Product and Experience Design

THE OPPORTUNITY

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THE APPROACH

  1. Customer Journey Mapping: I led the creation of seven multidimensional customer journey maps, documenting ideal-state customer journeys across the Learn, Buy, Get, Use, Pay, and

THE RESULTS

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Journey Map Sample

“You showed genuine empathy for customers and relentlessly represented them in shaping our product vision.”

“I really love the way you approach design problems, coming out with thoughtful solutions also under very tight deadlines.”

Driving digital transformation in hospice Care by designing the entire lifecycle from onboarding to end-of-life.

Employee onboarding: New product partnership with ServiceNow.

Redesigning and optimizing the retail bank experience and employee tools.

Improving Quality of Life for Caregivers and Family Members During End-of-Life Care

Example Service Blueprint and Journey Map

Additional Examples

Optimizing Energy Extraction Platforms Using AI/ML for a Global Energy Leader

THE OPPORTUNITY

A global energy firm faced challenges in optimizing the selection process for its energy extraction platforms. The existing process was manual, time-consuming, and prone to errors, leading to suboptimal decision-making, bloated development costs, and lost extraction volume.

Utilizing novel AI/ML models, the goal was to reduce the time required for selection, improve decision-making accuracy, lower operational costs, and maximize profit.

THE RESULTS

Efficiency Gains: The time required for platform design was reduced by 40%, allowing quicker decision-making and project initiation.

Cost Reduction: The optimized selection process contributed to a projected 15% reduction in development costs by ensuring the right platforms were chosen for each project.

Accuracy and Confidence: Stakeholders expressed increased confidence in the data-driven recommendations provided by the AI/ML system.

Using AI/ML to Ensure Maintenance Dollars are Allocated to Minimize Risk and Increase Public Safety

THE OPPORTUNITY

Pacific Gas and Electric (PG&E) faced challenges in optimizing their annual maintenance budgets, which are crucial for ensuring public safety and minimizing risks associated with infrastructure failures. The traditional budgeting process was manual and lacked precision, leading to potential overspending in low-risk areas and underspending in critical high-risk zones.

The task was to optimize the allocation of maintenance budgets to maximize risk reduction and enhance public safety. The solution needed to prioritize resources effectively, focusing on areas with the highest potential impact.

THE RESULTS

Enhanced Public Safety: By prioritizing high-risk areas, the project reduced the likelihood of incidents by a projected 32%.

Cost Efficiency: The optimized budget allocations led to a more efficient use of resources, with an estimated 20% improvement in cost-effectiveness by focusing on spending where it was most needed.

Data-Driven Decision Making: Integrating AI/ML tools provided PG&E with a robust, data-driven approach to budgeting, increasing transparency and confidence in their maintenance planning processes.