We craft insightful visualizations that tell data-driven stories about the dynamics of the life insurance industry.
The Data Visualization team contributes to MassMutual's competitive advantage through our design and development expertise, a sophisticated technology stack, and a refined pipeline to produce custom data visualization web applications and products. These applications enable data exploration, facilitate interactive data input and annotation as well as make data science insightful, accessible, and ultimately actionable to more people.
The Data Visualization team has several strategic pillars that enable us to deliver value. These initiatives include Design, Technology, Process, Talent, Expertise, Research and Development as well as Storytelling.
Our team created a design language, Signal, to define and guide the visual design and behavior of user interface elements and visualizations. Our design language leverages industry best practices, aligns with MassMutual branding, and optimizes through usability testing to enable users to accomplish tasks and gain insights from data. We work together with product teams and developers to create the best product experience while at the same time meeting business goals.
Our team builds and maintains visualization libraries and a web framework. These resources support the efforts of the visualization team and can be leveraged by the larger organization. They are used to produce common ui components, visualizations, interactive dashboards and data intensive web applications. The styles and behavior built into the libraries and framework conform to our style guide and follow best practices. Also, the libraries leverage other modern libraries and frameworks such as D3.js, React, Redux, Django, and Python Pandas. Finally, we provide references, examples, instructions and a cookie-cutter starter project for ease-of-use and adoption.
We conduct training sessions on visualization best practices and technologies as well as mentor others to accomplish data visualization project work using our libraries and frameworks. We also perform expert analysis on dashboards and provide feedback on possible improvements to presentation, layout, navigation and visualization methods.
We create interactive visualizations that guide people through data or algorithms in order to better communicate the subject matter and facilitate comprehension.
We devote time to researching different approaches to developing data visualizations of complex data, algorithms and machine learning models using novel technologies and/or methodologies.
We invest in developing the knowledge, skills and morale of the team. These initiatives facilitate autonomy, mastery and purpose.
Our process leverages best practices in user-centered design and software architecture. The implementation is strategic and technically advanced. This process results in visualizations, web applications and products that are efficient, accurate and enable users to easily accomplish tasks, quickly gain insights and take action. Additionally our applications are enjoyable to use. The process is broken down into the following five phases: Intake, Problem Space, Data Exploration and Design, and Implementation.