How Food Businesses Can Use Predictive Ordering to Boost Their Bottom Lines

Predictive ordering is the latest in the line of innovation in business technology. Predictive ordering software uses data on purchasing histories including order frequencies and similarities between different orders to automatically execute purchase orders. Although predictive software doesn’t execute orders itself, it reduces the time in executing orders. If you automate predictive ordering, you can eliminate the need for excessive human resource and introduce previously unrealized cost advantages.

With the growth of E-commerce in the food industry, the market has been flooded with unprecedented demand. The Australian food and beverage market generated revenues of over $350 billion and exported goods worth $36.1billion in 2018. As the industry continues to grow, all food business owners have begun to feel the pressures of rising demand. Businesses can only capitalise on these profit potentials if they can cope with the rising demand and many businesses are using predictive ordering to improve business efficiency. Business surveys point out the following facts about the importance and effectiveness of predictive ordering:

  • 86% of all companies working with predictive analytics for the past two years experienced increased ROIs across business functions.
  • 8% of all companies plan to invest in predictive analytics and predictive ordering capabilities to improve business capabilities.

Clearly, predictive ordering is central to order processing automation and will guarantee efficiency improvements.

How Does Predictive Ordering Work?

Let’s say you have a client who has a set amount of products that they order periodically. You can use predictive ordering to create customer specific shopping lists to make it easier for them to place orders.

Predictive Ordering

All that the customer does is choose the option to place the order and the user end OMS will place the order from them. The OMS at your end will handle all the invoicing, receipt creations and will mobilise the respective resources to fulfil the order. The back and forth between the two ends of the OMS will make sure that inventories are periodically replenished.

Does OMS Allow Predictive Ordering?

We’ve come a long way from where we once were with dedicated order management software. Many OMSs, OrderTron included, are built with order history tracking functions that can easily be used to automate ordering procedures. If a long-time customer keeps placing the same orders you could set up a notification for yourself or use the push notification functions in the OMS to inform them to place the order. This isn’t exactly order processing in the way that the OMS itself places an order; but rather a way to streamline order management on both ends of the supply chain.

Once you begin to pre-empt client orders, offer them pre-set packages of goods to order from, then you’ll automatically offer them better services. The client won’t have to periodically customise their orders and you won’t have to especially prepare those orders each time an order is placed. If a client orders a hundred units of a certain products at a certain time in the month, then you could just ship out a pre-prepared package the minute you receive the order.

How Do You Effectively Use Predictive Ordering?

There are multiple ways to use predictive ordering depending on how your client circles are organised. OMS systems allow business owners to categorise orders according to the size of the orders, the companies which place to orders and even according to the contents of the order.  The reporting tools offered by OMS can also tell business owners how frequently a client places an order, what the sizes of the order are and where the orders are shipped.

Food Businesses

You can use the information and tools provided by your OMS to effectively categorise to your orders and automate them to take advantage of predictive ordering. Some metrics you can use to implement predictive ordering are:

Frequency of Orders

When your clients plan out their inventories, they place orders based on how long their inventories will last or what is the most economical inventory level at any given time. There isn’t a uniform timeline for inventory cycles or an economic inventory level, however clients do have a fixed inventory cycle and fixed economical inventory levels.

Going through any client’s order history will tell you when exactly any given client places an order and whether it’s the same supplies each time. You could schedule a push notification to be delivered to your clients and prepare their orders beforehand. As you pre-empt client orders and remind them to restock, you will be better prepared to cater to their needs. Furthermore, using this basic predictive model, you can also reduce the time it takes to ship the product.

Type of Product

OMS systems also let you categorise clients based on the products they usually order. If you categorise clients according to the products that they typically order, you’ll find it easier to automate their ordering processes. If you’re serving multiple grocery stores, then the odds are that each store orders the same goods as the next. If you can identify similarities across ordered products, you can then identify inventory cycle lengths.

You should filter out your clients by the sort of products that each orders and then set-up notifications either for yourself or for them to fulfil their orders in a timely manner.

Categorising By Location

If you want to be a little versatile, then you can also filter clients out by the areas they operate in. If ten of your clients work in the same area, then it might also be possible to send out notifications to reorder or send out their orders together. A client’s location could serve as a potential metric that helps you determine their inventory cycles and then organise your products accordingly.

Predictive Analytics: Marketing Potentials 

Amazon has made quite a name for itself through its predictive analytics. The company uses a form of associative marketing where it suggests products that were also bought by people making similar purchases. To achieve successful predictive analytics, Amazon matched people with overlapping purchasing decisions to bring everyone on to the purchasing choices. Think of it like this, if you order a pair of shoes as someone and the other person also orders a pair of socks with the shoes, then Amazon will suggest that you buy the same socks.

Amazon’s software identifies one consumer’s purchases to make similar suggestions to others on the off-chance that they can get another sale through the website. You could possibly follow the same route to create marketing potentials for other products in your stock. You could create consumer profiles based on similarities in their market niche and their order requirements. You could then make suggestions to your clients to buy certain products that other clients are buying, given that the other clients have similar purchasing habits, to increase sales potentials for all of your products.

How Will Predictive Ordering and Analytics Help You?

Predictive ordering and analytics help businesses on two separate tiers:

  • Improving order fulfilment efficiency
  • Improving marketing efficacy to improve revenue potentials

Improvements in Order Fulfilment Processes

As competition becomes stifling for all food chain operators in Australia, the suppliers are the only parties capable of facilitating efficiency improvements. It’s very likely that inventory cycles will shrink as the number of customers increase and restaurants or other food businesses will have to order supplies much more often. With automated order processing software and documentation preparations, businesses can reduce the lead times preceding order fulfillment.

Once you accurately pre-empt customer orders and also remind them of when they ought to restock, you’ll automatically become a preferred supplier. Predictive ordering, through OMSs, can help you establish yourself as a reliable retailer who can keep up with market needs. This reliability goes a long way in helping improve client relations and the efficiency edge will help you increase market shares.

Additionally, order predictions will also help you restock your inventory to ensure consistent service delivery. In conclusion, predictive ordering will help you establish your authority as a premium service provider.

Improving Sales Revenue Potentials

Once you can predict your client’s orders, you can introduce them to newer products to expand your market size and increase sales revenues. If you make an accurate prediction of how your clients make purchasing decisions, you can use the insight to generate sales for other products. Much like Amazon, you will enhance your sales potentials through predictive analytics and ordering.


In conclusion, predictive analytics present food business suppliers and wholesalers the ability to match the increasing pace of the business environment. Pre-empting customer requirements will help offer better service delivery to clients and increase sales potentials. Your OMSs contain all the information you need to automate and predict your clients’ order preferences to improve your business potentials.

Considering market conditions and the burdens on the retail-end vendors, the back-end supply will also feel pressures of higher demand volumes. As such, all wholesale food services providers will need to improve their service delivery efficacy which only predictive ordering can provide.

Ordertron is an Order Management System that helps foodservice wholesalers and suppliers improve inventory management for improved business outcomes. The company’s Order Management Systems are designed for Food Service Suppliers and Small Businesses, with Android and Apple iPhone applications for clients. Get in touch with the company today for more information on their services or to take on their OMS for your business.

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