Design Strategist - Portfolio Level within IT Enterprise
As a Design Strategist at Duke Energy, I was embedded within an IT portfolio team to serve as a bridge between business and users. My role was to help teams identify and prioritize the right problems before work entered development, balancing Desirability, Viability, and Feasibility (DVF) across interconnected, data-focused products.
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This work supported Duke Energy’s broader digital transformation by ensuring decisions were evidence-informed, strategic, and human-centered from the start.
Portfolio Context within Enterprise IT
The IT portfolio I supported was responsible for a suite of products focused on organizing, mapping, and maintaining clean, reliable data for internal users across the business. While each product had its own roadmap, they were deeply interconnected in sharing data foundations, workflows, mental models, and occasionally resources.
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Because of this interconnectedness, decisions made within one product often had ripple effects across others. Yet planning and prioritization frequently happened at the individual product level. Without a shared portfolio-level understanding of user needs, the organization risked optimizing locally while missing systemic issues.
This created an opportunity for design strategy to operate at a higher altitude by connecting insights across products and shaping prioritization decisions at the portfolio level.
A shared strategy space used to connect discovery, DVF evaluation, journey mapping, and research insights across the portfolio
My Role
This was the work I was hired to do. As an embedded Design Strategist, I operated upstream, shaping how problems were defined before solutions were designed. My focus centered on Desirability: keeping users in the loop, validating assumptions early, and ensuring the team was investing in problems that truly mattered.
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Rather than supporting a single product team, I worked across the portfolio. I helped connect insights between initiatives, clarify shared problem statements, and embed DVF thinking into decision-making. My role was not to design individual features, but to strengthen how the organization decided what to build in the first place.
What was enabled:
A repeatable upstream process that kept users in the loop and created portfolio-level insight across products.
Upstream Problem Framing (DVF)
Framed work upstream using a DVF lens so teams aligned early on what “success” meant and which assumptions needed testing. This clarified desirability before investment, reduced downstream rework, and strengthened portfolio-level prioritization.
UserZoom Studies to Validate Desirability
Led multiple UserZoom studies across products and user types, using research not just to test interfaces, but to validate whether we were solving the right problems in the first place. Included unmoderated think-aloud sessions to capture how users reasoned through workflows.
Dovetail Synthesis = Enterprise Insight
Analyzed think-aloud data in Dovetail to identify patterns across studies and translate findings into portfolio-level insight. Rather than isolated usability findings, synthesis revealed shared workflow breakdowns, mental model gaps, and repeat friction points spanning multiple products.
Approach
I approached this work as decision infrastructure. Instead of optimizing downstream execution, I focused on creating an upstream, repeatable process that helped teams frame the right problems, form stronger hypotheses, and use evidence ( both qualitative and quantitative) to prioritize across interconnected products.
Enablers
The conditions that enabled adoption and sustained use.
Collaboration
Partnered closely with our analyst and product leadership to connect qualitative research with quantitative product signals. This closed the loop between discovery and prioritization, helping the business form stronger hypotheses, build more compelling DVF cases, and make portfolio decisions grounded in evidence rather than assumptions.
Supporting Tools
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Miro: Central strategy space for journey maps, DVF evaluation, interview notes, and synthesis across initiatives
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UserZoom: Unmoderated and survey-based studies to benchmark usability and validate desirability across user groups
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Dovetail: Think-aloud analysis and structured synthesis to translate qualitative data into cross-product patterns and insights
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Analytics partnership: Quantitative signals used alongside qualitative findings to strengthen hypotheses and investment decisions
Outcomes
Improved prioritization clarity: Teams aligned earlier on what mattered most to users, reducing downstream churn and accelerating decision making.
​Higher-quality hypotheses and business cases: Decisions were supported by evidence from research + analytics, not just stakeholder assumptions.
​Portfolio-level insight (not isolated findings): Patterns across studies revealed shared workflow and mental model issues spanning multiple products.
Greater decision confidence: Leaders gained visibility into why work was prioritized, increasing trust and alignment across the portfolio.
Reflection
This work reinforced design strategy as decision infrastructure and not just solution design. By implementing an upstream process and pairing UserZoom research with Dovetail synthesis and quantitative signals, I helped the portfolio move from fragmented discovery to a shared, human-centered understanding of not just what to build, but the 'why'. The result was not a single artifact, but a repeatable way of working that strengthened prioritization, reduced risk, and kept users meaningfully involved across interconnected products.