Janell Ream Email & Phone Number

Milwaukee, Wi, Us

Directed the management of Perrynorm Analytics' data platform while providing strategic support for analytics, enhancing the firm's ability to serve small business clients and non-profit organizations.

Kenosha, Wisconsin, United States

With the stabilization of the data ecosystem, I led efforts to eliminate technology debt, streamline data processes, and enhance documentation. These initiatives enabled company-wide access to data assets, empowering embedded analysts and strengthening ties with business users. As a result, business users were now positioned to make strategic decisions through in-house data and analytics. By collaborating with Senior Leaders, business users, vendors, and team members, I identified opportunities for new data sources, reporting, and analytics, shaping our roadmap for the upcoming year.I continuously worked across the business to enhance our data platform, ensure its integrity, and promote its safe and secure adoption.

As the data ecosystem matured with the migration from SQL Server to GCP, I planned and executed the transition of our Direct Mail segmentation platform from Matillion to Dataprep within GCP. Once the platform was established, I transitioned daily support to the Direct Mail team members, which allowed me to mature the overall marketing segmentation approach to include churn models, LTV models, and predicted-to-purchase scores.

My time at Jockey began by leading the Direct Mail program, overseeing audience segmentation, standardizing reporting, and driving post-campaign analysis.

Franklin, Wi

This team was positioned to support all call centers, underwriters, and claims teams within Northwestern Mutual which lent itself well to some interesting projects.While supporting the technology call center and the Disability claims team I led a proof-of-concept of utilizing process mining to uncover the common paths of work and those one-off paths that result in unfavored client experiences. Although we didn't move forward with the platform it did reveal opportunities to clean and streamline data collection.As a team we collaborated with senior leaders and knowledge experts to introduce the first straight through underwriting cases and established a process to identify no/low touch Disability claims for claims processing efficiencies.

After 2 years as a daily support analyst I was promoted to a monthly support analyst. I enjoyed this role as it was more of a leader role working directly with the managers of the teams we supported and ensured my daily analyst had the guidance and tools needed for their role. Through my monthly meetings with Senior leaders I began to identify gaps in the hybrid team's performance reporting as they relied on data from two disparate systems. I worked with the manager and knowledge experts on how to accurately integrate the two data sources which led to performance reports to identify coaching opportunities and encourage great behavior from others. I enjoyed working with Senior leaders, knowledge experts, members across the Workforce team, and with the daily analyst to use data to improve processes.

Our Workforce Optimization team supports call centers, back office teams, and hybrid teams. In this role I supported the daily operations of ensuring our various teams were staffed efficiently to adequately service our various internal teams, field members, and clients. To do this I would review daily metrics to learn our shortcomings and wins and use them in each coming day to proactively monitor and adjust the day to meet the day's needs.Our team was split into daily analysts and monthly support analysts. I established great working relationships with the monthly support analysts and learned the importance of great collaboration and how it can simplify many tasks. I would also accompany the monthly support analyst in monthly planning meetings with the Senior members who managed the teams we supported.

I was an integral member of the small team that coordinated the delicate tradeoff of field members inputting their records of engagement with disjointed clients in Excel documents to gauge our effectiveness of re-engaging them with new financial representatives. This role taught me the complexities that come with manually supplied data, how to coach our field team in supplying the data and streamlining the monthly spreadsheet handoff, synthesizing data to report on progress and effectiveness, and the importance of continuously researching Excel features/functions to aid in our monthly process.

Elkhorn, Wi

Master Of Analytics, Applied Mathematics

GPA: 3.64 - Capstone was developing a predictive model for straight through processing of underwriting life applications as well.

Actuary Science, Financial Mathematics

GPA: 3.44 Dean's List for 4 semesters