From instinct to insight: How Chef David Jiang cut breakfast leftovers by 67%

After 32 years in the kitchen, David Jiang, Executive Chef and Food & Beverage Manager at Aloft Shanghai Hongqiao, knows the value of experience. But since using Winnow Foresight, he has also seen how technology can complement that knowledge, helping chefs make more informed decisions about what food to prepare and in what quantities, ultimately reducing food waste.

David has spent the past 10 years as an Executive Chef and today oversees both kitchen and restaurant operations at Aloft Shanghai Hongqiao. Since implementing Winnow Foresight in June 2026, Aloft Shanghai Hongqiao has reduced food waste per cover by 67% across its breakfast operation.

For David, that reduction represents more than an operational result. Having seen living standards improve in China over the course of his career, he believes there is a growing responsibility to use food and resources more carefully. He is particularly conscious of the contrast between food being discarded while people around the world still struggle to access enough to eat. Winnow Foresight is helping David and his team act on that responsibility, using better data to prepare more accurately and waste less.

What is Winnow Foresight?

Winnow Foresight is an AI-powered food waste tracking and production planning tool designed to help focused-service hotels optimize production. Accessible on mobile, the system uses data to forecast production needs and help teams prepare more accurately.

From experience to evidence

Before using Winnow Foresight, breakfast production planning at Aloft Shanghai Hongqiao relied heavily on experience. The team would look at budgets, hotel occupancy and the number of guests with breakfast included in their stay. But those figures did not always reflect actual demand.

David notes that up to 10% of guests with breakfast included do not actually come to the buffet. Without more precise data, the kitchen would naturally prepare extra food as a buffer to make sure there was enough for everyone.

“Before, it was mainly based on our experience,” David said. “Without accurate data, we would prepare more than we needed because we were worried there wouldn’t be enough.”

Winnow Foresight gives the team another reference point. Historical data and AI-powered recommendations help them determine how much to prepare for the following day.

“The AI results are very reliable and can be used as a reference for what needs to be produced,” David said. For David, technology does not replace a chef’s judgment. It provides better information to support it.

Targeting overproduction item by item

The impact became visible quickly. In the first two months of using Winnow Foresight, Aloft Shanghai Hongqiao achieved a 67% reduction in food waste (g/cover).

Some of the biggest reductions in overproduction were:

- Fried noodles: 83% reduction in leftovers
- Chinese cabbage: 78% reduction in leftovers
- Winter melon: 73% reduction in leftovers

Seeing performance at an individual-item level helps the team identify where they are preparing too much and adjust quantities accordingly.

But more accurate production planning is not only about preventing excess. It can also help the kitchen prepare enough of the items guests enjoy most. Data from Winnow Foresight, for example, helped the team identify white-fleshed dragon fruit as a popular breakfast choice. Better visibility into demand means the kitchen can plan sufficient quantities of popular items, helping to avoid stockouts while reducing unnecessary production elsewhere.

“For the items guests like, we can prepare more. For the items that are less popular, we can reduce the production,” David said.

The team has also observed growing interest in healthier options, including a preference for chicken-based sausages over more traditional pork varieties. Combining these insights with direct guest feedback helps the kitchen continue refining production.

The goal is straightforward: prepare less of what guests leave behind and enough of what they enjoy.

Saving time in a busy kitchen

For the team at Aloft Shanghai Hongqiao, another practical benefit of Winnow Foresight is how easily it fits into the daily routine. The team can review the recommendations and build a clear production plan for the next breakfast service, helping chefs prepare more accurately while freeing up time for other priorities.

More accurate planning also supports efficiency across the operation. Rather than preparing larger quantities of every item as a precaution, the team can focus its time, ingredients and resources according to expected demand. David says breakfast food costs have also decreased since Winnow Foresight was introduced.

Where AI and experience come together

After more than three decades as a chef, David could rely entirely on instinct. Instead, his advice to other chefs is to embrace technology and use it alongside the experience they already have.

“Ultimately, you use AI and experience together to make the judgment,” David said.

For David, the takeaway is not about choosing between technology and experience. It is about using both. Better data gives chefs another tool to make the knowledge they have built over years in the kitchen even more effective.

The results at Aloft Shanghai Hongqiao show that this approach can deliver more than waste reduction alone. More accurate production planning can help control costs, improve kitchen efficiency and ensure there is enough of the food guests enjoy most.

For other chefs tackling food waste, David’s message is clear: embrace change and technology, learn from the data and use it to make the best judgments.