How digitalisation of operations will save delivery costs

on demand delivery retail

This article provides a practical insight on how companies can save substantially on their operational and delivery costs by digitalising a part of their organisation and implementing a more data-driven decision-making structure.

We will show that the costs of implementation are much lower than the savings that will be visible almost immediately after going live.

4 steps to start saving costs

The path that leads to optimisation is pretty clear. We will discuss the following steps that your organisation would have to take, and how you can implement solutions with relatively little effort.

  1. Bring your fleet online
  2. Bring your operations online
  3. Set out a benchmark for planning
  4. Analyze your data and save delivery costs

But first let’s look a little bit closer at the customers that we have been working with and the challenges that they are facing.

Where are the current operational challenges ?

Over the past years, we have been working closely with many companies across the globe, such as 3pls, retailers and distributors.

At the start of our partnerships, we always go into a detailed discussion on where they feel the challenges are with respect to their delivery operations. What they all have in common is that they faced one or several of the following challenges:

  • Inefficient resource utilisation
  • Lack of visibility and control over drivers and orders
  • Unpredictable volume during peak periods
  • Manual dispatching and order management

These challenges often lead to requirements such as: live tracking of the drivers, automated route planning, ability to involve third-party drivers on the system, etc..

From CarPal’s perspective, our experienced product team tends to look beyond the technical requirements, get to the true source of the challenges faced, and come up with the best possible solution that could be feasibly adopted by the companies.

Storage and usage of data

Over time, we realized that there is one thing above everything else we need to solve all challenges: data.

When asked about any of the 4 challenges faced, most companies would not be able to specify or elaborate on:

  • How inefficient the current resource utilisation is
  • How the lack of visibility impacts their KPIs
  • How unpredictable volume increases the operation costs
  • How manual dispatching costs the company more than automated dispatching

Hence, the solution does not lie within offering a broader range of features to satisfy company’s requirements. The ultimate goal is  to get data and use it to help their team to make better decisions, which would then directly lead to saving on delivery costs. All features in CarPal Fleet are built around data gathering and analytics to support this goal.

Bring the fleet online

Bring the fleet online

We are all aware that last-mile is typically the most expensive part of the supply chain. When shipping an article from Amsterdam to Beijing, the highest costs are reflected in bringing it from the airport in Beijing to the recipient. In reality, the last-mile is also the most manual part of the supply chain, and very often the least optimised leg of the whole journey. In the past, companies refrained from trying to digitalise the last-mile for multiple reasons:

  1. High costs involved in purchasing GPS devices to track the fleet.
  2. Limitation of the data acquired through the use of GPS devices (They provide insight into ‘where is the driver’, but not so much about the deliveries and ‘what is the driver doing’).
  3. The company is using contractors or 3PLs: The company would not have any visibility or control over the data if the 3rd parties choose not to share it.

Mobile technology

The rapid advancement of mobile technology in recent years has changed the game and opened up a wide range of possibilities for us to revisit the challenges and try to tackle them in a brand new manner.

With CarPal Fleet, we can now bring the whole fleet (in-house and/or contractors) online within days by simply installing an application on a smartphone. The customer can choose to either let drivers use their own phones, or invest in purchasing Android company devices. Involving the 3PL in this digitalization process is a little bit more tricky, and we will cover that part in a separate article.

The moment the entire fleet is online, data on their every movement starts to flow in and is stored in our secured data warehouse. We collect information such as:

  • Velocity records
  • Route taken
  • Traffic faced en route
  • Break times and stops
  • Pickup/delivery timings
  • Pickup/delivery delays
  • Number of drops completed per hour
  • Problems faced during delivery (customer not home, items missing, etc.)
  • Proof of delivery

Most companies previously did not have access to any of this data, other than the sporadic comments from drivers like ‘I’m stuck in traffic’ or ‘Recipient was not at home’. So the new set of data automatically becomes the benchmark for future optimization. This becomes particularly interesting when the operations and route planning are also digitalised as we will show below.

Bring the operations online

Bring the operations onlin

In order to demand the fleet to be (more) efficient, we need to start with proper planning. If the route provided was not optimal in the first place, we cannot blame the driver for not being able to complete sufficient deliveries or deliver them within the requested time windows.

Manual or automated route planning

After placing orders in the system through spreadsheet upload or API integrations (with WMS or ERP systems), the operator can choose to manually dispatch or run the automated route-planning algorithm.

