Supply Chain
Article | May 22, 2023
The pandemic has had a significant impact on the logistics and shipping sectors, forcing businesses to rethink their supply chain tactics. Fresh COVID- Supply systems around the world are already under threat from 19 outbreaks. China's measures to stop the spread of Omicron by shutting down shipping terminals caused a lockjam of cargo ships. A similar scenario was seen in US and European ports that were congested as a result of a significant increase in cargo.
Additionally, these difficulties have been made worse by the tremendous staff shortage in the US. Although there are more job openings than before, the total strength of the workforce has taken a hit. A report by WNS and Corinium Intelligence reveals that over 60% of shipping and logistics organizations have amped up the automation aspect of their operations by two years. So, what does that mean for the future? In this article, we will talk about the four most promising trends that will define the shipping and logistics industry in 2025.
Live Monitoring Powered by Big Data and the Digital Twin Technologies
Big data is simplifying the ability to be agile, efficient, and cost-effective, and connectivity with other technologies and elements of the infrastructure is driving a real-time view of the supply chain further. Other innovations such as drones and self-driving trucks will contribute to this real-time update and processing of massive amounts of data. In addition, tracking software for freight will provide even greater visibility to customers and enterprises.
Automated Planning Through Collaboration Between Humans and Machines
Artificial intelligence (AI)AI in shipping and logistics has grown exponentially in areas of planning. AI applications are used to alter transportation and route planning. According to Gartner, by 2030, AI augmentation, will surpass other forms of AI application and account for 44% of all AI-powered value. Predictive alerting is a prominent example of augmented intelligence. Smart alerts based on predictive analytics can be used by logistics professionals to carry out a variety of crucial tasks, such as estimating truck arrival times, anticipating equipment maintenance and product damage, and organizing for a spike in demand.
Hyper-local Supply Chains
Enterprise will downsize and bring their supply chains onshore over the course of the next few years, ushering in the next generation of hyper-local logistics. The two forces driving this transition are the need to stay agile and resilient to counter disruption and meet challenging customer demands for same-day delivery. The global same-day delivery market is estimated to reach a value of USD 20.36 billion by the year 2027. This will cultivate a hyper-local service to meet the growing demand.
Sustainability
An emphasis on sustainability will be the highlight of the shipping and logistics industry. Enhanced connectivity will enable enterprises to optimize their human as well as robotic resources.
Future Forward
The shipping and logistics industry has been forced to accelerate their digital adoption and increase their resilience due to the uncertainty in the past couple of years. Establishing real-time visibility, leveraging human-machine collaboration, adopting hyper-local logistics, and improving sustainability are all ways that businesses are preparing for the future.
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Management
Article | June 21, 2023
Unlock operational efficiency and deliver exceptional customer service with a WMS. Learn how cloud-based WMS improves control, enhances customer service, and prepares businesses to develop & succeed.
Contents
1. Importance of Warehouse Management Systems
2. How Warehouse Management Systems Optimize Operations
2.1. Productivity Tracking
2.2. Inventory Control
2.3. Labor Management System
2.4. Slotting
2.5. Batching Logic
3. Essential Warehouse Operations Procedures
3.1. Inbound Logistics Process
3.2. Outbound Logistics Process
5. Conclusion
1. Importance of Warehouse Management Systems
A warehouse management system (WMS) is essential for optimizing warehouse operations and delivering exceptional customer service. There are five compelling reasons to consider implementing a WMS. Firstly, it enhances inventory control and management by reducing inventory levels, improving order fulfillment, and increasing accuracy. Secondly, it improves customer service and tracking through improved picking accuracy and automated shipment organization. Thirdly, a WMS boosts company productivity by adding warehouse efficiency and quality control to the fulfillment process. Fourthly, it provides a significant return on investment by improving sales accuracy, reducing errors, providing safe warehouse and simplifying customer support. Lastly, a good WMS integrates seamlessly with existing business management systems and adapts to evolving needs. Additionally, WMS enables businesses to meet compliance regulations through real-time data recording, enhanced business intelligence, and process automation.
