loops to every product possible. The argument of “more information always being better” is compelling. As marketing teams around the globe discuss where their new products are headed, one thing you’ll often hear is, “How can we make our next (blank) smart and connected?”
With Industry 4.0 practices and the connectedness between ourselves and our artifacts, we are generating, storing, and communicating more data than ever before.
But is this new data meaningful?
The advent (and already waning) trend of personal fitness trackers is an interesting example. A study conducted by John Jakicic published in the Journal of the American Medical Association concluded that of 470 test participants trying to lose weight, those without fitness trackers were more successful in reaching their goals. Since having instant data didn’t produce better health, it’s questionable whether these devices affect our decision making.
In our digitized world, data is cheap and easy to acquire for the most part. You could argue that we already have enough data in the world to help us solve our most intriguing problems. What we lack are conclusions to act upon that data.
When looking at quality of life, insight is more powerful than data. An excellent example is IBM’s Watson cognitive computer.
In the arena of supercomputing, IBM’s Watson is not all that impressive. It’s not the fastest, the most powerful, or the most energy efficient. But in qualitative measures, Watson represents a hugely powerful platform. Its ability to draw meaningful connections between massively distributed and disparate data, makes it a leader in delivering valuable conclusions, rather than just well-organized data. In this way, Watson is transforming healthcare. By reading and cross referencing every medical journal available and interpreting data sets too large for human comprehension, Watson can aid doctors and researchers by suggesting new cures to diseases based on the data it crunches—and considers.
Maybe if fitness trackers suggested a change in behavior rather than bland metrics, they might be more effective. Integrating human intelligence opens the door to a meaningful call to action. It’s the conversion from data to insight that presents the most challenging gray area.
So, as your marketing team leaps to make their next product “smart,” be sure to ask:
- Can this data be converted into meaningful insights?
- How does that conversion take place?
- Will those insights alter behaviors or decisions?
- Do those altered behaviors or decisions result in a net positive effect?
By asking “should we” in addition to “could we,” your team’s project can be more than just extra digital noise in an ever-growing pipeline of data. Human Factors are always a wise consideration. Your next big project might integrate perfectly into the Internet of Things. Or it might not. Knowing the difference is what could determine the shape of your process.