Turning Store-Level Data Into a Business Case for Renovation.
Role: Product Design, Independent Strategy Engagement
Team: Marcus Moya (Store Manager)
Timeline: 03/11/2026 - 06/12/2026
Project Overview.
The Tyler Avenue Starbucks had no clear picture of its own financial performance: labor costs, inventory shrink, and revenue patterns lived in disconnected systems, which made it impossible for the store manager to build a credible case for the renovation the location badly needed.
There was no design brief, no existing research, and no budget. This was an example of a real business problem and an invitation to help solve it.
I ran this as an independent strategy engagement. From raw data to a structured, evidence-backed recommendation report and treating financial and operational analysis as a design problem, I was able to turn fragmented numbers into a clear, decision-ready story for store leadership.
The Challenge.
Tyler Avenue was hindered by:
Fragmented financial data: Upper management lacked a clear picture of revenue streams, labor costs, and inventory patterns.
Operational inefficiencies: Broken systems, inadequate staffing, and outdated processes caused waste, bottlenecks, and delays.
Employee dissatisfaction: Unclear workflows and insufficient resources led to stress, burnout, and decreased performance.
Renovation advocacy: The store needed a comprehensive renovation to meet both operational and customer experience standards, but lacked clear, data-backed justification.
Objective: Provide clarity on financial performance, streamline operations, improve employee experience, and advocate for physical store improvements.
My Role.
I owned this project end-to-end as an independent product strategy engagement. My responsibilities included:
Firsthand observation of store operations to identify workflow bottlenecks
Stakeholder interviews with store partners to surface pain points
Analysis of financial and operational data provided by store management
Development of paper-based data visualizations to communicate findings clearly to store leadership
Delivery of a structured recommendations report to the store manager
Process & Approach.
Discovery & Research
Observed store operations firsthand to identify workflow bottlenecks and inefficiencies in real time
Interviewed store partners to surface pain points in daily workflows, staffing, and tools
Analyzed financial and operational data provided by store management, including revenue, labor, inventory, and shrink patterns
Analysis & Synthesis
Mapped findings to identify the highest-impact operational pain points
Applied product and design thinking to translate raw data into clear, decision-ready problem statements
Developed paper-based visualizations to communicate complex financial patterns in a format accessible to store leadership
Recommendation Development
Prioritized recommendations based on feasibility, impact, and alignment with store leadership's goals
Structured findings into a clear report for the store manager, covering workflow improvements, staffing efficiency, and renovation justification
Framed renovation needs with data-backed rationale to support escalation to district management
The Tradeoff.
With no existing dashboards or tools, I chose to hand-build data visualizations rather than wait for a proper reporting tool. I chose a paper-based approach that traded polish for speed, since store leadership needed something they could act on immediately rather than a perfect system months later.
Impact & Status.
Quantified inefficiencies across labor, inventory, and process pointed to an estimated recoverable cost of $50,000 - $250,000+ annually, depending on implementation scale and adoption
The renovation itself was ultimately not pursued once it surfaced that Starbucks leases rather than owns the Tyler Avenue location, a real estate constraint outside the scope of the original engagement
The non-renovation recommendations (labor, inventory, workflow) remain actionable, independent of that finding
Reflection.
This project also reinforced a lesson that goes beyond design craft: even a well-evidenced recommendation can run into constraints that have nothing to do with the analysis itself. Surfacing the lease structure early would have let us scope the engagement more precisely from the start, which is a reminder to map organizational and structural constraints (ownership, contracts, lease terms) alongside user and operational research, not after.