Demand-based ordering (DBO): How AI can benefit inventory planning

Demand-based ordering is a tough nut to crack. 

Fail to do it correctly, and your inventory management can take a hit. You can over-order ingredients, wasting money on food you never get the chance to use. Or you could under-order ingredients, failing to meet customer demand. 

Either way, it’s not good for business. 

So how can you improve demand-based ordering to reduce costs and increase profit margins? 

The trick is using the right technology, which is where AI comes into the picture. Don’t worry — it’s not as scary or technical as it sounds! 

In this article, we walk you through how AI is the driving force behind successful demand-based ordering. And more importantly, we show you how to use AI effectively.

First things first, what is demand-based ordering?

Demand-based ordering (DBO) involves ordering ingredients and menu items to meet customer demand. 

For example, if you have a busy restaurant every Saturday night, you order more ingredients to meet the increased demand. On the flip side, you might also order less food if you have a quiet period. 

When demand-based ordering is successful, it’s great for business. It ensures your inventory management is as efficient as possible, keeping your costs in check, minimising your food waste, and storing enough ingredients to meet customer demand at any given time.

Nory success story 🥳 See how Harsthorn – Hook used Nory’s real-time inventory insights to get better control over food costs  — and minimise food waste in the process.

“Nory’s insights mean we can make informed decisions because we know exactly where the business is at. This has been the most important thing as we guide our business into growth.”

George Hartshorn, Food & Beverage Director at Harsthorn – Hook
Nory demand-based ordering on the mobile app

Why is demand-based ordering better than traditional inventory methods of inventory planning? 

Traditional inventory planning methods make it hard to accurately predict demand. Think about a fixed ordering schedule as an example. Every week you order the same items, regardless of how many people are dining in your restaurant. 

But what about when customer demand changes? 

If the weather is terrible, for example, you might not get as many walk-ins. So what happens to the food you’ve ordered? Chances are, it’ll go to waste before you have a chance to use it. 

Or what about if there’s a popular event nearby? You could get more customers than expected, and not have enough in the inventory to meet demand. As a result, you’ll be turning customers away when you could have been making more money. 

This is where demand-based ordering is helpful, and particularly when it’s powered by AI. It takes these external factors into account, helping you accurately predict how much food you need for any given shift. 

Now, let’s look at AI in a bit more detail. 

How does AI enhance demand-based ordering? 

Artificial intelligence (AI) adds another layer of functionality to demand-based ordering. 

It analyses large amounts of historical data alongside external factors (like weather, holidays, and events) to predict future demand. Over time, it learns more and more about your restaurant and where the demand is highest. 

By analysing these patterns and trends, an AI-powered system can automatically adjust ordering quantities in your demand-based ordering system. This means you can match anticipated demand in real-time.

Let’s walk through a couple of the key elements of AI in demand-based ordering. 

Predictive analytics for accurate forecasting 

Predictive analytics uses historical data and machine learning algorithms to make informed predictions and accurate forecasts.

For example, let’s say that predictive data shows that the most popular menu item on Fridays is a cheeseburger. As a result, you might increase your inventory list to include more cheeseburger ingredients for this particular day. 

Plate of nachos and a drink in a restaurant

But how exactly does predictive analytics work?

It gathers data from various sources, including sales data, profit margins, and customer demographics. Then, the system cleans and analyses the data to make predictions about future demand and forecasts.

The quality of data plays a crucial role in how accurate the predictions are. There’s only so much predictive analytics can do with out-of-date or inaccurate information. That’s why it’s so important to use systems that accurately track sales and performance, like Nory

Take a look at Masa as an example. The restaurant accurately forecasts sales within a margin of 3% using Nory’s AI-powered restaurant management system. 

“Constantly being able to see what your sales are, what your cost of labour is — and trusting that is really valuable.”

Shane Gleeson, owner and founder at Masa

Machine learning for continuous improvement

Machine learning involves technology mimicking human behaviour. Don’t worry, it’s not as creepy as it sounds! 

It essentially means that the system uses algorithms to perform complex tasks that are usually completed by humans. For demand-based ordering, this includes understanding previous menu sales to order the correct amount of food in the future. 

Over time, the system evolves and learns more about your sales and performance. Then, it adjusts to patterns and optimises your orders accordingly. These types of adaptive learning systems make inventory management more efficient, ensuring you order the optimal amount of inventory and schedule the right number of staff to meet demand. 

Benefits of using Nory to improve your demand-based ordering 

Nory’s AI-driven software allows restaurants to predict customer demand and order inventory accordingly. But don’t just take our word for it! Here’s how other restaurants use our platform.

Use real-time data 

Nory measures, analyses, and displays real-time data. This means you can instantly see how you’re performing and make quick decisions about inventory planning, including ways to:

  • Reduce costs
  • Minimise food waste
  • Improve operational efficiency 

Take a look at Pasta Cosa as an example. Now that they have real-time access to sales and performance data, they can make instant, informed, and strategic decisions about inventory management (as well as other areas of the business). 

“Implementing Nory revolutionised our operations. The real-time data allows us to make informed decisions about labour costs, scheduling, and inventory management.”

Kayleigh Baccine, Co-owner at Pasta Cosa

Integrate with other systems

To streamline operations across the business, Nory integrates with existing ePOS systems like Toast and Vita Moja. With a single glance, you can see where you’re performing well and where you can make improvements to boost revenue and cut costs. 

Plus, it helps you make smart decisions about your inventory management. 

Griolladh is a good example here. The growing franchise integrated Nory with Toast, gaining visibility and control of its expanding operations. This visibility was vital as the business scaled, enabling them to effectively forecast sales and manage inventory costs. 

“Nory has been with us every step of the way. It’s been incredibly helpful to the business, and has played pivotal role in the successful franchising of Griolladh.”

Jacob Long, Co-founder at Griolladh
Nory inventory management dashboard on desktop and mobile

Access ongoing training and support

To make the most out of an AI-powered system, you need to know how to use it effectively. 

This means receiving onboarding support, training, and guidance to ensure you know how to use the system to its full capacity. 

This is exactly what we do at Nory. In fact, ongoing support is something we’re pretty passionate about. We want all of our users to be confident and able to use our software effectively. 

Adam Jefferies, Head of Operations at Clean Kitchen, talks about his experience with Nory’s support: 

“The team was really supportive. Being able to just drop a note anytime I needed it and jump on the call immediately was great. It was good to get that sort of flexibility from the Nory team.”

Use Nory to implement AI-driven demand-based ordering

With the right technology, demand-based ordering can improve your entire bottom line. It can prevent overspending, improve labour scheduling, and optimise your inventory management to meet customer demand. 

If you want to take the leap into AI-driven DBO, reach out to the team at Nory. We can talk you through how it works and answer any questions you have.

Want to learn more?

Check out our walkthrough of Nory to see how we can help your business thrive

See Nory in action

FAQs about demand-based ordering systems

What is a demand forecasting system?

A demand forecasting system is another word for a demand-based ordering system. It predicts future demand for your restaurant based on historical data, trends, and any other external factors. 

What is supply order vs demand order?

Unlike demand ordering, supply ordering involves replenishing your inventory based on predetermined schedules. This type of inventory management can make it hard to meet customer demand, particularly if you have a busy day but not enough stock on the shelves. 

Can you use demand-based ordering for a central production unit (CPU)?

You certainly can! It works similarly to a normal restaurant, but it analyses all the venues at the same time. The system reviews data from each location before making adjustments for the food order to be sent to the CPU.