Viability of Hyperlocal Operations & How To Make Them Quicker, Greener & Profitable

The quick service and hyperlocal delivery segments have seen meteoric growth in recent years. The pandemic and rapid innovations in information technology have been the primary drivers.

The earliest adopters of technology to streamline and scale their hyperlocal operations have been industries that historically catered to the ‘instant delivery’ model – quick service restaurants (QSRs) and grocery stores.

But now eCommerce retailers have also jumped onto the bandwagon, offering not just same-day delivery but even 2-hour order fulfillment for categories ranging from home essentials to fashion.

Bearing The Cost of Fast Deliveries Operations

Businesses in price-sensitive emerging economies have absorbed the costs associated with providing fast deliveries to tap into changing consumer behavior and capturing market share. In contrast, similar businesses in developed markets like the USA and Western Europe have shifted the cost burden to consumers, dampening consumer appetite to buy.

Citing heavy losses experienced by such businesses, some industry analysts have been quick to label this business model as a cash-burn strategy or too costly for customers to be viable. Others have raised objections to the environmental impact of such a delivery model due to growing emissions from increased vehicular traffic.

Let us look at how and when a hyperlocal delivery model is viable and what businesses can do to boost profitability.

What markets are suitable for hyperlocal operations?

Hyperlocal operations are the most viable in catchment areas with dense populations, where there is a steady demand for core products a business offers. Let us understand what this means.

Hubs or outlets that businesses intend to serve hyperlocal markets need to have a considerable number of people willing to order from them for the business to invest in logistics to fulfill these orders. This is why several industry leaders are investing in setting up strategically located ‘dark stores’ or warehouses, which are usually more centrally situated, but rent is lower than high street shops. 

But having a large number of people in the neighborhood is of no relief if there isn’t consistent demand for what the business is selling. Even in the most populous cities, only so many people purchase a particular item daily. Thus low-value consumer goods, which have frequent and consistent demand, are the most suitable for launching hyperlocal operations.

The next consideration is inventory – businesses must find the right balance between offering a catalog of products that would attract varying customers and ensuring that they don’t have to maintain a massive stock. A personal care business can’t survive if it offers only a certain kind of hair oil, but it also cannot afford to stock 100 brands of hair oil, shampoo, soap, cream etc. It is thus essential that businesses leverage analytics and historical data to forecast demand and build their inventory to ensure a healthy turnover rate in their inventory. 

How to make hyperlocal operations profitable?

Now that we understand when a hyperlocal delivery model is viable, let us look at some best practices for such operations:

Decide the optimal trade-off between resource capacity utilization and wait time

The more a business increases their capacity, the quicker it can serve functions and orders. If you have 100 deliveries to make in a day, you’d be able to serve it the quickest if you had 100 delivery drivers. But the amount of work that each driver does will be very little, i.e., there will be minimal capacity utilization. On the flip side, if you had five drivers do 20 orders each, the capacity utilization would be maximized, but the delivery time would dramatically increase.

While this may be a simple concept, it is not easy to arrive at the optimal level of capacity, i.e., the number of delivery drivers, such that both capacity utilization and wait time are acceptable. Businesses tend to inflate their capacity to fulfill aggressive delivery-time SLAs but then find that their capacity utilization is limited, significantly increasing their overall and per-delivery costs.    

This trade-off is more kind to businesses that have higher planning reliability. In this case, an increase in capacity utilization mitigates the impact of wait time when there is more certainty regarding the quantum and stability of demand.

Increasing resource capacity by automating delivery processes

With drivers being one of the highest contributors to operations costs, businesses must look to enable their drivers to increase the number of customers they can serve in the same amount of time. This is possible by automating processes such as order allocation and route planning.

A smart allocation engine, such as the one Shipsy’s platform offers, automatically allocates a received order to a driver closest to the hub through geofencing technology. After allocation, the driver directly receives the details on their driver app, reducing the time and cost of manual intervention.

With increased adoption and innovations in GPS technology, businesses can ensure that their drivers take the shortest route from hub to door. It hits the trifecta of reducing the delivery time, delivery cost and environmental impact of fulfilling every single order.

Shipsy’s AI & ML-enabled route optimization engine uses our proprietary geocoding engine to establish the delivery location and the quickest route from the hub to the delivery destination while factoring in the capacity and speed of different vehicles in the fleet (as discussed below).

The order allocation and route optimization engine is also able to work together to batch orders, allowing riders to make multiple deliveries in one trip.

Fleet composition – using multiple vehicular types and ‘floating fleets’

Hyperlocal businesses receive orders of varying sizes and distances from their operation hubs. Depending on this, a fleet composition incorporating different vehicle types, such as cycles, scooters/motorcycles, vans and trucks, may be more effective than having a uniform fleet. Often a lighter vehicle can fulfill orders within the promised time with significantly reduced financial and environmental costs. 

If a business uses multiple fulfillment centers located in close proximity, i.e. within the same city, they should look to use a ‘floating fleet’ model rather than a ‘dedicated fleet’ model. A floating fleet can pick up and deliver orders from multiple locations rather than serving one hub. A driver can be routed to pick up the next order from another fulfillment center if the delivery destination of their previous order is closer to it than the original hub. This model allows drivers to serve more orders and reduces their idle time.

Hawkish driver performance management to retain & reward top-performing drivers

Delivery drivers have among the highest rates of attritions for any profession, estimated at around 6-7% per month. Considering the cost and time it takes to train new drivers, this is a significant sinkhole for a business’s profitability.

In this context, businesses need to identify and reward their top-performing drivers. With the use of analytics, it is possible for businesses to analyze driver-level data on parameters such as delivery success rate, route adherence, ETA adherence and more. 

Using this data, businesses can then appropriately reward the top performers while also helping them identify factors that may be negatively impacting their operations, enabling them to increase resource capacity and operational efficiency.

Customer communication & incentivizing consumers for flexibility in delivery times

Customers expecting a quick delivery expect regular updates and preferably live tracking of their consignment. This allows them a greater feeling of control and flexibility in planning their schedules around a delivery. Businesses must offer these services to delight and retain customers. 

While the chorus around hyperlocal deliveries has been that ‘customers want it now,’ often customers are ready to wait longer for their delivery if it is not urgent. Through discounts and rewards, businesses must influence customers to settle for a turnaround (TAT) time that’s longer than the shortest delivery time. With longer TATs, businesses can plan route trips incorporating multiple deliveries, increasing efficiency and decreasing costs. 

While there remain several challenges in managing hyperlocal operations and turning a profit, these are the key drivers that businesses need to focus on to achieve success in this dynamic domain. Making every delivery quicker, greener and more profitable is possible with the right logistics management tools.

If you want to learn more about how Shipsy’s smart logistics management platform can enable your business to manage and leverage On-Demand Delivery capabilities effectively, visit our website or contact us for a meeting or a demo.