- Improve overall supply chain efficiency
- Enable demand and supply managers to enhance demand forecasting
- Optimize inventory management and resource planning
- Empower informed, data-driven decisions that drive cost savings and performance
Defining UX for scalable, data-driven demand forecasting
To boost supply chain efficiency, I interviewed six demand planners from companies like Philips and Novartis to uncover forecasting and inventory challenges. The insights shaped a detailed persona capturing their needs and goals.
The insights gathered from customer interviews helped identify opportunities to enhance their processes and support better decision-making.
I facilitated a design thinking workshop with 3 PMs, 2 Principal Engineers, 2 Senior Engineers, and 4 Engineering Managers across 4 work streams - data lake, forecasting, collaboration, and setup. This helped bring customer insights, AWS legacy systems, and canonical data model together, forming the foundation for both UX and technical architecture.
I created early wireframes to visualize how customers would onboard, set up a demand plan, add their data for models to predict forecasted demand, analyze forecasts on visually rich dashboards, and manually override demand when needed.
The team worked on their respective work streams while I developed high-fidelity designs. I presented the narrative to Peter De Santis, SVP of AWS, and his leadership team, addressed feedback, and advocated to expand the design team to meet launch timelines.
I partnered with my PM to brainstorm Forecast Adoption Rate and Planner Engagement Rate as a key signal of how seamlessly our UX enables users to trust, understand, and consistently use the forecast. Apart from these, Forecast Accuracy metrics (MAPE, WAPE and Bias) ensured forecast quality from an engineering persepctive.
I collaborated closely with Amazon Connect and Central AWS UX teams to align on design language and patterns. I built on foundational patterns from Cloudscape Design System while iterating on new ones.
While the individual work streams started functional development with the wireframes, the final designs and specs helped them execute the front end for the workflows.
While the sales team presented demos to companies under NDA, I facilitated 1:1 task-based studies with Amazon.com, Fabric.com, Philips, and Novartis. Key enhancements included locking periods for configuration, forecasting method selection, and bulk overrides with cascading across product hierarchies.
The hierarchical overrides concept, which emerged from our information architecture work, earned an approved patent. This innovation enhances flexibility and control in complex supply chain systems.
Through this experience, I learned how to break down complex problems into manageable parts, design scalable solutions, and think beyond immediate challenges. Embracing a systems-thinking approach helped me understand how individual components interact within a larger framework, ensuring sustainable and impactful outcomes.
I'm always open to discussing new opportunities, collaborations, or just chatting about design. Feel free to reach out!
divs.hariharan@gmail.com
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