Other parts of this series:
We all know that machines can enhance a human’s intellectual abilities. Now, machines are partnering with people to radically improve the emotional intelligence (EQ) and social relationships of the workforce of the future.
Financial services companies have long known that emotional intelligence (social skills, empathy, self- awareness) is strongly correlated with star performance among their employees. Relationships, or social capital, can be just as important in differentiating financial service companies from competitors as intellectual capital.
As I’ll show in this blog series, companies can now augment their workforce’s emotional quotient with the IQ offered by a new generation of personal and environmental technologies. These technologies can collect unprecedented levels of information about social and emotional states at work.
Data from sensors can paint a vivid picture using input about emotions, stress levels, relationships, performance, productivity, and collaboration patterns. For example, watches, headbands and rings detect physiological data such as heart rate, skin temperature and brain waves to accurately read a person’s mood.
This information can be used as the basis for giving concrete advice on adjusting workplace behavior. To capitalize on this emerging opportunity to sharpen employees’ emotional intelligence, banks and insurers can take a range of steps. These vary from minimally intrusive steps that merely quantify emotional dimensions at work, to changing the way employees interact with peers and customers to boost their performance.
Quantifying the personal
Data can be collected on individuals and provided back to them in real-time. By increasing self-awareness, workers can make real-time adjustments to tasks at hand. This field is called auto analytics. It is already popular in sports, where teams use heart rate and other biometric feedback to make real-time decisions about the players on the field.
One example is real-time feedback tools that highlight use of positive and negative words in conversation. The goal is to help employees (consider a field agent selling insurance or a call center service representative) use more positive words to improve social relationships and ultimately boost the bottom line.
Leveraging the power of prediction
With a reservoir of accurate data, an organization can experiment with interventions to boost performance. This includes using intelligent machines to predict emotions and behaviors. These insights help guide interventions aimed at improving performance. Based on previously collected data about each individual’s social behaviors, managers will be able to simulate how well specific people will work together and what challenges will likely emerge.
Companies could test different team configurations to maximize different traits. A group with diverse connections could excel at gathering new information quickly, while a team with close-knit connections could be better optimized to execute tasks effectively. Work assignments, team dynamics, and leader selection, to name a few, can be driven by analytics that can predict the impact of specific decisions.
Building emotional bench strength
Machines can also use analytics and cognitive computing to teach people how to improve their social skills or more accurately read other people’s emotions. This is true not just for workers, but also their managers, who appear to embrace the potential. One specific opportunity is digital coaching, helping improve managers’ abilities to coach or lead their employees.
Using tech to forge emotional links
Perhaps the most sophisticated use of technology—but also the most intrusive— involves changing people’s social and emotional behaviors in real time. The least intrusive way to do this is to have machines suggest actions, but still give humans the option as to whether or not they execute on them. Technology with GPS functionality might suggest an interaction with colleagues in close proximity based on similar work goals or shared interests, for example.
In my next post, I’ll look how financial services companies can start deploying such technologies in their workforces.