Glenn Hofmann, chief analytics officer, New York Life Insurance Company

What are your key areas of focus for data and analytics in 2022?

We have many initiatives underway this year related to stakeholder engagement and technology.

1. Stakeholder engagement: We have established strong partnerships and multiple projects with core departments including finance, marketing, service and underwriting. More recently, we have expanded our reach to provide data science support to additional areas of the company which has provided our team with a variety of interesting and challenging projects in which a model-driven solution is used for the first time.
2. Technology: On the tools and infrastructure side, we continue to see the benefits of our cloud-based computing environment for all aspects of the data science lifecycle, including model deployment. This year we are adding a new tool for model monitoring to provide an automated way to detect data drift and monitor both model performance and quality.

Tell us what leadership means to you in the context of your role as a senior data leader.

At New York Life, the influence of my leadership fits into three categories: empowering others, advocating for the team and supporting our stakeholders.

1. My direct reports are empowered to make key decisions and operate day-to-day as if they were managing their own businesses. In turn, they empower their teams to make decisions based upon the collaborative efforts with their business partners. I have found that providing such autonomy, with some direction, fosters a better work environment and creative thinking which then leads to huge strides being made by the team.
2. As a leader, I advocate strongly for my team. This includes acquiring access to the best and most effective tools and technology infrastructure for the team, having work recognized through awards and promotions and ensuring that each team member has a clear career path based on their interests and aspirations. I strongly believe in providing such opportunities along with a training stipend and the appropriate support.
3. As the chief analytics officer, I am responsible for providing guidance and exemplifying best practices regarding data science to the rest of the company and supporting our stakeholders with their data science needs. This includes interfacing on behalf of our business stakeholders with internal groups such as vendor management, legal and governance. We provide end to end support from ideation to implementation to keeping an eye on future developments.

And what about the skills of your data teams and of your business stakeholders? How are you developing data literacy across the company/organization?

New York Life, as a company, encourages innovation and continual learning. As such, we have been successful in fostering an active data science community with participation from all areas of the company at all levels of data science knowledge and experience. Some are merely curious while others are actively learning data science skills. We host events, both internal and external speakers, training and many other learning opportunities.

Most recently I have taught half-day data science workshops to our executive officers and provided them with a background of what data science means at New York Life. This includes highlighting examples of models that have been deployed in various areas of the business, how we engage with our business partners, what their roles are as business sponsors and other services that we offer such as consulting, vendor selection and targeted training. Through guided table discussions with their peers, our executives have often been able to identify new areas where a model-driven solution could help make more accurate and/or more efficient decisions.

For our business partners on current projects, our philosophy is to meet frequently and meaningfully. This has enabled our business partners to be very familiar with the model building process as well as the data that we use to build the models. We have experienced that the more our business partners understand and are engaged in the model building process and the resulting model, the more value and benefit they see. The phrase ‘seeing is believing’ fits nicely. By seeing the model building process, they believe in the value it provides.