In the wake of the COVID19 pandemic and due to large swathes of the world’s population in isolation, demand for online grocery shopping has increased sharply. A mid-March Ipsos MORI survey of adults in the UK found that more than 40% were buying more items from their supermarket than they normally would, with 14.2% of UK internet users claiming to be shopping for groceries more online (according to RetailX) - a demand which continues to rise as lockdown measures become stricter.
In order to cope with this increase grocery providers are putting in place a number of systems and policies, including virtual queueing systems to secure a delivery slot, restricted usage only for health care workers and the more vulnerable and in some cases closing the service to new customers, effectively turning away business.
A recent Financial Times article shared a comment from Ocado’s CFO in an investors call, “The biggest constraint is not the number of vans or drivers, it is the capacity in our customer fulfilment centres, I would love to wave a magic wand and have the Erith [warehouse] at 200,000 orders per week, but life just isn’t like that,” he added, referring to a fulfilment centre that is currently serving 80,000 orders per week.
The biggest constraint is not the number of vans or drivers, it is the capacity in our customer fulfilment centres, I would love to wave a magic wand and have the Erith [warehouse] at 200,000 orders per week, but life just isn’t like that.
Online grocery shopping is a relatively mature market in the UK but the system is buckling under the pressure. We took a look at the recent policies implemented by the UK’s most popular supermarkets and grocery delivery companies to see how they compared:
As consumers, we’re all trying to navigate changing policies & availability, which are all being put in place by retailers who have one single objective: to deliver more orders. One key way to do this is to make their supply chain network spatially optimized, i.e. decrease the number of routes and increase the number of deliveries, using logistics optimization.
So how helpful can spatial optimization be in the face of a nation that is panic-buying? For a long time, Ocado Technology has been able to differentiate their customer experience by using precisely these types of analysis (as well as cutting-edge robotics in their distribution centres) to provide an extremely reliable service within one hour delivery slots.
Unlike the United States, supermarkets have easy access to all motorways and can reach 90% of the UK within just 4 hours of the country’s distribution centre hub (the East Midlands, otherwise known as the Golden Triangle). This is what allows the UK to typically operate with a just-in-time model - allowing supermarkets to order stock on a daily basis based on individual store-level demand.
Normally, that’s an extremely efficient way to run a supply chain network - but when we see an extreme increase in demand (such as online spending increasing by 25.5%) it causes a continuous knock-on effect on the supply chain (as Richard Wilding OBE comments in this Wired Article).
Of course, changing an entire supply chain system around the COVID19 crisis is a challenge - but online retailers and logistics companies can have more control in the last-mile phase - which our Data Science team expanded on in a recent blog post. How? Here are a few examples of spatial supply chain optimizations:
This anonymized example shows a first step on how to apply optimization to solve the on-demand transportation problem in food delivery in Madrid, and the benefit obtained from doing so. Again, using Origin Destination Matrices and a Batch Assignment Algorithm we can optimize routing using real-time location data. Being able to visualize such steps and decisions made by the different algorithms is a very powerful tool for a very time-consuming task, which is where CARTOframes can help. See the full Data Science workflow here.
In this example we can see how to create a manageable and profitable delivery network for distinct territories for 9 Gap store locations, which are derived from 1.5 million points of historical delivery data. Using an Origin Destination Matrix (ODM), we are able to design optimal territories that allow us to build optimal routes delivering in line with 2-hour designated slots. You can see the rest of this optimization walkthrough in this blogpost.
Publix is a leading grocery store chain in the southeastern United States, with primary operations in Florida, with over 1,110 stores served by 8 distribution centers. We evaluated Publix store and distribution center locations to understand how Publix is currently serving their stores, where they should place a new distribution center to serve new locations, and to quantify the ROI of opening a new distribution center. To see the full analysis you can read this post.
Online grocery stores are frantically trying to adapt to changing consumer behaviour through the coronavirus; changing competition law from the government and having enough workers to support the business (with someone sending HQ team members to the frontline in distribution centers).
However, like any other business, they are also preparing their businesses for the post COVID-19 era - when demand lowers and customer expectations go back to normal. Forecasting for when that may happen is a challenge, but using analytics through the process will be fundamental to their success.
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