2. How Warehouse Management Systems Optimize Operations
2.1. Productivity Tracking
Warehouse management systems (WMS) are crucial in optimizing operations by providing comprehensive productivity tracking tools. These systems capture and analyze key performance indicators (KPIs) such as order fulfillment rates, picking accuracy, and labor productivity. Organizations can identify bottlenecks, allocate resources effectively, and implement process improvements by tracking these metrics in real-time and generating insightful reports. With WMS productivity tracking, businesses gain a clear understanding of their operational efficiency and can make data-driven decisions to enhance overall performance.
2.2. Inventory Control
Efficient inventory control is essential for logistics warehouse management, and WMS solutions excel in this aspect. WMS provides real-time visibility into inventory levels, locations, and movements. Businesses can accurately track stock levels, monitor expiration dates, and implement automated replenishment warehouse processes. With advanced features like cycle counting and stock level alerts, WMS ensures inventory accuracy and reduces carrying costs. By optimizing inventory control, businesses can avoid stockouts, minimize excess stock, and improve order fulfillment rates, enhancing customer satisfaction.
2.3. Labor Management System
WMS incorporates a robust labor management system that enables businesses to allocate and manage their workforce effectively. These systems provide tools for labor planning, task allocation, and performance tracking. WMS optimizes labor allocation by assigning tasks based on employee skills, availability, and workload. By monitoring labor productivity and efficiency, businesses can identify opportunities for improvement and implement training programs to enhance employee
performance. With WMS labor management capabilities, organizations optimize labor costs, minimize overtime, and improve overall operational efficiency.
2.4. Slotting
Strategic slotting is a critical component of warehouse optimization, and WMS offers advanced slotting capabilities. By analyzing data on product demand, turnover rates, and order frequency, WMS determines the optimal locations for different products within the warehouse. Efficient slotting reduces travel time, minimizes congestion, and streamlines order picking. WMS enables businesses to assign appropriate storage locations based on product size, weight, and velocity. By optimizing slotting strategies, organizations can significantly enhance picking efficiency, reduce errors, and improve overall warehouse productivity.
2.5. Batching Logic
Batching logic is a key feature of WMS that enhances order-picking efficiency. WMS intelligently groups multiple orders with similar product requirements, locations, or delivery routes. By consolidating these orders into batches, the system enables batch picking, where a picker can fulfill multiple orders in a single trip through the warehouse. Batching logic reduces travel time, minimizes labor costs, and increases order picking speed. By maximizing picking efficiency, businesses can improve order fulfillment rates, reduce order cycle time, and meet customer expectations effectively.
3. Essential Warehouse Operations Procedures
A robust distribution center network serves as the backbone of operations, transforming raw materials into finished products and ensuring their timely delivery to customers. To gain a comprehensive view of logistics network and improve supply chain visibility, it's crucial to understand the distinction between inbound and outbound logistics.
3.1. Inbound Logistics Process
Inbound logistics encompasses the services required to bring materials and goods into businesses. This includes transportation, storage, and delivery processes. With the help of warehouse management systems (WMS), purchasing can be streamlined by synchronizing vendor details and inventory control levels. WMS allows efficient receipt scanning and guides warehouse staff to shelve items accurately. It also recommends optimal put-away, slotting, and storage space utilization techniques. Additionally, WMS facilitates reverse logistics by providing real-time information on product availability, enabling timely restocking and preventing stockouts.
3.2. Outbound Logistics Process
Outbound logistics focuses on the storage, transportation, and delivery systems that ensures finished products reach their final destination. WMS plays a vital role in this process as well. It enables accurate order picking through barcode or RFID scanners, reducing errors and ensuring the right products are chosen. Warehouse management processes integrated with WMS can automate product packaging, allowing for differentiation across sizes and optimizing packaging channels. Moreover, WMS simplifies printing shipping labels, price tags, logos, and other necessary documentation, eliminating manual data input and reducing human errors. WMS enhances the overall customer experience and minimizes fulfillment errors by ensuring timely delivery and notifying customers.
