Warehousing and Distribution
Article | June 27, 2023
Innovations such as AI and automation have been tipped to kickstart the Fourth Revolution. While the technology is being widely adopted, it is constantly evolving. Therefore, there is uncertainty surrounding its overall impact, particularly on professional roles within the supply chain. Some fear that the technology will replace its human counterparts, while other experts suggest it will work in unison with humans, supporting them to focus on higher value opportunities. Amidst all of this uncertainty one thing is for certain: AI and automation will change how we operate.
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Warehousing and Distribution
Article | June 16, 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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Supply Chain
Article | August 17, 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 16, 2022
The logistics sector is experiencing a significant technological shift similar to that of all other industries due to the growing need for remote work solutions. Social networking, the Internet of Things (IoT), cloud-based logistics, and other technological advancements are reshaping the logistics industry and moving it in a new direction. Additionally, the supply chain and logistics as a whole are greatly influenced by factors like transportation and digital transformation.
Modern digital technology is fundamentally altering how various sectors function. Increased connectivity amongst the people has also increased the needs of customers, created new purchasing habits, and gave birth to an entirely new industry as a whole, e-commerce.
The Shift Towards the Could Technology
Over the past few years, the transportation and logistics industry has witnessed a shift towards digitization as more and more people have access to the internet and computer for day-to-day work.
From online grocery stores to local delivery apps and even on-demand airport shuttle services, the adoption of cloud technologies has given a viable solution to customers and businesses at a lower cost than before. As a growing number of businesses reevaluate their use of innovative technologies, cloud computing is becoming an increasingly serious and practical choice.
The cloud is of significant use in the world of freight transportation and logistics, as it stores crucial shipping information that can be accessed at any time via transportation management systems from anywhere. The technology is emerging as a game changer for the businesses operating in the logistics industry. Here is a list of benefits cloud technologies offer:
Logistical space planning
Real-time package updates
Leverage artificial intelligence (AI) and machine learning (ML)
Vehicle health monitoring
E-ticketing management
Final Thought
Cloud-based solutions have enormous potential to improve operational and financial efficiency in the transportation and logistics industry. Some facets of cloud-based solutions also have the ability to transform the overall shipping experience altogether. Assessing the merits of this technology, a large number of leading businesses are incorporating it for applications such as fleet-specific planning, shipment optimization, faster delivery, and others. In the coming years, cloud-based solutions are likely to become very popular in the supply chain industry as they keep getting better.
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