Reduce food waste with smarter supply chain forecasting

If you’re learning there are more innovative ways to improve future sales forecasting, but you’re not sure where to start — this is for you! In this article, we’ll go through:

  • How costly poor forecasting is for fast casual and quick serve restaurants

  • The types of insights QSR companies are using to arrive at more accurate forecasts

  • How these accurate forecasts minimize surplus inventory, wastage disposal fees, and out-of-stocks

The high cost of inaccurate QSR forecasting

According to Restaurant Hospitality, the restaurant industry spends $25 billion every year on wasted food and overstocks as a result of inaccurate forecasts and poor foot traffic predictions. Working to prevent food waste can cut an individual restaurant’s costs by up to 6% — which is millions saved for a QSR. 

Key to reducing these costs is the ability to understand each location’s environment, events taking place in that environment, and how these events impact demand on a daily basis.

For example, locations near sporting venues need to know not just that a game is happening, but they also need to understand the difference between how a game day vs. a non-game day impacts sales.

We recently found sports games driving a 25% increase in burger orders for one QSR. Aligning inventory and staffing ahead of time for these types of surges in demand can help you save big.

Sports games are only one kind of event — and for accurate forecasts, you need to know about all of the other types of events nearby that will compound or mitigate demand impact on game days.

External data strengthens restaurant forecast accuracy

While historical data is valuable, relying on it alone can lead to inaccurate forecasting, especially in a dynamic market. Only using first-party data forces restaurants to guess, or spend significant manual time attempting to fix their forecasts. And while managers can always call around to schedule more staff on a surprisingly busy day, having the right inventory for a demand surge is far more complex. For inventory, there is no quick fix — it takes accurate supply forecasting. 

Forecasting to prepare for the future is the foundation of all operational decisions in most successful restaurants — especially as many shift to constant, dynamic forecasting fueled by external intelligence that enables them to understand each restaurant’s context at scale.

What are you missing when you under or over forecast?

Relying on historical data alone is an issue for supply forecasting, especially given the past 2+ years of abnormal dining conditions. With hundreds of thousands of fresh food items at the mercy of your forecast accuracy every single day, guessing just won’t cut it anymore. 

Separately, under forecasting can lead to lost sales when you run out of an item, and can negatively impact your brand image. Reliability is a point of pride for many QSRs — when a customer turns up they should always be able to get their favorite menu item.

This reliability can also make or break customer loyalty. Studies show 30% of customers who experience out-of-stocks either buy nothing, or go buy a similar menu item elsewhere (Source). Avoid losing customers entirely with better forecasts that simplify the balancing act between being properly stocked minimizing food waste.

When you know what will drive demand, you can align your forecasts to avoid overstocked stores, expensive wastage disposal costs, and extra shipping fees to manage overstocks or under-stocks.

What are important inputs for improving forecast accuracy for supply chains?

For any existing supply chain forecast or model, the right external intelligence enables you to improve your forecast either through manual adjustments, or by training your forecasts. 

Some of the factors that influence demand — such as the weather, time of year, and events — can be factored in your forecasts to better match supply to demand. The question then becomes: what data or intelligence inputs are most important for understanding demand?

The good news is, you don’t need to be a data scientist to answer this question. You just need to have a pulse on what’s happening around your stores. Incorporating factors that are driving demand is key and often overlooked - factors such as school holidays, severe weather or festivals and concerts happening near or around your stores. For example:

  • There are 13,000 school districts in the US, each with potentially different spring and summer breaks. Understanding how different school calendars affect demand as families go on vacation is crucial for your restaurant locations that are near schools. 

  • Hurricanes and tornadoes can cause serious damage across multiple states. Understanding the exact area affected is important for understanding how your labor needs may shift & what locations will experience lower levels of demand.

  • Festivals and concerts drive hungry attendees through your doors before and after the show. Understanding the start and end time of a nearby Rolling Stones concert in Austin can help you understand which nearby locations will see demand surges before and after the show for better inventory and supply management. Discover more about how to use events to improve inventory management.

We’ve partnered with some of the top SCM tools to improve your accuracy even further. If you don’t own your own forecasts, but leverage forecasting tools like Blue Yonder or Antuit, see our partnerships here.