Workership: A data-driven approach to worker voice

A data-driven platform to identify worker priorities and enhance the workplace experience.

The problem we are committed to solving is the difficulty in surfacing granular but important worker priorities in the workplace. This is an important problem to solve because a workplace isn’t going to function properly and productively if the needs of the workers aren’t identified and addressed.

Workership leverages data and technology to surface worker priorities at a granular level and allows unions and management to address them proactively and continuously. The platform does so by parsing and simplifying workplace policies for workers, getting anonymous input from workers on these specific policies, and using that data to identify worker priorities.

Workership’s data-drive solution to bring worker voice to the forefront can empower a vast number of workers by helping address their needs and also make labor-management relationships much more constructive that it is now.

Workership uses a data-driven approach to identify worker priorities and enhance the workplace experience.

The technology itself isn't new (anonymous/curated social network combined with data analytics) but it's application in facilitating worker communications and issue prioritization is innovative.

Experimentation around data-driven approaches to worker voice is important because the nature of the workforce has and will continue to become more fragmented. Traditional approaches to worker advocacy, with its reliance on manual and face to face worker interactions, hasn't caught up to the changes in the workforce.

For any given workplace, Workership parses existing workplace policies and simplifies them for workers. Verified workers then engage on our platform where they can anonymously discuss and vote on these issues. Workership analyzes data from this engagement to identify granular worker priorities on a real-time basis. That data can be used to create positive changes in working conditions in a continuous and proactive basis.

As we have data from a lot of workplaces, we are going to leverage machine learning to do predictive analytics to help optimize on various success metrics. 

Over the next 12 months our goal is to

• increase user engagement in our existing pilots 
• get new clients to pilot our platform
• generate revenue from our clients
• use data from the platform to create positive changes for workers

Over the next 3 to 5 years, our goals are:

• Have the platform be used by over 20 million users in 20K workplaces/bargaining units.
• Make Workership the main source of data to be used to improve labor management relationships
• Leverage machine learning algorithms to identify factors that impact productivity, turnover, and other success metrics in a customized and granular way.

We are going to partner with labor unions and companies and have their workers use the platform.

Currently, the website is being actively used by approximately 150 workers/users in 2 workplaces/bargaining units.

The users are very engaged on the platform and we have over 150K pageviews on the platform so far.

One of the user groups used Workership as the main data source to create their agenda for their labor management meeting in May 2018.

Within 12 months, we expect to be serving 20K workers/users in 50 workplaces/bargaining units. The data generated by workers on the platform will be used for labor management relationships and contract negotiations to address the needs of workers.

In 3 years, we expect to be serving 500K workers/users in 2000 workplaces. By this time, we will be using machine learning to conduct predictive analytics and optimize on various success metrics.

Our team has the combination of technology, business and labor policy background necessary to succeed in this sector. The team has previous experience in entrepreneurship, ability to build the platform in-house, and well connected with the labor management world in New England. Also, some of the team members are long time service workers in the US with an understanding of workers' issues.

We are going to generate revenue through subscription fees paid by companies, unions and governments for use by their members/employees.

I am applying to solve to connect with people who care about the future of workers in this rapidly evolving nature of the workforce. The existing labor management dynamics has made many workers extremely frustrated, and it is important to experiment with innovative technologies to come up with constructive solutions to this problem. 

Some of the key barriers for our solution are:

Getting more companies and unions to experiment with worker voice tools.  MIT Solve can help connect with organizations who see more worker voice as a good thing that not only empowers workers but also makes their organizations more effective.

Improving security of the platform: Since anonymity is a key part of the platform, maintaining operational security of the platform is critical. I am hoping to connect with mentors who can help on this front via MIT Solve.