Fragmented readiness data
Operational information was distributed across programs, systems, and planning cycles, and the scope and requirements were undefined when the work began.
DOD · MISSION READINESS · PREDICTIVE MODELING
From readiness data to mission foresight.
Designing the first predictive modeling framework for a defense organization making complex operational signals clear enough to guide planning, maintenance, and confident action.
EXECUTIVE SUMMARY
Mission readiness required a shared view forward.
A defense organization needed its first predictive modeling framework: an analytics ecosystem able to surface resource gaps, support maintenance planning, and bring greater precision to readiness decisions.
I helped translate high-volume operational data into an experience that analysts, planners, and leaders could use together to assess readiness scenarios and plan toward sustainability goals.
01 · THE CHALLENGE
Readiness data existed. The ability to test what comes next did not.
Reactive decisions
Maintenance and logistics decisions often followed issues rather than anticipating them.
Technical complexity
Advanced modeling had to remain understandable to people in distinct roles and across multiple operational and classification levels, while supporting real-time accuracy and a defensible audit record.
High consequence
A small, specialized, zero-fail fleet meant sparse, high-impact data, where one asset's status could ripple across the whole readiness picture. Every insight needed to support confident, accountable mission planning.
02 · THE EXPERIENCE MODEL
Make prediction understandable.
The framework connected the evidence beneath a readiness signal with the decision it could support—turning data science into a clear operational conversation.
Start with the work
Ground predictive views in the real decisions analysts and planners must make.
Show the route to insight
Make assumptions, inputs, and confidence visible rather than treating the model as a black box.
Scale a shared language
Give data science, operations, and leadership a common way to discuss readiness.
02 · THE PRODUCT VISION
A customized ServiceNow Suite for financial intelligence.
The platform brought configuration, analysis, evidence, and collaboration into one governed environment, helping people move from finding information to acting on it. Answers drew on an on-premises, fine-tuned, domain-specific language model and retrieval across more than a decade of source material, so sensitive data stayed inside the organization’s boundary.
Intake
Capture budget requests and funding needs in a consistent workflow.
Monitor
See how funds are allocated and available as plans change.
Track over time
Follow spend against funding timelines and budget-specific rules.
Visualize
Compare financial information to support clearer portfolio decisions.
One consistent view across three distinct budgets
- Operating O&M
- Capital investment DME
- Working capital Distinct funding rules and timelines
Agency financial views
A broader financial view designed to serve as a consistent standard across the agency and its bureaus.
Vendor support
Vendor management built on the same layouts, connecting contract and spend context to the portfolio view.
Delivered as part of a custom ServiceNow engagement for a federal civilian agency. Client CUI details withheld.
03 · FROM INSIGHT TO IMPACT
Research, design, and delivery moved as one.
Understand mission work
Led weekly interviews and collaborative workshops to map workflows, priorities, and readiness pain points.
Make prediction usable
Tested visual and interaction models, moving from divergent concepts to high-polish prototypes.
Set the foundation
Coordinated specifications and design governance for scalable predictive capabilities.
KEY NUMBERS · MISSION READINESS 2025
Three months a readiness model the client wanted to build on.
What this established
The work established a new predictive framework for mission readiness, making complex signals easier for mission users to act on. It also created a foundation for future predictive and AI systems while strengthening collaboration across data, design, and engineering. The client responded so positively to the design direction that it became the gold standard for additional readiness work across the branch, prompting conversations about the funding and requirements needed to move forward.
Discovery
Gold standard
Funding discussions
Figures above reflect program scope and observed outcomes where available. Underlying data sources were classified and outside the design team's view. Delivered for a U.S. military branch. Client and program details withheld.
TAKEAWAY
Predictive systems matter when people can use foresight with confidence.
Human-centered design keeps advanced analytics tied to the decisions, tradeoffs, and mission realities that give it value.