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

1. 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.
2. 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.
3. 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.
4. Identify Data Augmentation Partners: Teams will research and propose potential partners for data augmentation to enhance the value of PCMI’s data products.
5. 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.
6. 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