Key Factors of Supply Chain Inbound Freight Management
Co-Author: Sufi Julfikar
A supply chain freight management can be divided into 2 sections, inbound and outbound. We would be covering the basics of inbound freight management and the key factors to manage this.
What is inbound freight management?
Inbound freight management deals with managing inbound shipments for various combinations like vendor/suppliers to warehouse/distribution centers/fulfillment centers/direct shipment to retail sites/multiple shipping points (or consolidation centers) etc. The below diagram refers to only one combination.
If inbound freight is managed properly then it can lead to improvement of on-time deliveries, reduction in wastages, reduced freight costs, increased customer service, etc.
Key factors that need major attention while managing Inbound Freight which helps in inbound logistics run smoothly:
Supplier/Vendor:
From which source & where you are bringing the goods. It can be Local, Domestic & International. Local refers to in & around 50miles from your Distribution center which means your transportation cost will be minimal.
The most important consideration here is to map all the transportation legs between the Source and Warehouse to foresee the problems.
Consolidation of Goods:
Many organizations would think of having FTL (Full Truck Load), to achieve this data transparency is important with suppliers.
How the goods are consolidated, as you will be bringing in various types of goods which require additional attention like some needs to be Refrigerated/Frozen, Chilled.
There are trailers which include Ambient, Refrigerated/Frozen, chilled in one trailer which has multiple compartments, the size and other details to suppliers would help in planning, preference for acceptance of orders.
Transportation Mode selection:
By which mode you are bringing in the goods, through Road, Rail, Sea or Air. Most of the time we would be using at least two modes. These modes of transport have an intense effect on Supply Chain management.
The decision is hard to make but considering certain factors like Item size, durability, and when to reach/deliver we can choose the transportation mode.
Carrier type Selection:
Before going to a third party or requesting for proposal do some basic analysis of lead time with carriers; locations to cover; frequency of trips; any other requirement apart from general ones. These data can be gathered by Transportation Management.
Plan for additional costs if coverage in a specific geographical area or any additional service is required.
Give your requirements in clear such as on-time performance, equipment type, availability, etc., and it's better to have the capability to allocate freight to carriers.
Distance:
Shippers send lanes to carriers typically once per year. Lane details mainly consist of Origin Zipcode + Destination Zipcode + Estimated Volume.
Carriers provide rates in terms of “Rates/Cost per mile”.
Surge/Spot pricing covers volume over-committed capacity.
According to the latest data, the average trucking cost per mile in the U.S. is $1.82. So, if one of your trucks drove 100,000 miles last year, you spent $182,000 to keep that single truck on the road.
The problem comes when businesses plan vehicle routes manually. This manual planning often ignores key factors such as historical road conditions and average speeds etc. It’s better to have Automated Vehicle Routing which helps in cutting the route time and the distance.
Drivers and their Driving behavior:
Some techniques can be utilized to improve miles per gallon,
Optimizing behavior by monitoring the time spent by drivers on top gear & idle time.
Train drivers to shift up through the gears more effectively to reduce the strain on the motor and how they can spend the most time in cruise control.
It’s better to use the latest technologies like Advanced Vehicle Experience trucks which can result in utilizing them efficiently. The most important highly recommend here is, to provide Drivers more comfort & convenience by opting for the sleeper Flex Studio with a fold-out bed along with necessary other features.
Freight Type:
Mainly 2 freight type exists, one is Prepaid, other is Collect. Many are moving to Collect from Prepaid to have ownership on accessorial, linehaul, fuel surcharge costs.
In Collect, the organization have more rights and does not depend on either supplier/3PL (3rd party)
When both Prepaid & Collect are performed with the due diligence it saves time when used in a correct situation as it remains a constant influencer of freight rates and can have significant cost reductions and overall control.
Unloading:
Managing Inbound shipments in terms of arrival of trailers, allotting them lanes to unload the goods has a good chance of control of the process which gains more precision.
When opting for Prepaid/3PL, it's better to have integrated software so the transportation companies themselves can sign up for a time slot convenient for them to load and unload materials. This also alerts us if any of the trucks is missed or delayed, so it can be planned for later arrival at the dock.
