How Din Tai Fung Uses AI For a More Stable Supply Chain
Din Tai Fung is one of the most operationally demanding restaurant brands in the world. Running a supply chain at that standard takes more than discipline — it takes the right tools. Here's how Sightline OS helped their team drive an industry-leading proactive supply chain management strategy.
Xiao Long Bao, one of Din Tai Fung’s specialities.
Din Tai Fung is a globally recognized premium full service dining brand, known for having the highest Average Unit Volumes in the U.S. restaurant industry, with +$27MM average AUV per location. They are an iconic and fast-growing brand with several signature items, including xiao long bao, and a highly complex supply chain.
Din Tai Fung holds itself to an extraordinary standard — and their supply chain team is no exception. To meet that standard at scale, they needed proactive supply continuity risk detection and forecasting tools that could keep pace with their growth. Without them, maintaining service levels was consuming time that should have been spent on the strategic, business-enhancing work that actually moves the brand forward.
Within five months of implementing Sightline OS, Din Tai Fung reduced distributor out-of-stocks on their most critical SKUs by 25% by proactively identifying risks before they turned into stockouts — and saw a 13% reduction in out-of-stocks across all proprietary SKUs. Din Tai Fung achieves industry-leading distributor service levels, with a 99.7% fill rate across their proprietary products, preventing menu outages and lost sales.
“The team holds high standards, with a ‘never 86 a menu item’ mentality. I’m proud to uphold those standards too.” - Jason Lee, SVP Supply Chain & Manufacturing, Din Tai Fung
The dining room at Din Tai Fung, just before a bustling service
Sightline OS Products Loved by the Din Tai Fung Team
As Din Tai Fung scaled, it became clear they needed a foundation built to match their ambition. Their previous platform offered a retrospective view of operations, and leaning on distributors' internal buying systems meant working with data that couldn't keep pace with the precision their growing network demanded. To continue delivering at Din Tai Fung's standard, they needed tools that were as forward-looking as their growth.
Sightline OS’ AI-powered forecasting took the guess work out of production planning
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With no advanced planning software to support them, Din Tai Fung’s team was manually forecasting demand for proprietary items produced daily — leaning on simple models that wouldn't account for the full complexity of their operation. Avoiding over and under-production was a challenge, leaving teams at risk of waste and outages.
Historical averages and formula-based forecasting are no longer enough to protect the guest experience.
Sightline OS's AI-powered forecasting engine accounts for every variable needed to accurately predict supply risk — lead times, shelf life, ordering cadence, seasonality, and demand shifts — continuously learning from Din Tai Fung's own data to deliver forecasts that get more accurate over time, not less.
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Sightline's forecasting engine gave Din Tai Fung a reliable, data-driven production planning schedule for the first time. Instead of manually calculating demand, the team now works from a machine learning-powered forecast that continuously learns from their data and automatically incorporates seasonality and external factors — aligning supplier production with actual demand signals and reducing both over-production and shortfalls. The result was a 14% improvement in forecast accuracy over the course of Q1 2026.
Supply issue management happens in one place, allowing for efficiency and organization
“Sightline has helped our team improve forecasting accuracy, increase pricing transparency, and manage service issues more efficiently by bringing critical supply chain data into one platform.”
- Humza Syed, Senior Distribution Manager
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Shorts, subs, and supply disruptions were being tracked across spreadsheets. Every issue required manually rebuilding context, switching between tools, and chasing information that should have been in one place. It was slow, error-prone, and unsustainable at scale.
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Shorts, subs, and supply disruptions are now managed inside the Sightline platform. When an issue occurs, the team identifies it, understands the root cause, actions on it, and tracks resolution all within the same platform. The difference in speed and accuracy is significant — and so is the reduction in time the team spends on issues that used to consume their days.
A distributor transition that gave the team more visibility and ownership into their inventory
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During distributor transitions, new market ramp-ups, and new product launches, the team had limited visibility into inbound POs and DC inventory. They were flying blind at exactly the moments when visibility mattered most.
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When Din Tai Fung made a regional distribution transition, Sightline provided full visibility from day one — allowing the team to track supplier inbound purchase orders and inventory build-up prior to launch. The transition unlocked a new, higher-performing distributor relationship and gave the brand the confidence to execute the switch without losing visibility at any point in the process.
Sightline OS didn't just give Din Tai Fung better data — it gave them a different way of working. And the impact shows up across the supply chain in fill rates, recovered spend, hours the team gets back, and in new, proactive conversations with leadership.
ABOUT SIGHTLINE OS
Sightline OS is a supply chain platform purpose-built for restaurant chains — with AI--powered forecasting, inventory optimization, and COGS management designed for the pace and complexity of modern foodservice operations.
