"Cracking the Delivery Code: The Quest for Efficiency"

As we journeyed through the pandemic, e-commerce and delivery services transitioned from a mere curiosity to an essential lifeline, ultimately becoming a commoditized staple of daily life. Understanding the inner workings of last-mile delivery companies has become extremely fascinating for me. This article explores the intricacies of last-mile delivery operations and the quest for efficiency.?

The last-mile delivery arena is a complex jigsaw puzzle, with numerous players such as Amazon, Target, Walmart, and smaller niche operators like DoorDash, Instacart, Uber Eats, and Shipt. They cater to a wide range of customer needs, from delivering essentials, groceries and restaurant meals to niche ethnic grocery products. Despite their differences, their core focus remains the same - getting products directly to the customer's doorstep. The pandemic served as a catalyst, spurring investment and interest in the last-mile delivery sector from the VC community. Companies adapted with agility, developing various strategies like focusing on hyper-local delivery for quick turnaround times or targeting niche markets.

The businesses which purely focus on last-mile service have it as a double-edged sword. Companies that don't carry inventory enjoy lower costs but may struggle to control customer experiences when items are out of stock at partner retailers. The secret sauce to profitability lies in understanding the unit economics and how efficiencies can be driven out of it. With insights from industry expert on unit economics I go on to build a hypothetical case to show how order-size Vs efficiencies need to work together to break-even on the simplest operational costs!?

Impact of Batching (combining) orders & Delivery Density:

Consider two scenarios for the delivery of your grocery order. One with a single order full-fillment that is set to be fulfilled without any other orders(ie.,within an hour) another where you have a degree of flexibility on time giving you an option to batch multiple orders. As the table below illustrates, the operational cost per unit is very high in the first case whereas, in the second one you can simply gain better efficiencies by batching multiple orders together. A kicker here, if you are able to optimize your delivery network and increase delivery density(ie., have multiple delivery orders in the same neighborhood) you can further reduce the cost per order unlocking higher profit margins. This is why many companies offer delivery windows, allowing them to better manage resources and enhance efficiency. So inadvertently, any company that has chosen a model where their differentiating factor conflicts with their ability to gain efficiency puts them in a very tough spot to turn a profit(Ex: your hyper-local delivery startups)

Revenue to break-even on operational costs in a day:

Now, expanding on this to break-even the operational cost of delivery(ie., 22$/hr assuming a delivery can be done within an hour) if you do the math, the average basket size must either be $180 or you need to batch about 6 orders worth $30 each or 3 orders worth $60 each in the same zip-code. See an illustration of a hypothetical Bay Area market that a grocery deliverer wants to serve in 6 delivery windows each day(rationally assuming they want to do 12 hours/day operation with 2 hour windows) and how much revenue is needed to be made here to break-even per day:

As you see you’d need at least $962K/day to break-even pure operational costs if this company operated consistently across the 6 delivery windows in just Bay Area with a varying #orders based on basket sizes and an ability to batch them. Now, people don't operate in a rational flow for the business to forecast and prepare for this accurately. There will ebbs and flows on both sides. Meaning, people might not want to order in some slots and some days revenue will be less than others(peak and non-peak). Sometimes, the nearest grocery location is farther than optimal. Other times a company has only one order in a particular zip-code that still needs to be fulfilled at a loss to maintain customer relationships. All of these need to be modeled too! With the most basic of assumptions, we are able to witness how this business can easily get complex.?

To this extent, the last-mile delivery industry is experiencing a transformation. Faced with operational challenges and the need to achieve critical mass for profitability as evidenced above, companies are shifting towards partnerships, consolidation, at times quitting high-labor cost markets like the US? in exploration of cheaper markets like South America or rethinking the whole cost-structure with autonomous delivery drones and vehicles! The importance of a carefully crafted strategy for achieving profitability cannot be overstated. In the end, it's essential for companies to thoughtfully evaluate their chosen business model and its potential impact on their long-term success. So, the next time you see a friendly delivery person bringing your groceries or a delicious meal to your doorstep, let your curiosity be sparked by the fascinating world of last-mile delivery and remember the intricate dance of efficiency and innovation that makes it all possible.