This project engages students from the University of Illinois in a practical, hands-on experience with PCMI, a leader in software solutions for warranties. The project aims to explore new data product opportunities, develop a business case, and support the design and development of innovative data-driven products.

Goals

Identify New Data Product Opportunities: Students will investigate three potential
areas for data product innovation:
Enhancing existing products by integrating analytics directly into them.
Developing new standalone data products for current customers.
Creating new standalone data products targeted at new market segments.
Develop a Business Case: Each team will establish a business case to justify the
investment in their proposed data products. This includes market analysis, potential
ROI, and strategic alignment with PCMI’s objectives.
P&L Model Development: Over the course of the project, students will build a profit
and loss (P&L) model for the proposed data products, detailing anticipated revenue,
cost, and margin scenarios.
Identify Data Augmentation Partners: Teams will research and propose potential
partners for data augmentation to enhance the value of PCMI’s data products.
Requirements and Solution Design: Students will develop detailed requirements for the
approved new data products and collaborate with the PCMI RDR (Research,
Development, and Requirements) team on the solution design.
Development Backlog Creation: Following Minimum Viable Product (MVP) best
practices, students will create a development backlog for a PCMI development team to
execute.

Expected Outcomes

A portfolio of new data product ideas fully explored and documented.
Comprehensive business cases supporting further investment in new products.
A robust P&L model for each proposed product.

Deliverables

Final report detailing research findings, business cases, P&L models, and product
requirements.
Presentation to PCMI stakeholders showcasing proposed data products and strategic
insights.
Development backlog ready for implementation by PCMI’s development team.

Evaluation

Quality and innovation of data product ideas.
Feasibility and thoroughness of the business cases.
Practicality and detail in the P&L models and development plans.
Engagement with potential data augmentation partners and early adopters.

This project proposal offers a unique opportunity for students to apply their academic knowledge to real-world challenges, fostering innovation and strategic thinking in the development of new data products at PCMI.

Supervisor: Zhiyu Quan