Improving decision-making through Transport Management Systems

The light long overdue was shed on the logistics industry when supply chains broke down during the Covid-19 pandemic. Supply chain professionals were always the advocates and understood the criticality, but when grocery store shelves started to stock out, the world realized its importance. Global spikes of approximately 25% in e-commerce businesses and the 'convenience' factor that these businesses have been pitching to customers since their emergence was finally demonstrated. This led to a rising investor interest, specifically in how transport management can facilitate in instilling efficiency across the network. The result was a sudden boost in start-up funding and a growth in new business models tapping into quick-commerce, delivery as a service etc.

Visibility became a hot topic for companies which were now requiring more flexibility and agility across their supply chains. 'A McKinsey survey of senior supply-chain executives in the second quarter of 2021 showed that 77 percent of companies planned to prioritize investments in supply-chain visibility.?This finding is confirmed by a Kenco survey in which 90 percent of respondents reported that supply-chain visibility is a top priority.'

Transport management refers to the coordination and management of the movement of goods and people from one location to another. Transportation is a critical aspect of supply chain management and logistics, and can impact the efficiency and effectiveness of an organization's operations. Some common strategies include:

1. Mode optimization: Selecting the most efficient and cost-effective mode of transportation for a given shipment, such as using trucks for short distances and ships for longer distances.

2. Network design: Optimizing the layout of transportation routes and hubs to minimize costs and transit times.

3. Capacity planning: Anticipating and managing the demand for transportation services to ensure that adequate capacity is available at all times.

4. Fleet management: Optimizing the use of vehicles and equipment to reduce costs and improve efficiency.

5. Collaboration and partnership: Working closely with suppliers, customers, and other stakeholders to share information, coordinate activities, and achieve common goals.

6. Advanced technology: Using technology such as transportation management systems (TMS), GPS tracking, and automated dispatching to improve visibility, control, and responsiveness.

7. Sustainability: Implementing sustainable practices to reduce environmental impact and improve social responsibility.

All of these strategies aim to improve the efficiency, reliability, and cost-effectiveness of the transportation system, while also taking into account social and environmental considerations.

Data plays a critical role in transport management by providing the information needed to make informed decisions about transportation routes, modes, and costs. Data can be used to track the movement of goods and people, monitor transportation performance, and identify areas for improvement.

Some examples of data that may be used in transport management include:

1. GPS data from vehicles, which can be used to track the location and movement of goods and people in real-time
2. Data on traffic patterns, weather conditions, and other external factors that can impact transportation routes and schedules
3. Data on transportation costs, including fuel costs, labor costs, and equipment costs
4. Data on the performance of transportation providers, such as delivery times and reliability

By using data to inform transportation decisions, organizations can optimize their transportation operations and reduce costs, improve efficiency and customer service.

With the advancements in technology, data can be collected and analyzed in real-time using IoT (Internet of things), AI (Artificial Intelligence) and ML (Machine Learning). This enables transport management to make quick decisions, predict and prevent issues and improve overall performance. A handful of ideas where these technologies can be used are:

1. Route Optimization: Optimizing routes for delivery trucks and vehicles to reduce fuel consumption and travel time.

2. Predictive Maintenance: Predicting vehicle failures and scheduling maintenance based on real-time data.

3. Traffic Flow Prediction: Predicting traffic flow patterns to optimize the management of road networks.

4. Autonomous Vehicles: Developing self-driving vehicles to reduce the number of accidents caused by human error.

5. Demand Forecasting: Forecasting demand for transportation services to improve supply chain management.

6. Fraud Detection: Detecting fraudulent activities in transport and logistics operations.

7. Customer Service: Improving customer service through the use of chatbots and virtual assistants.

8. Inventory Management: Optimizing inventory levels in transportation and logistics operations to reduce waste.

Some real life examples of organizations using these technological advancements are as below.

1. Amazon: Using AI and machine learning for warehouse management, route optimization, and predictive maintenance of delivery vehicles.

2. UPS: Implementing machine learning for demand forecasting, route optimization, and real-time tracking of packages.

3. DHL: Using AI for supply chain optimization, predictive maintenance, and route optimization.

4. FedEx: Implementing machine learning for demand forecasting, real-time package tracking, and fraud detection.

5. XPO Logistics: Using AI for predictive maintenance, route optimization, and predictive modeling of delivery schedules.

6. J.B. Hunt: Using machine learning for demand forecasting, driver behavior analysis, and trailer utilization optimization.

7. C.H. Robinson: Implementing AI for demand forecasting, carrier selection, and fraud detection in logistics operations.

8. Convoy: Using machine learning for real-time carrier matching and load optimization in the trucking industry.

An understanding of the importance of management of transport is key for execution and thereby improving overall efficiency of the business and its economics. To date, many large firms struggle to fully comprehend the implications of mismanagement of transportation and continue to use legacy systems and practices. Post COVID-19, the transportation management system market was valued at $5,968 million in 2020, and is projected to reach $11,367 million by 2027 at a CAGR of 9.6%.

(Source https://www.alliedmarketresearch.com/transportation-management-market-A06268 )

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