I created the design vision for an Agentic AI Match Day Orchestrator, an AI-driven inventory intelligence concept designed to help Nike anticipate demand, protect revenue, and orchestrate real-time decisions around global sporting events. Working with data scientists, product managers, and executive stakeholders, I shaped a concept that translated signals and data into actionable SKU-level predictions.
Role
Product Design Lead
Organization
Accenture
Year
2026
The match-day intelligence dashboard turns revenue opportunities into active alerts, helping logistics teams understand where demand is accelerating, risk is emerging, and AI predictions are improving over time.
DEMAND FORECASTING
A focused alert experience that translates match-day demand signals into action, showing where revenue opportunity, predicted lift, stockout risk, and store impact are converging. The experience helps teams prioritize the locations and products most likely to need intervention.
DEMAND SIGNALS
Signal widgets provide the evidence behind a prediction. Together, these signals improve confidence and transform demand forecasting from a single number into a richer story of momentum, behavior, and opportunity.
I design prediction tools to help teams move from reactive to preventive, predictive, and prescriptive processes and opportunities.
WHAT IF ANALYSIS
A what-if engine for match-day decisions allows teams to model win, loss, or draw outcomes and understand how weather, sentiment, and team form may impact SKU demand.
INTELLIGENT DISCOVERY FRAMEWORK
A contextual learning layer that brings transparency to the system, helping users understand every KPI, formula, label, widget, and prediction without breaking their workflow.
