What’s Next for Wearables?
As a strategy and innovation consultant I’ve been afforded the opportunity to test and try out many consumer wearable devices. While these devices have a lot of potential, right now their potential impact on large organizations is minimal. Obviously the accuracy of the devices is a major concern, but outside of that it’s important to think about what data these devices can actually generate and how difficult it will be to generate meaningful correlation from the data.
After trialing many wearable devices here are my main takeaways:
The wearable technology providers with the best application development are the ones that will be the winners. Most of the utility and wow factor from wearable devices is derived from the data analytics and applications available for devices. An example of this was hexoskins app that had a cool visualization for inhaling and exhaling (although it couldn’t give you additional information like VO2 Max based on this information). Since most wearable technology products are focused on the technology and not the software there is a lot left to be desired from the apps that accompany products from a reliability and capability standpoint.
Battery technology must be improved and standardized or wearables run the risk of becoming novelty items. I had a few issues trialing all the wearables devices, the first of which was that I ran out of plugs to plug all of the different devices in. Wearable technology providers should decide on some type of wireless charging platform or technology that works across devices. I emphasize wireless because once I took the devices off to charge often times I forgot to put them back on. Part of my reluctance to put the devices back on had to do with the effect using multiple devices had on my cell phone battery life.
Universal levels of accuracy (an accreditation system) need to be developed for wearables. The readings on devices measuring like categories were wildly different. Important consideration needs to be given to where these devices are on your body because I suspect that the difference in location contributed to the variability I was seeing in the readouts. The best example of this was the heart monitors which all had significantly different readings. Assuming that the Hexoskin chest monitor is the most accurate, because it goes around your chest, in general the lowest Heart Rate recorded was the iWatch wrist based heart monitor, while the ear based LG heart rate monitor was at times lower than the iWatches heart rate monitor and at others higher than the Hexoskin chest monitor.
It will take an ecosystem that has multiple connected devices to develop and record accurate and useful information. This means that the ideal wearable technology could be a device that is attached at multiple points on your body like ankles, lower back, chest, upper back and wrists and utilizes multiple sensors to provide a holistic view of an individual. Additionally there will have to be some type of modular design functionality that will allow wearable devices to have exchangeable sensors that focus on very specific issues. Lumo lift is a great example of this, as the device can only correct your posture when sitting down (although simply being reminded to change my posture while seated greatly reduced my back pain). If this device could simultaneously improve your posture will running and standing the value of it would increase exponentially in addition to the ability for the device to quantify the reduction in pain I’m experiencing (a week after I initially wrote this Lumo Lift announced a running variant with a battery that lasts a month). Another example of a company on the right track is Withings, who have developed an integrated network of products and a well-designed application. They seem have realized that trackers alone are not valuable over the long term and have a whole suite of connected home and body devices: from watches, to smart body analyzers, home security, wireless blood pressure monitors, aural alarm clocks, and baby monitors. All of these products can be controlled from the App which ran the best out of all the apps I used.
This experiment with wearables taught me that the devices will not be transformative unless they are eventually able to analyze an activity, grade your level on some type of standardized scale, and suggest corrective actions. Currently most of these devices give an estimate of how far you’ve gone, and how hard your heart was working over that period. As stated earlier the hardware itself is secondary to the analysis and applications that use the data from the hardware. Two of the more impressive examples of this that we saw were from providers DorsaVi and Fatigue Science that used wearable technology in combination with advanced algorithms to create products that can be used to scientifically reduce work injuries (Dorsa Vi) and reduce/quantify the effect of sleep deprivation on decision making (Fatigue Science). Both of these companies have focused on the accuracy of the device because they recognize that the accuracy of the device is what will allow them to find relevant correlations. As for off the shelf devices it feels like a lot of these devices are one step away from being useful for a long period of time in daily life and also in an enterprise setting. Device makers should continue to partner with scientists and big data analytics providers to help them find useful correlations and predictive abilities for their devices.