Product Design Lead
A SaaS product using AI to enable supply-chain distribution managers to anticipate and address supply chain problems before they arise
The global supply chain is hugely volatile, and when products aren’t available on the shelves when consumers want them, companies loose money. Inventory Flow uses machine learning to identify where the problem spots will occur, and automatically resolves financial risk by optimizing future product allocations and actions.
In order find the roots of this problem I had to better understand what the issues were. I met with Stakeholders within Noodle — from the product team to better understand the strategic direction of the app, as well as Enterprise Services who were closer to our customers and had an excellent understanding of their needs.
Additionally, I met with and researched our potential users, Distribution Planners at Enterprise companies. Finding these potential users was challenging because they needed very specific skill sets and institutional knowledge to understand the purpose and context of the application. Also, Distribution Planners come in many flavors, and so it was important to speak with Local Planners, Regional Planners, and Global Planners, to understand their specific needs.
I compiled the results of my research and narrowed it to the following list. While many other issues came to light in my research, these were the recurring items, and a small enough list that I could get the team behind it:
1.Too many clicks
2. Can’t compare different distribution plans or do scenario analysis
3. Accepting and rejecting stock transfers is far too slow
4. Can’t see task completion
5. No consistent underlying logic to navigation
Aside from these issues, the app had to be made more future proof with plans in place for features on the horizon.
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