Intelligent Distributed Order Management: The Answer to Omnichannel Fulfillment Challenges

Last year, my cousin had a daughter, and I became an uncle for the first time. Naturally wanting to be a contender for the best uncle ever, I wanted to send a care package for my baby niece. I wanted to buy a bunch of toys, pacifiers, baby bottles, baby bibs. Since e-commerce gave me the option to fulfill my wish with minimum effort, I chose to order it online. However, as I proceeded to check out, my enthusiasm was cut short. Multiple products in my basket were out of stock, although they were available in stores and other places, none of which were close to the delivery address. This got me thinking. Why was the company unable to fulfill my order of multiple products in one transaction? Why couldn’t I send all my gifts in one package? 

Online shopping has become the easiest way to purchase goods, both for individual customers and businesses. E-Commerce thrived through the global business environment created by the Covid-19 pandemic. With E-Commerce being this dominant, companies had to focus on omnichannel fulfillment issues and Distributed Order Management. In the pre-Covid world, when a customer wanted to order any item online which wasn’t available in the e-commerce fulfillment center, the system would simply say that it was out of stock. However,  this is no longer good enough for consumers. When they can’t find an item in your online store, they simply leave you for other companies. Through Distributed Order Management, companies now have more options to fulfill customer orders from online and in-store transactions and improve customer satisfaction and inventory productivity.

What is Distributed Order Management (DOM)?

With the emergence of omnichannel shopping and customers having more and more options in how they shop and how/where they receive the goods, retailers encounter an increase in fulfillment complexity. Distributed Order Management allows the company to utilize inventory in multiple locations across the network, including central warehouses, stores, regional distribution centers, and even suppliers, to fulfill orders and satisfy customer demands.

What is the actual problem?

Thanks to the evolution of e-commerce platforms, customers now expect all their needs to be met instantaneously with convenience and ease in the competitive retail landscape. Orders need to be taken, processed, shipped, and received by the customer, and they should arrive on time as promised at the time of the order. In the past, this was relatively simple since most retailers operated locally and had simple order fulfillment processes. With the emergence of omnichannel shopping, the order fulfillment challenges, the issues regarding Order Fulfillment no longer can afford to be solved in a suboptimal manner. With the availability of advanced analytical methods, including AI/ML and optimization techniques, it is possible to provide rigorous analytic solutions to these problems. There are multi-objective optimization problems that need solving, and rule-based configurations have to be done so that systems efficiently achieve their omnichannel fulfillment. As I will discuss in further paragraphs, most DOM systems employ similar techniques to frame this as a modeling problem and solve it efficiently.

Distributed Order Management

We know the problem; what is the solution?

The solution lies within the main subject of this article: Distributed Order Management. 
DOM systems allow retailers to visualize their fulfillment problems with analytics. In addition, DOM lets you configure your own set of rules when it comes to fulfillment prioritization. It is not a magic wand that will allow you never to let an order go unfulfilled; however, it makes it possible to minimize unfulfilled orders, ship times, and costs while profit and customer satisfaction is maximized.
DOM tackles a multitude of retailers’ problems. First, it reduces unfulfilled orders and works towards maximizing order fulfillment, so customers see fewer “out of stock” warnings shopping through a company’s e-commerce channels. The next step matches the rules necessary to meet the fulfillment: Which store has a product in demand? What is the transportation cost? Will the demand be met in time? These questions are all integrated via the fulfillment rules, so the system knows what to do when. Finally, it also figures out stores/warehouses with excess stock, manages multiple orders, allocates necessary inventory, optimizes transportation costs, and manages multi-objective optimization problems to generate the best results. It might not be a magic wand, but it is pretty close to it.

How to implement DOM?

DOM systems require four data components to be effective:

1. Access to real-time order and inventory data

 To do distributed order management in real-time or near real-time, having visibility on available inventory data, including returns available to sell, is crucial. 

2. Operational and logistics costs

To evaluate different options for fulfillment by sourcing inventory from multiple locations, the model needs to be aware of the operational costs and constraints. This should  include each potential fulfillment location (stores, web fulfillment center, central warehouse, distribution), the shipping costs, and lead times between these locations, as well as the customer destination (home, store, locker, etc.),

3. Rules for fulfilling orders

 Are there any priority customers? Is there any safety stock that should be maintained at all times? Are there any restrictions to where from/to a product can be shipped? Customer preferences on how they would like to receive the shipment, such as single package vs. multiple shipments, are some rules that can be included to order fulfillment.

4. Location-specific constraints 

Maybe not all stores are set up to fulfill, and/or they have limited resources or holding and packing capacity to fulfill omnichannel orders. Location specific-constraints such as how many packages they can ship per day or how many packages they can hold for pickup contribute to making operationally feasible decisions. 
DOM systems effectively start working to optimize the fulfillment process. There are different ways of doing this. For example, many retailers work with rule-sets determining where to get the inventory within the network, such as ship from the closest store to the customer or ship from only large stores which usually have more available stock and sales staff. Employing optimization techniques is a more sophisticated and dynamic approach that works with the realities of the network and balances the operational costs against customer requirements.

Fulfillment Methods

Make Retail Great Again

Retailers are having mixed reactions to the business environment created by Covid-19. Some of them are thriving better than ever, while others are suffering. But no matter how they are planning to go through in this business environment, they are not allowed to underestimate the power of omnichannel operations. With brick and mortar stores suffering the most during the pandemic, the money is there to be made in the E-commerce channel and given customers different options for speed and convenience of getting what they need. And to fully capitalize on this opportunity, retailers are forced to use cutting-edge practices like Distributed Order Management so they can operate at their best. 
To survive in the regular growing retail employment, retailers must make sure they are fulfilling orders efficiently and optimized. Using DOM can make sure customers are not disappointed, whether they are ordering high-end items like smartphones or toys for babies.

Solvoyo Planning and Analytics