Research Program That Changed How We Ship
Research Program, UX Research
My Work
Rebuilding Trust in an AI-Driven
Discovery, Mixed Methods Research, UX Research
UX Audit-Case Study
Enterprise/Mainframe, UX Research
User Journey Mapping
User Journeys, UX Research
Protected: Quantitative Research to Drive Go-To-Market (GTM) Strategy
Quant Research, Research Program
Approach
Set direction and connect to business goals
- Align research initiatives with the organization’s digital transformation and mainframe modernization goals.
- Translate high-level business objectives (e.g., operational resilience, compliance, reliability) into actionable UX research plans.
- Ensure research supports the adoption of AIOps and agentic AI by focusing on user needs and business impact.
- Continuously connect research insights to evolving business strategies and technology roadmaps.
Secure support and clarify priorities
- Engage IT, business, and compliance stakeholders early to clarify research priorities and success metrics.
- Facilitate workshops and interviews to identify pain points and opportunities in the adoption of mainframe and AI technologies.
- Communicate research value by linking user insights to business outcomes (e.g., reduced downtime, improved efficiency).
- Build consensus and secure ongoing support for research-driven innovation.
Embed research into culture and processes
- Establish standardized research processes and integrate them into agile development cycles.
- Advocate for a user-centred, AI-first mindset across mainframe modernization initiatives.
- Develop frameworks to ensure research findings are systematically applied to product and process improvements.
- Promote continuous learning by embedding research touchpoints throughout the solution lifecycle.
Plan, execute, and manage research activities
- Planned, executed, and oversaw end-to-end research programs across mainframe and AI user journeys.
- Coordinate cross-team efforts to ensure timely and relevant research deliverables are produced.
- Track progress and impact of research activities using clear KPIs and feedback loops.
- Adapt research plans in response to stakeholder needs, technology shifts, and organizational priorities.
Ensure insights are shared and drive organizational action
- Combine mainframe engineers, AI/ML experts, IT operations, and business stakeholders to co-create effective solutions.
- Promote knowledge sharing with syncs, documentation, and platforms for accessible research and user feedback.
- Integrate UX research into workflows for informed decisions, enhancing reliability and user experience across teams.
- Align diverse teams to drive innovation and improve AIOps and agentic AI in mainframes.
Clarify objectives and focus the research.
- Collaborate with stakeholders to identify and prioritize critical challenges in AIOps and agentic AI adoption.
- Frame research questions around trust, explainability, and user experience in mainframe contexts.
- Ensure the research scope encompasses both technical and human factors that influence solution success.
- Establish clear objectives to guide focused and impactful research efforts.
Select methods and plan logistics.
- Select appropriate qualitative and quantitative methods (e.g., contextual inquiry, usability testing, analytics).
- Design studies to capture the needs of mainframe operators, developers, and business users.
- Plan logistics for research in complex, high-security enterprise environments.
- Ensure research design accommodates both legacy workflows and new AI-driven processes.
Execute research and gather information.
- Conduct interviews, observations, and surveys with mainframe and IT operations staff.
- Gather real-world feedback on AI-driven automation, agentic workflows, and incident management.
- Capture data across routine and high-impact scenarios to ensure comprehensive understanding.
- Use secure, compliant methods to protect sensitive enterprise information during research.
Interpret data to generate insights.
- Synthesize findings to identify patterns in user behaviour and workflow challenges.
- Uncover friction points in AI-human collaboration and automation trust.
- Assess the usability and effectiveness of agentic AI interfaces for mainframe tasks.
- Translate data into actionable insights that address both technical and business needs.
Present actionable results to stakeholders.
- Present insights through tailored reports, visualizations, and stakeholder workshops.
- Highlight recommendations for improving trust, transparency, and user adoption of AIOps solutions.
- Ensure findings are actionable and directly inform product and process enhancements.
- Foster ongoing dialogue with stakeholders to drive continuous improvement and innovation.
Connect
Connect to discover more.
Thank you for exploring my UX Research portfolio.
It gave you a meaningful glimpse into how I uncover insights, drive clarity, and bridge user needs with business strategy.
Think I might help?
I’m currently open to UX Research projects, consulting opportunities, and Lead or Principal roles within forward-thinking organizations.
Let’s connect — I’d love to learn about your challenges and explore how we can create impactful solutions together.