From this step of “Unloading” onward the Inbound DC (Distribution center) operations’ journey starts.
There are several ways to Optimize the above factors for that we must have Data to be accurate, timely, and comprehensive.
We must also have the objectives that we specify what we want to accomplish with logistics optimization.
Models are the way we translate operational requirements and constraints into something the computer can understand and use in algorithms. We need models to represent how shipments can be combined into loads for a truck. A very simple model such as the total weight/volume of the shipments will faithfully represent some loading requirements.
Variability must be considered explicitly, as it occurs in almost all supply chain and logistics processes. For example,
- Travel time varies from trip to trip.
- The number of items to be picked at a DC differs from day to day.
- The time to load a truck varies from truck to truck.
Integration of data must be fully automated, because of the large amount of data that must be considered by logistics optimization. For example, optimizing deliveries from a warehouse to stores each day requires data regarding the orders, customers, trucks, drivers, and roads. Manually entering anything other than very minor amounts of data is both too time-consuming and too error-prone to support optimization.
Transportation Management system (TMS):
TMS suites/vendors play a big role in inbound freight management for any organization. You can see Gartner’s 2021 Magic Quadrant of Transportation Management systems. TMS suites like Blue Yonder, Oracle, etc. are in the leaders' quadrant. Most of the TMS suites/vendors provides over-the-road planning, execution, track and trace, load design, asset-based/fleet-based routing and scheduling, multimodal capabilities, etc.
Most TMS vendors support all basic capabilities, their ability to support advanced capabilities, such as detailed planning/optimization and modal coverage, varies significantly. Not all TMS vendors can support complex transportation networks, especially for enterprises that require strong support in multiple locations across the globe.
Select your TMS vendor as per your organization's need and the type of business.
Data and technical implementation — Reference Architecture :
Below we are showing the high-level Data and technical implementation architecture for Supply Chain freight management. Multiple technical solutions can exist, we have shown one such implementation as a generic example. Tools you can select based on your need and every tool comes with its own value propositions.
In the above diagram, we are showing both fast and slow paths for data ingestion, you can select which path to adopt based on your need.
- In the fast path or rather I would say stream path, you have to first select the standards and protocols based on your need. Various standards exist in the industry like MQTT, HTTP2, HTTP, Profinet, Modbus, Websocket, SNMP, and many more.
- For streaming ingestion, you can select confluent managed services or standalone Kafka or any other services based on your need and use case. In case if you are using confluent cloud or standalone Kafka services then you would need to configure Kafka connectors for downstream systems.
- This layer is divided into the Staging and ETL layers. You need a consumer to consume data producer (Streaming layer). Further raw data can be processed by ETL tools to clean and curate the data as per need. Feel free to select any ETL tool as per your suitability.
- Final processed and to be consumed data can be stored in any format based on what cloud services you are using. Don’t forget to implement proper Data Quality(DQ) and Data lifecycle management (DLM) rules to properly manage data in this layer. Also, you can measure data readiness via various tools available in the industry.
- The entire 3rd and 4th layers are proposed to launch in the Cloud ecosystem, select any cloud provider based on your suitability. This would be treated as your Single Source of Truth (SSOT) Data Lake.
- Entire Data ingestion if done through batch mode (non-streaming mode), then you can use any JDBC/ODBC services to get data from the ODS layer. In few cases, you might not find ODS layers and thus you can hit directly the transactional systems (but this is not the preferred way in many cases).
- To orchestrate the entire solution you can have one Orchestration tool from start to end.
- Implement a Data Security layer, for both Data in transit and data at rest.
- Both raw and processed data can be exposed to the Data Visualisation layer. You can select any tool based on your need. Based on the selected tool architecture either you have to go via Data Federation or Data Hydration methods. Some tools allow push-down optimization as well to faster response time.
- Similar to Data visualization tools there are a lot of services or tools for Data Querying, you can select any tool from the industry based on your need. Mainly data analysts, data stewards, business analysts leverage this layer heavily.
- For data science and analytics purpose, you can select from various existing tools. Based on where the tool is getting launched you have to opt for Data Federation vs Data Hydration from DataLake.
