Case study · 01 / 02
Redesigning a supply chain forecasting platform
Stemly uses machine learning to help supply chain and finance teams forecast and plan. We replaced a dated enterprise tool with one that people find easy to use.
Product DesignUser ResearchUsability TestingProduct Management
DesignResearchSpecsResult
01 · Research
A dated platform
Most enterprise tools in supply chain are old. They are hard to change, slow to react to what happens in the business, and their workflows are so complicated that people struggle to make decisions with them.
DesignResearchSpecsResult
02 · Design
No shared picture
- Different mental modelsEveryone on the team pictured the product structure differently, and we used industry terms in different ways.
- Complicated workflowsThe data science steps behind each forecast were hard to simplify without losing what users needed.
DesignResearchSpecsResult
03 · Result
What we did
Three things helped most:
- Fast prototypesWe could change a design the same day, after an internal review or a call with a client.
- A shared glossaryWe wrote down the industry terms we used, so everyone meant the same thing.
- Readable charts and tablesWe spent the most time on the data views, so people could see what the numbers meant and what to do next.
DesignResearchSpecsResult
What changed
The new platform did better than the old systems it replaced.
More accurate forecasts than the old systems
Less time spent on each design round
Faster launch than we first planned
Fewer clicks for users
Higher user satisfaction
More productive, as reported by clients
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