The Future Of Retail: Technologies Enabling Q-Commerce Growth
My dad is the VP of our household’s grocery supply chain. Every Saturday since my childhood, he has driven to the farmer’s market and hand-picked fruits and vegetables so mom and I could eat the best and most organic fruits and vegetables the market has to offer. Now he spends his Saturdays laying on his favorite sofa and looking for the best deals on fresh groceries online; he even cross-shops using three different apps! With the pandemic beginning last year, my dad was robbed of this small pleasure he had in life.
The shift to online shopping was accelerated due to the Covid-19 pandemic. Millions of shoppers, like my Dad, are not going back to their old habits because there are now faster and more convenient ways for buying daily household needs. Along with E-commerce, another rising star of this pandemic-struck world has been quick commerce (Q-Commerce, or Rapid Food Delivery). It excels on a union of E-Commerce mobile apps and last-mile delivery innovations. More than 30 Q-Commerce companies are currently operating in Europe, and half of them were founded very recently, in 2020.
“According to OECD, during the pandemic, brick-and-mortar retail services such as food services saw 7.7% drop in sales while non-store retailers (mostly E-Commerce providers) achieved 14.8% increase with their sales in the U.S. And this shift in consumer behavior is expected to be sticky due to accessibility benefits and the easy to use nature of E-Commerce.”
Nowadays, we have online apps that promise farm-to-table veggies and fresh-baked vegan cookies with less than 30 minutes of delivery time. I’ve noticed that my father only goes to the farmers market when there is a special occasion. Now he shops across all the apps he has on his smartphone and chooses the one he thinks has the best quality for the least price on that day.
To keep customers like my dad satisfied, RGD and Quick-commerce companies need to invest in new technologies to optimize the supply chain and logistics operations. These technologies are often invisible to the end-user but make a big difference in keeping the promises about product availability, freshness, and speed of delivery.
“With the pandemic, consumer loyalty started bleeding in almost every industry. A McKinsey research from July 2020 found that during the pandemic, 75% of shoppers have switched between the brands they frequently shop from.”
Customers are becoming more impatient when it comes to online shopping. Q-commerce companies need to make sure the inventory levels are managed at each fulfillment center (darkstore, or MFC) in a way to maximize availability and minimize waste and also constantly adjusted to meet the local demand, which can vary due to customer demographics, local events and promotions, and the competitive offerings.
Inventory Optimization involves decisions about the inventory level, the location, and the mix of products. It needs to be tightly coupled with demand and supply planning, as they share common planning parameters and influence each other. Safety stocks must be adjusted dynamically to be ahead of the curve in cases of demand/supply variations.
Let’s say I’m an online grocery provider that wants to sell avocados. I have to forecast my avocado sales, including seasonal patterns and promotional effects. And after that, I have to decide how much avocado inventory I have to hold, so I never have stock-outs or excess waste.
Supply Chain Digitalization & Autonomous Planning
Speed and availability are the most important reasons customers choose RGD and Q-Commerce companies. These businesses have to keep investing in automation across all supply chain points to keep up with the demand. Integrated forecasting, store replenishment, warehouse procurement, purchase order creation, operational constraints such as storage space, unloading capacity, and commercial agreements such as vendor lead times, minimum order quantities, packaging configurations can hugely improve productivity and accuracy in the planning processes. When these are automated, up to 99% of the daily planning decisions can run autonomously, allowing the team to focus on more tactical decisions and take preemptive actions before any disruption occurs.
Crowdsourcing of Drivers and Rider Forecasting
Crowdsourcing is nothing new, as companies like Airbnb and UBER have been using them for a while now. It is now possible for Q-commerce companies or retailers to use this model. It allows for low start-up costs, asset-light operations, and improved customer experience. It also provides an excellent part-time employment opportunity with flexible shifts.
However, this also comes with its planning challenges. Q-Commerce companies can leverage advanced analytics and automation technologies to make this process almost a no-touch one. They can optimize courier and order matching, increase visibility, and track important metrics such as order lead time, OTIF, courier performance, and customer satisfaction. The best thing about crowdsourcing is that it does not only benefit companies but local people too.
With crowdsourcing, the rider forecasting challenge arises. How many riders, couriers will my company need? How much capacity do I require? When will I need the most riders (rush hour etc.)? What will the weather be like in the following delivery period, and how many riders will not show up for various reasons? How do we plan for the impact of weather? How much will heavy rainfall impact demand? How will it impact the supply of riders or the delivery time windows?
These are all questions that must be answered to employ best practices in this area.
Rider scheduling can be planned and automated with a supply chain planning platform. The data available for order forecasting and the heatmap analytics of orders, rider performance, and other external factors such as the weather will allow the platform to create daily rider scheduling.
Like most logistics challenges, last-mile delivery is a transportation problem in its essence and requires robust algorithm-based optimization. How to maximize service rate? How to minimize transportation costs? And how to optimize the entire transportation network? These are questions that need answering when solving the last-mile delivery problem.
Companies need to consider locations, time, traffic, capacity, and courier availability to answer these questions. Usually, this problem requires software to solve. The model and solution system designed to solve this problem should also be flexible and agile. Especially in Q-Commerce, the business is highly volatile, and time is of utmost importance. A flexible model would be easy to make necessary alterations and fast in generating new route optimization plans. Maybe orders are peaking right before dinner time, as most households want to order missing ingredients, causing a bottleneck there. So you may require a different allocation of couriers or use vehicles with higher capacities so you can increase your fulfillment per transportation unit.
Covid-19 has altered markets and business models in an unprecedented way. Some industries suffered while it also allowed other ones to boom. Q-Commerce is one of the industries that benefited from this. However, there are many challenges to making these business models sustainable and profitable during fast growth.
Digital transformation and autonomous planning capabilities in supply chain planning and logistics will be the key differentiators that will decide these companies’ long-term viability and profitability.
Atakan Kantar is an Industrial Engineering and Economics graduate and Growth Engineer at Solvoyo. He specializes in the digitization of Retail & CPG companies. He also takes part in pre-sales cycles to understand potential customers’ business needs and finds the best-fit solution.
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