Engineering Engagement: Mesh CEO Saurabh Nangia on Leveraging Data Analysis to Foster Personalized Employee Experiences

Employee experience is fundamental to a business’s success; when workers are excited, committed and feel included, productivity increases and turnover drops, not to mention the health and wellness benefits. Despite this key understanding, less than half of US workers report feeling engaged at their jobs. Luckily, there are concrete initiatives that businesses can undertake to support their employees, and Mesh—an employee data intelligence platform—makes that process simple.

Saurabh Nangia, CEO

As Mesh co-founder and CEO, Saurabh Nangia, tells it, “Mesh is an intelligent social network for companies that makes it easy for employees to manage goals, share feedback, and conduct check-ins. It replaces a lot of different management tools and increases employee engagement, especially in remote teams.” Mesh helps managers stay connected with their employees by providing a one-stop shop for transparent and effective performance  management, internal assessments, and company communication.

Over the course of a decade working with tech startups, Nangia noticed that most companies were all about deploying cutting-edge technology to better understand and engage their customers, but there seemed to be a gap when it came to understanding and supporting the people who actually drove their business: their employees. “No one was capturing clean and relevant data with regard to the actual team members who are helping you build the company,” says Nangia. “In terms of figuring out what people are working on, how they are achieving their on-going goals, what strengths and values they exhibit and what sort of relationships they have within the company, there were no intelligent platforms that accurately captured it.” Without care and attention to these crucial elements of employee engagement, how can a business truly succeed?

Especially as the practice of working from home broadens, managers need to promote transparency through clear expectations and regular assessments. Nangia explains that “there needs to be a continuous performance management platform out there that will help build a sense of community and belonging across remote employees and improve their connection to the organization’s goals and values” This is where Mesh’s unique machine-learning approach comes into play. Central to Mesh’s interface is a social feed where employees and managers post experiences and feedback about their projects, goals, and colleagues. “Whenever they are updating any progress on a goal, everyone sees it. They can come and share feedback with them, they can applaud, they can give them points on it,” says Nangia.

Mesh then uses natural language processing and machine learning to determine the sentiment and core competencies displayed in each post. “We use ML, basically, so this entire thing will act as a personalized input into the performance management of every individual.” Mesh analyzes the data it collects, weighs the data based on analyses of individual user behavior to eliminate biases, and creates unique profiles for each user that publicly highlight their performance and accomplishments. “Leaders not only want to know who are the most engaged and productive employees, they then also need to drive personalized actions to ensure that each team member is aligned and feels included and valued,” Nangia explains.

To facilitate these complex analyses and maintain smooth operations, Mesh uses a variety of AWS services, including Amazon SageMaker, ElastiCache, Cognito and RDS. Nangia highlights three main benefits of using these machine learning and database management services from Amazon. First, “we don’t have to worry ever in terms of the uptime and reliability of the services; it’s all been taken care of by AWS.” The second is that “for enterprise launches, AWS makes it super easy to handle security requirements by creating a separate public-facing subnet from the private-facing subnet with no internet access ”.

Mesh also relies on AWS to take on the time-consuming task of managing all the various solutions and services that it uses. This means that for Mesh, there’s “none of that hassle we have to face at this point, and scaling systems is super easy. In a minute, we can just add another host behind the load balancer or move on to a larger instance.”

And scaling up is exactly what Mesh intends to do, according to Nangia. “In the next five years, I’m hoping that more than five thousand companies globally are using Mesh in some form or the other. My vision for Mesh is that eventually it will become the go-to platform for collecting and getting insight out of your employee data.” By utilizing a continuous social feed to aggregate data and Amazon’s machine-learning platforms to analyze that data for effective insights, Mesh hopes to help employee engagement and productivity peak across the board: good news for employees and businesses alike.