Key Takeaway
If you are an ecommerce company that has outsourced their delivery to third party logistics companies, then this blog is for you. In this piece, we talk about how you can create a central place for your ops and city teams to monitor and analyze the performance of these 3PL providers.
Introduction
E-commerce has changed the way in which society sells goods and services and become a part of our daily lifestyle. It has experienced rapid growth since its humble beginnings with e-commerce sales projected to grow to 599.2 billion USD by 2024. The COVID-19 outbreak saw e-commerce sales spike 25% in March 2020 alone.
With e-commerce companies rapidly expanding and serving more orders per day, it has become important for them to outsource these orders to specific people who can manage granular city level supply chains on their own. This need has resulted in the global third-party logistics (3PL) market with specialized services such as inventory management, cross-docking, door-to-door delivery, and packaging of products.
In this blog,we will talk about how e-commerce companies that use third party logistics providers can use location analytics to set up what we call a control tower for their ops and city teams.
The Problem(s)
A report from Tomkins Associates shows that E-commerce firms pay their 3PL providers upto 10.8% of their own net revenue. This makes it very important to realize exactly how valuable is your 3PL partner, and how much does the service really cost on-ground.
While ecommerce companies gain a lot in terms of hyper-local supply chain management by partnering with these providers, they also end up taking significant risks in doing so.
There are multiple providers with different pricing and delivery capabilities in different areas, so evaluating their performance & having the visibility is critical to find the right provider for the right area.
These are not limited to a high cost in terms of overheads and base charges per delivery paid to the 3PL Partner, but extend to risks in an information gap between the provider and the city level ops team of the e-commerce firm. Some companies do get individual dashboards from each of their providers but the process is currently painful to get answers to their questions.
As a result, the commerce firms don’t have direct visibility on how much the shipments cost to delivery across their customer geography and they end up suffering in cases of delays, damages, returns, cancellations and so on!
The Status Quo: What's happening in ecommerce companies currently?
E-commerce firms must measure and evaluate the costs that they undergo in outsourcing and weigh it with respect to the performance of their 3PL partners. Doing this currently is a very painful process. They have to compile large amounts of data regarding their delivery trips, their user behaviour and the performance of their storage units.
- The biggest issue is data is split among many different systems: UPS/FedEx/Courier Billing, Label Generation Software, Customer Support, E-Commerce Software, etc.
- When they look at performance they look at their regional P&Ls and the granularity is at best by zip code or city. There’s very little segmentation to better understand their cart performance.
- The business teams and decision makers have no visibility about where the current bottlenecks are and where more opportunities lie to make money.
Why is “Visibility” as critical as Bread and Butter?
At Locale, we have been working with different ecommerce companies and have learnt what they care about and what’s important for them. In this section, we talk about how visibility is the best way to provide an e-commerce firm with the necessary information to use, evaluate and maximise the output of their 3 PL providers.
Visibility helps in pruning costs by being more proactive and intervening at times of panic to take the right operational decisions. Let's quickly trace the life of one order to find out:
- Order Placement: First, the user opens the app, and searches for something. What are the reasons that may prevent him from booking: a high delivery time? Inconvenient prices? Poor category range? Let’s say that they place an order.
- Warehouse: Now where does your 3PL provider begin their share of the work, once you’ve shipped it to a local warehouse? They deliver it from there. Now a few problems might occur at this stage. There could be a delay in locating, packaging, and loading the produce. In case of perishables, this is especially problematic. Maybe the warehouse is located far away from places which generate a large number of orders thus causing delays.
- Last Mile: Once the delivery process begins, there can be a delay caused due to a physical breakdown of the truck, jamming of routes or inefficiency of delivery personnel. What this looks like could range from delivery executives going off the grid, missing a checkpoint in the delivery process or even claiming a delivery whereas the customer might not have received it.
It is important for e-commerce outfits to know the cost, value and efficiency of a shipment, and data regarding the user behaviour, delivery journey, and warehouse performance can help them make the best decisions.