4. Implementing Cloud Warehouse Management Systems to improve productivity
Using a cloud-based warehouse management system offers several advantages for businesses looking to optimize their inventory control and streamline operations in complex distribution environments. Cloud supply chain management solutions provide benefits like multi-warehouse tracking, sales forecasting, and on-time delivery. Here are three key benefits of implementing a cloud WMS:
Increased control over business growth: Cloud-based WMS provides real-time visibility into inventory, allowing businesses to manage operations and make informed decisions efficiently. With automatic updates and centralized access, stakeholders can access relevant information anytime, enabling better control over business growth and flexibility to adapt to changing market demands.
Improved customer service: A cloud WMS empowers teams to track shipments, update arrival dates, and effectively manage the supply chain. It enables seamless communication and collaboration across the organization, ensuring timely deliveries and enhancing customer satisfaction. Efficiently conveying information leads to better customer service and a competitive edge.
Preparedness for upcoming changes: Cloud WMS offers an affordable and scalable warehousing solution. With cloud computing, businesses can easily adjust resources to meet fluctuating demands and seasonal changes. The ‘self-service’ access to WMS applications in the cloud allows for increased agility and quick adaptation to evolving business needs. Unlike traditional self-hosted systems, cloud WMS eliminates the need for upfront hardware investments and provides seamless scalability.
5. Conclusion
In the rapidly evolving business landscape, a warehouse management system (WMS) holds immense importance for organizations aiming to optimize their operations. As we look to the future, the role of WMS becomes even more crucial. With advancements in technology and the advent of new platforms, a cloud-based WMS offers unparalleled integration possibilities. By harnessing the power of cloud supply chain planning systems, businesses can gain better control over their inventory and navigate the complexities of modern distribution environments. The benefits are significant: increased control over business growth, improved customer service through real-time tracking, and preparedness for upcoming changes. By embracing cloud, WMS empowers businesses to stay agile, enhance productivity, and drive sustainable success in the dynamic business landscape of the future.
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Transportation
Article | April 26, 2023
Data volume in supply chains is usually enormous. Analytics applied to the supply chain help make sense of the pile of information by identifying patterns and drawing conclusions.
Contents
1 Importance of B2B Supply Chain Analytics
2 Obstacles in Supply Chain Analytics Integration
2.1 Barriers in Collecting and Processing Data
2.2 Insufficient Technical Skills
2.3 Issues in Managing and Integrating Data
2.4 Inadequate Analytics and Insights Generation
3 Addressing Supply Chain Analytics Complexities for Better Decision-Making
3.1 Leveraging External Expertise
3.2 Enhancing Collaboration and Communication
3.3 Improving Data Quality and Governance
3.4 Developing Analytics Capabilities
4 Power of Successful Supply Chain Analytics Integration in Transforming Businesses
5 Conclusion
1 Importance of B2B Supply Chain Analytics
Supply chain analytics has become a pillar of contemporary business strategy, enabling organizations to leverage data insights and enhance vital supply chain processes. By utilizing real-time data analytics, businesses can streamline their supply chain operations, boost productivity, and increase customer satisfaction. With unparalleled visibility into key performance indicators, B2B supply chain analytics provide the opportunity to identify inefficiencies, reduce costs, and react swiftly to ever-changing market dynamics, streamlining the process for supply chain business analysts who manage supply data.
Leveraging the power of supply chain analytics tools is important for the success of modern businesses in the age of data-driven decision making. With the ability to optimize inventory levels, manage lead times, and reduce transportation costs, supply chain data analytics provides a competitive advantage that can increase the efficiency, productivity, and profitability of businesses of all sizes and in all industries.
2 Obstacles in Supply Chain Analytics Integration
Supply chain analytics integration has become increasingly critical for companies seeking to optimize their supply chain operations. However, several obstacles hindering successful implementation often complicate the integration process; hence, understanding and knowing them in advance is vital for smooth operations.
