It is fair to say that the COVID-19 pandemic has had a jarring impact on retail supply chains in myriad ways, in terms of how retailers had to respond and react to a new way of handling their supply chain operations. That was made clear in the findings of a recent study published by Blue Yonder (formerly JDA), a provider of AI-driven and end-to-end supply chain management services, and WMG, an academic department at the University of Warwick, England that provides research, education and knowledge transfer in engineering, manufacturing and technology.
Data and feedback in the study, which was administered online by Qualtrics in late April, was based on insights from 105 senior executives in retail supply chains throughout Europe, Asia, and the Americas.
The study’s findings focused on myriad areas of retail supply chain operations, including:
To get a deeper dive into the study’s findings, Logistics Management (LM) interviewed Jim Hull, Senior Director of Industry Strategy at Blue Yonder.
LM: The study noted that 58% of retailers indicated a high degree of manual intervention was required to respond to the fluctuation in demand and supply. Can you please provide some examples of that manual intervention?
Hull: Good examples of what we saw are store order overrides – essentially a store manager starts to see that a product is selling faster than ‘normal’ and tries to get ahead of it. They create special orders for more product that gets shipped from the DC to the store, but many stores doing this causes the DC to quickly run out of product. The DC Planner then has to override their normal order quantities to try and get more product, including going into currently open purchase orders and increasing the quantities.
Of an interesting note, we did see that retailers leveraging our AI ordering engines picked up that store increase in demand faster and reacted automatically. This allowed the entire system to sense the demand shift faster and allowed those retailers to get back to the suppliers a bit earlier than other retailers, giving them ‘first bite’ at the available supply.
LM: 40% of respondents noted an aspiration to operate fully automated warehouses in the next five years. What needs to happen/occur for them to have that goal come to fruition?
Hull: To achieve a fully automated warehouse there are several pieces that need to be put in place:
LM: Why are retailers better at responding to decreases in demand rather than increases in demand?
Hull: From a planning perspective, traditional replenishment systems tend to quickly react to slowing sales, but lag when sales pick up.
In a slowing sales environment, when the replenishment system checks available inventory vs. predicted demand, it will see that there is still plenty of inventory, and thus not create a new order, slowing down the whole supply chain relatively quickly.
When sales pick up, though, the system sees the inventory is being pulled through the system, but typically uses a moving average or similar approach to ‘guess’ how much of the recent trend to believe. Most retailers I talk to want to see a trend continuing for a few weeks before fully betting on the increased sales, so they keep their replenishment systems on the conservative side. This works fine for repeat surges like the 4th of July or Holidays where you have a sense of how high demand will go, but in the recent crisis no one knew if the spike was real or short term and therefore were slow to react.
Additionally, it is much easier to ramp down capacity in areas where it isn’t needed than it is to ramp up an already highly utilized portion of the supply chain. For example, in Grocery, the frozen foods chain depends on refrigerated storage and transport trucks. When people were suddenly eating home much more, the frozen food sales took off. However, grocers couldn’t easily add more frozen storage at the DCs, nor quickly procure a bunch of refrigerated trucks, so they struggled to meet the increased demand in these somewhat specialized areas.
LM: Why is the percentage of “digitally ready” retailers only at 12%?
Hull: In one word, “Data.” An autonomous supply chain requires clean data, at the right level of granularity. This includes clean inventory data at all points in the supply chain, solid product information, sales information, pricing history, promotional history and digitized promotion plans, etc. Most retailers are only now beginning the journey to create an enterprise data resource that can feed the digital supply chain.