So how do we create one single control tower for the ops teams: one place for all their location analysis? Across all of these issues, their potential solutions have one word in common: location.
The Solution: A Control Tower using Location Data
What are the top use cases and metrics that create the barometer to judge a 3PL partner?
Real Time Monitoring
Can you be more proactive about what's happening on the ground and in case of no shows?
- Tracking: Can we track the movements of shipments in real time? How are certain shipments behaving on certain routes?
- Anomalies: Can we get real time triggers in case of anomalous behaviour or discrepancies from any KPIs (sudden dip in bookings/fluctuations)?
Shipment Deliveries
How do you analyze which partners are giving the best and worst customer experience across different locations?
- Delays: Which partners or routes are associated with maximum delays across different areas?
- Returns: Which areas have seen the maximum amount of returns? Is there is a pattern in the partner handling that location? Is it a warehouse?
- Cancellations: Which partners are associated with the highest cancellation rates in different areas and SKUs? Is this linked to a delivery location?
- Re-deliveries: Where are there re-deliveries of shipments occusing or failure of delivery?
Cost Analysis
How do you get a better understanding of what’s the total true cost of shipping across different partners and cities?
- Base Shipping Price: What is the base fee and how does it vary across different locations and different providers?
- Additional shipping fees (charged later): What is the extra expenditure that is being made as parts of various overheads across providers? Why are they being levied?
Warehouse
How do you evaluate how often shipments come from multiple warehouses and what is the true cost of those deliveries in different areas for all your partners?
- Inventory by Warehouse: In case you have more than two warehouses, how do you load balance your SKUs based on order density?
- Shelf Time: How much shelf time are my goods across SKUs spending in different warehouses?
- Delays by Warehouse: Which warehouses face the highest delays in packaging, loading and overall deliveries?
Customer Support:
Additionally, customer support data can be analyzed to figure out where do we need to focus:
- Late Shipments: Where are customers not experiencing getting a good experiece because of delayed orders?
- Complaints: Where are customer complaints coming from? Which partner is responsible for these deliveries?
- Product Complaints: From which regions do customers return products and why? Which warehouse is responsible for this?
- User Cancellations: Where are user cancelling their orders the most and in which part of the journey?
How to use Control Towers for Hyperlocal Marketing
When retailers and especially e-commerce companies better understand customer geography with more granularity, it becomes much easier to allocate marketing & operation spend. They can focus on most profitable regions and start pursuing hyper-local marketing strategies that will increase sales & reduce their overall operational spend. Some metrics to do this analysis are:
- Order Patterns: What is the preference of users in terms of order patterns across SKUs and locations? Can we shoot ad campaigns in those areas to increase acquisition?
- Product Searches: Which areas show the highest searches for some products? Are they being fulfilled?
- RoI: Which localities have very high/low sales? Which ones fail to do so?
Why Choose Locale?
We, at Locale believe in a simple philosophy: to answer all your complex data related questions at the click of a button. You can now crunch all this data, combine the inputs from different sources, and get actionable insights: without really having to write a single query!
We aim to help every e-commerce company create their own control towers, measure the cost-benefit analysis of their 3PL partners, and make decisions on these topics, at the click of a button.
Locale is the answer to all location analytics searches for any company. The analytics console is built in a way that it can:
- It can handle large scale data (close to 55 million pings in production) and can be integrated to your system in a day (allows integration with countless different data sources)
- Can help you deep dive to the tiniest granular level and take crucial business decisions using both real-time as well as historical data.
- Our pre-built consoles makes it easy for you to edit and customize them according to your needs so that you can visualise your most important metric in a matter of few clicks without writing a single query.
Need to know where to expand? Why do delays occur? Which warehouses to shut down? How to reduce cancellations? Need it all under the same roof? Then visit our website or get in touch with me on LinkedIn or Twitter.
Similar Reads:
The Locale.ai Blog
The Locale.ai Blog
