The age old adage — that technology is easy to manage while people are hard — continues to ring true.
Statistics show that employee disengagement due to poor management cost the nation’s companies between $450M and $550M in lost productivity per year (Gallup 2013).
While there have been huge gains in data-driven insights across medicine, healthcare, e-commerce, entertainment, and more — the one area that continues to be trial and error remains the management of people. Unlike machines, people’s behaviors, intent, and motivations are exactly that — individualized and non-generalizable.
However, more and more emerging technology aims to gain insight and intelligence around each and every team member — by ingesting data from emails, phone calls, wearables, biometrics, and computer vision to provide a nuanced view into how to best manage your interactions and relationships.
What sounds like sci-fi may be put to use in just the next few years — with the rise of startups building this intelligence layer, managers will have more intelligence than ever to drive behavior change — both from themselves but also from their direct reports.
There are many existing tools out there that improve written communication, such as Grammarly’s writing app, with over 6.9 million daily users. The next wave of companies will further augment our writing, and imbue it with predictive analytics to anticipate how other people will react to our emails. Textio, a startup based in Seattle, is now able to advise certain words to use to close hires. Known as augmented writing, Textio’s platform can quantitatively predict whether a document or email you’re writing will get the outcome you want. By pairing a highly predictive machine intelligence layer and a user interface, Textio brings quantitative insights to our individual writing and communication styles. CrystalKnows is another company with a platform that can recommends the exact words to use, depending on who the email recipient is and their personality style.
Voice
There has been a rise of startups building solutions in the conversation and voice intelligence space. By recording and transcribing calls, companies like Dialpad* can uncovers key insights about the conversations in real-time, analyzing calls and capturing key tasks, due dates, and action items. Their product VoiceAI can provide a customer service operator with feedback in real time on a call, or give managers visibility as when to intervene or provide support in a call.
For customer service, Cogito has designed AI-enhanced software that listens to calls with customers and assesses their agents’ emotional intelligence. Agents are assigned an “empathy score” based on their interactions and speaking behaviors with their customers, and can provide in-call guidance and feedback to coach the agents.
Wearables
AR/VR already has applications in public speaking, medical training, sports and military simulation, and empathy training. Humanyze has a people analytics platform that merges data from its’ employee ID badges with employees’ calendars and emails to determine whether physical office layouts affect workflows, communication gaps, and productivity. Upskill* is an AR solution for the industrial workflow that provides an interface for wearables that trains and guides industrial workers in assembly operations with real-time information on their line of sight in the field, and provides step-by-step instructions to drive performance.
Companies like Kinetic, StrongArm, and dorsaVi have developed movement and muscle sensors to give employees doing heavy lifting direct feedback on their work, to better guide them how to safely move, to prevent workplace injuries and reduce risk.
Computer Vision
For industrials, machine learning and computer vision technology can assess whether workers are wearing safety gear on the factory floor. Smartvid.io can identify industrial photos containing workers, then recognize workers missing hard hats, not wearing safety colors, or both. This computer vision technology took just minutes to review 1,080 images (as compared to a human viewer).
Another example would be for recruiting, where HireVue uses a combination of voice and facial recognition software to examine body language speaking tone and keywords from video interviews, to better inform the hiring manager during the interview process.
Biometrics
What if your Apple Watch could tell you when to use different voices or intonations, based on your listener or audience? We’ve also seen technologies like Halo Sport being produced for athletes, with a neurostimulation headset that stimulates the part of your brain responsible for muscle movement and muscle memory for athletic training.
The company Feel produces an emotion sensor and platform that graphs a user’s emotional state by monitoring a variety of physiological signals from your body like electrodermal activity, blood volume pulse, and skin temperature to recognize changes in your emotions throughout the day. With this data, the platform provides personalized and real-time recommendations to help users reduce stress and improve well-being. Would a subset part of this data be shared with managers or HR, to guide and grow their empathy for an employee?
Early MIT research has produced wearables that can tell you how you are making others feel as a part of conversation. Using transcripts, sound samples, and biometric data — including electrocardiogram readings and skin temperature measurements — the wearables can detect their listener’s resulting emotion and provide real-time feedback back to the speaker. While this technology has early use for people with Asperger’s syndrome or other conditions that can make it a challenge to perceive human emotions, this technology may not be far off for leaders who need to read a room while delivering a tough message or conversation.
While the use cases for these types of technologies are still early in their days of development, given our current appetite for data and insights in our daily lives, a future where people managers and leaders get the same real-time data and personalized insights may not be as far off as we may think.
- These companies are Work-Bench portfolio companies.
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