2.1 Barriers in Collecting and Processing Data
Effective data collection and processing are critical in generating accurate insights to drive supply chain analytics decision-making. However, it comes with challenges; the most critical obstacle is data silos, where data is stored in isolated systems or departments, leading to difficulties in accessing and integrating it. It gets more complex when different departments or partners use varied data formats or standards. Additionally, cleaning and processing data is also challenging, as it involves identifying and eliminating duplicates, inconsistencies, and errors that can negatively impact analytics accuracy.
2.2 Insufficient Technical Skills
Successful supply chain analytics integration depends heavily on technical skills and knowledge. Insufficient technical talent and expertise are significant barriers to successful integration. The integration process requires specialized technical expertise and the supply of skilled professionals with expertise in ETL, statistical analysis, knowledge of ML, IoT, SQL, and more in managing supply chain analytics Talent lacking technical skills cannot accurately interpret data, leading to ineffective
decision-making. Preliminary data analysis, processing, and visualization due to a lack of technical expertise results in suboptimal decision-making, which can be costly for businesses.
2.3 Issues in Managing and Integrating Data
Data integration combines data from various sources and formats to create a unified view. However, businesses face data governance, quality, and standardization issues, resulting in incomplete or inconsistent data. Lack of accurate information reduces the efficiency of supply chain analytics and impacts decision-making. Additionally, data management is complex, and business face difficulties creating effective data management processes, resulting in problems related to storing, retrieving, and updating data.
2.4 Inadequate Analytics and Insights Generation
Obtaining valuable insights from enormous data collected during the supply chain process requires advanced analytics tools and technologies. Many businesses, however, continue to rely on traditional reporting methods, which limit the range and complexity of insights generated. The lack of expertise in data analysis and visualization can lead to poor interpretation and use of data, resulting in suboptimal decision-making. In addition, businesses experience difficulty identifying relevant data sources or may struggle to establish the necessary data governance frameworks to ensure data quality and accuracy.
3 Addressing Supply Chain Analytics Complexities for Better Decision-Making
Supply chain analytics can provide valuable insights, but the complexities involved in analyzing and interpreting data can be a significant hurdle. Learning the strategies for addressing these complexities to improve decision-making in supply chain management has become essential.
3.1 Leveraging External Expertise
Leveraging external expertise can be a powerful strategy for addressing supply chain analytics complexities related to collecting and processing supply chain data during integration. External experts bring specialized skills, experience, and knowledge that may not be available in-house, enabling organizations to overcome talent shortages and expand their capabilities. Furthermore, consultants, data scientists, or technology providers provide an objective viewpoint on the organization's data and processes, identifying areas for improvement and optimizing performance. By collaborating with external experts, organizations can access the latest tools, technologies, and best practices, ensuring that their supply chain analytics are up-to-date and relevant.
3.2 Enhancing Collaboration and Communication
Enhancing collaboration and communication can effectively address the challenge of insufficient technical skills in thriving supply chain analytics integration. By promoting cooperation and cross-functional communication, organizations can leverage the skills and expertise of team members from various departments to fill gaps in technical knowledge. This approach can also help to break down data silos and improve data sharing and integration. In addition, collaboration and communication can facilitate knowledge transfer, enabling team members to learn from one another and develop a more comprehensive understanding of the supply chain analytics process. Ultimately, this can lead to improved decision-making, as a more skilled and knowledgeable team can generate more accurate and insightful analytics.
3.3 Improving Data Quality and Governance
Businesses ensure accuracy, completion, and up-to-date data by establishing standardized processes and protocols for collecting, storing, and analyzing data. Data quality checks, including data cleansing and normalization, can help eliminate errors, redundancies, and inconsistencies that can negatively impact the accuracy and usefulness of analytics. In addition, effective data governance, including establishing data ownership, security, and privacy policies, helps ensure that data is managed and shared appropriately across the organization. As a result, it reduces the risk of data breaches, compliance violations, and other data-related issues, ensuring that organizations have access to reliable data for better decision-making.