Due to the nature of certain businesses, some still prefer manual dispatching over automated. For instance, a large distributor that has a fairly manual warehouse operations and usually has unexpected maintenance to perform on the vehicles when they get back to the warehouse. Of course, there is a lot of room for improvement on their operations, but it would make more sense for them to plan their drivers’ routes manually. CarPal Fleet system currently allows for both options.

Going from offline to online

The goal is to move away from handing out spreadsheets (or other forms of manual assignment sheets) to the drivers before they leave the warehouse, but to assign the orders to them directly via the mobile app. Since the orders are now safely stored in the system and digitalised, both manual and automated planning allow for benchmarking our expectations, which would lead to optimization and ultimately cost saving.

Set out the benchmark for route planning

When planning a route (manual or automated) we typically look at the following:

  • Delivery time window
  • Distance
  • Availability of the driver
  • Capacity of the vehicle
  • Expected traffic
  • Orders that require a specific vehicle (chilled truck etc.)

Set out benchmark for planning

For every route planned, the key is to set a benchmark. Let’s have a look at a practical example for one of our customers in Europe:

In this particular case, we planned around 60 orders to be collected from a single warehouse. This customer employs around 25 drivers. Let’s just take a small part of their entire route planning to keep it simple:

Warehouse Address
Operating Hours
вулиця Причальна, 5А, Київ, 01000
06:00:00 – 23:00:00
Delivery Window Delivery Address Capacity Distance from previous location Travelling time from previous location Estimated arrival Estimated departure
09:00 – 11:00 Украина, Киев, ул. Дубового, 2 (м. Дарница) kiev 1 9.364km 14.01 minutes 2018-08-08 09:14 2018-08-08 09:44
09:00 – 11:00 Київшосе Харківське19А kiev 1 0.000km 0.00 minutes 2018-08-08 09:44 2018-08-08 10:14
10:16 – 12:16 Київшосе харківське174а kiev 1 0.000km 0.00 minutes 2018-08-08 10:14 2018-08-08 10:44
09:00 – 11:00 ул.Раисы Окипной 8Б, офисное здание kiev 1 8.282km 12.34 minutes 2018-08-08 10:56 2018-08-08 11:26
10:00 – 12:00 вул.Євгена Сверстюка 11 kiev 1 1.276km 3.26 minutes 2018-08-08 11:29 2018-08-08 11:59
10:00 – 12:00 вул.Євгена Сверстюка 11 kiev 1 0.000km 0.00 minutes 2018-08-08 11:59 2018-08-08 12:29

 

So our benchmark is that every delivery would takes about 30 minutes (service time) to complete after arrival, and we expect that the driver can complete the 6 deliveries within the given time windows.

Analyze data and save delivery costs

analyse and save delivery costs

As mentioned before, now that we have digitalised the operations, all the data would now be stored in the secured data warehouse. Before making further decisions, we need to ask ourselves what we want to know. For the sake of example, let’s look back at the benchmark we set earlier, and see how the driver actually performed on that day and if there is something we can optimise.

While analyzing the actual delivery data, we learned a few things:

  • Since some of the deliveries were to be delivered at the same location, it took the driver less than 30 minutes on average to complete the deliveries. After a month of data collection, we decided to set the average service time to 15 minutes instead. Based on this new benchmark, the customer saved around 90 minutes per route. The driver could complete additional deliveries within the same time slot or the company could simply save on delivery costs by ending the route of the driver earlier.
  • The area in which this customer operates has relatively little traffic congestions, so we learned that every delivery location is reached about 20% earlier than originally planned. In reality, they were too early which frustrated the recipient. At the end, we had to adjust the expected average velocity of the vehicle.

Conclusion

So, how can this work for your (SME or Enterprise) business? Let’s look at the investments required for a fleet of 25 drivers.

Initial investment

  • Android devices: ~US$250 per device – US$6,250
  • Training of staff

Monthly costs

  • Data package phone 1GB: US$7 per month -US$175
  • CarPal Fleet software: starting at US$20 per vehicle – US$500 per month

Costs saved by analyzing data and making small operational improvements:

  • Daily idle time of 90 minutes for 25 drivers and vehicles, assuming they earn around US$15 per hour over a period of 1 month, the total operational saving: US$11,250

In other words, this customer completely made back the initial investment and monthly technology costs by running simple data analysis, and gained a huge saving on the delivery costs just during the first month.

Besides optimizing their internal operations, they have also improved customer satisfaction by making sure drivers do not deliver too early, which is ultimately an important factor for revenue retention, if not a booster for future growth.

 

last mile delivery

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