System Design Case Study - Ford Data Model of The Future

I was the content architecture lead on a process change team of five. We were tasked with streamlining content management for Ford.com and Shop.Ford.com. With sophisticated data modeling, schema.org API utilization, and workflow optimization, we realized a seven-figure annual savings on operating costs and an improvement in both content quality and consistency.

Situation

Challenge #1

Ford Motors offers a tremendous variety of products at different price points and configurations, across many markets.

Challenge #2

Supporting content operations at Ford.com and Shop.Ford.com requires handling a variety of data sources and formats which are ingested, sanitized, normalized, and then made retrievable. 

Risks & Opportunities

• Disjointed and inconsistent content delivery systems reduce positive business outcomes.
• Supporting numerous data sources can lead to redundancies and data entry/translation errors. 
• Ford Motors is legally mandated to present individualized claims and disclosures on a per-product and per-market basis for the wide variety of geographic locations in which it operates.

Tasks & Goals

Primary Task

Develop a new content model that could support current operations on Ford.com and Shop.Ford.com in a scalable and extensible way for future products and initiatives. 

Secondary Tasks

• Revamp existing internal tooling
• Define new workflows
• Create documentation to support the process changes

Goals

An e-commerce platform that could efficiently ingest content data in the various formats needed and make it easily retrievable.

• Enhance the customer experience on the e-commerce platform
• Improve messaging consistency where needed while supporting granular marketing strategies
• Improve efficiencies in content operations

Action

Assessment & Planning

1. Audit existing marketing content and data structures.
2. Identify key stakeholders, including marketing, production engineering, IT, and data analytics teams, to gather requirements and insights.
3. Define the objectives and scope of the new content model project.

Data Model Design & Development

Collaborate with the IT and data analytics teams to design a new marketing content data model. The model incorporated metadata, taxonomies, and content hierarchies to facilitate easy content management and retrieval.

Implementation

1. Migrate existing marketing content into the new data model, ensuring minimal disruption to ongoing campaigns.
2. Develop and deploy automated tools for content tagging and metadata management.
3. Train marketing and content teams on the new data model, processes, and tools to ensure smooth adoption.

Testing & Iteration

1. Test to identify and resolve any issues with the new data model and associated process change.
2. Gather feedback from users and stakeholders and iterate.
3. Implement analytics tools to monitor content performance and user engagement.

Results

Efficiency Gains: Streamlined processes for creating, organizing, and retrieving marketing content reduced production spending by $500,000.

“Wow! This is going to save us five-hundred thousand dollars THIS QUARTER.”

-Project Director, Content Systems

Better Personalization: Enabled personalized marketing campaigns to increase user engagement and conversion rates.

Improved Consistency Across Touch Points: Ensured consistent messaging and branding across multiple e-commerce touchpoints, boosting business outcomes.

Scalability: Established a scalable data model and associated workflows and documentation to support future growth and integration with emerging technologies.

My Role

Content Architecture Lead

Timeline

Nine Months

Skills

• Data Modeling
• Automated Workflow Development
• Process Change Management
• User Experience Design
• Market Research
• Systems Design
• Multichannel Marketing
• Content Marketing

Tooling

• Adobe Experience Manager (AEM)
• Atlassian Confluence Platform
• Microsoft O365
  • Powerpoint
  • Excel
• Schema.org API
• JSON
• JAVA
• XML
• Adobe Digital Asset Manager (ADAM)