3.4 Developing Analytics Capabilities
Developing capabilities significantly help organizations overcome inadequate analytics and insights generation challenges in analytics integration. Investing in advanced analytics tools and platforms like technical skills, data infrastructure, and advanced supply chain analytics techniques help businesses generate real-time, accurate, and actionable insights from collected data. Developing analytics capabilities requires creating a culture that values data and analytics, establishing robust data governance frameworks, upskilling the workforce and creating cross-functional teams collaborating on data-related projects. In addition, it helps businesses gain a competitive advantage.
4 Power of Successful Supply Chain Analytics Integration in Transforming Businesses
Effective supply chain analytics integration is revolutionizing business operations. Real-time and supply chain predictive analytics have helped businesses gain unmatched transparency in their supply chains, enhance critical processes, improve operational efficiency and customer satisfaction, and experience revenue growth and profitability. The ability to identify inefficiencies and supply chain optimization opportunities enables businesses to effectively allocate resources and reduce expenses. In addition, successful supply chain analytics integration enables businesses to respond quickly to changing market dynamics, optimize inventory management, and strengthen the resilience of their supply chains.
Businesses are leveraging the power of big data analytics to disrupt and transform supply chain at all levels. The concept of data, which was once a fundamental component of digital supply chain transformation, is now revolutionary. Therefore, it is essential to achieve advancements in supply chain analytics integration and management.
5 Conclusion
With technological and data analytics advancements, businesses can utilize real-time data insights to make data-driven decisions, optimize supply chain processes, and improve customer experiences. Integration of supply chain analytics is crucial for supply chain businesses of all sizes. Utilizing supply chain analytics software can further streamline integration as well as enhance data analytics and supply chain management.
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Software and Technology, Logistics
Article | July 8, 2022
Introduction
From warehouse robots to delivery drones, the supply chain is experiencing a tremendous upheaval. AI promises a totally autonomous and self-organized future supply chain. A fleet of vehicles utilizing a swarm algorithm can enhance cargo yard throughput; a trusted peer-to-peer ledger on blockchain architecture could change compliance in the sector; and wearables, mobile robotics, and machine learning technologies could speed up order fulfilment. IOT e-brokerage solutions can link shops to couriers and transporters with a click. Tomorrow's supply chain will be leaner, quicker, and self-organized. A few innovative technologies will fuel this unparalleled rate of change over the next 15 years. Here are the major technologies that are shaping the future of the logistics industry.
Logistics Technologies for the Future
Shipment Tracking Systems
Previously, customers ordered shipments, had an anticipated arrival date, and then were kept in the dark until they chose to call. Customers can now access shipping and tracking systems around-the-clock due to developments in the internet and software. This not only enhances the customer experience (cx), but it also saves the business time and money.
Internet of Things (IoT)
The IoT reduces costs and delays by minimizing hazards in the supply chain. Cabs, cargo ships, trains, etc., have sensors that link to an alarm system or dispatcher. These sensors analyze and communicate information to the crew, who learns about hidden threats. IoT isn't a new technology, but it continues to influence logistics by improving in-transit visibility and delivery.
Radio Frequency Identification (RFID)
RFID technology has been used for a few years to monitor inventories labor-efficiently. A product tag or sensor produces radio waves. The company processes the data. RFID tags are similar to barcodes, but their faster information transport and data processing appeal to companies and the direction of technology. Many organizations use RFID tags to track containers in warehouses.
Enhanced GPS Accuracy
Almost everyone utilizes GPS on their vehicles or smartphones. These devices' accuracy has improved over time, assisting lost drivers and enhancing the supply chain. By monitoring truck locations and boosting hauls with current traffic data, GPS increases efficiency and customer satisfaction.
Closing Lines
Unprecedented times have produced unprecedented transformations that will last for generations. Changing demographics, technology improvements, and COVID-19 impacts are altering global supply networks. We must understand the driving factors and act on what we learn to adapt and rise to the situation. For the sake of our current workforce and future generations.
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