Transportation
Article | April 26, 2023
Efficient demand forecasting techniques transform supply chain management, help optimize inventory levels, streamline operations, improve customer satisfaction, and achieve a competitive edge.
Contents
1. How Accurate Demand Forecasting Impacts Business Operations and Profitability?
2. Navigating the Pitfalls of Traditional Demand Forecasting
2.1 Limitations of Manual Forecasting Methods
2.2 Inaccuracy and Inconsistency in Demand Prediction
2.3 Multiple Products and Markets Challenges
2.4 Influence of External Factors on Demand Forecasting
3. Advanced Demand Forecasting Techniques for Supply Chain Management
3.1 Statistical Forecasting
3.2 Collaborative Demand Planning
3.3 Demand Sensing and Real-time Data Analytics
3.4 Agile Supply Chain Management Practices
4 Summing up
1. How Accurate Demand Forecasting Impacts Business Operations and Profitability?
Accurate demand forecasting plays a vital role in determining the operations and profitability of a business. By anticipating future demand, companies can more effectively plan their production, inventory management, and supply chain activities to meet customer needs while minimizing costs.
Additionally, accurate demand forecasting can aid businesses in enhancing customer satisfaction by proactively meeting customer needs and expectations, improving customer experiences and increasing customer loyalty. To generate actionable insights that drive informed decision-making, businesses must leverage advanced analytics and predictive modeling techniques that combine data from various sources with industry-specific knowledge and expertise.
“Businesses that leverage advanced analytics and predictive modeling techniques for demand forecasting report an average of 5% improvement in their supply chain efficiency.”
(Source: A survey by Deloitte)
Supply chain businesses frequently rely on sales data from the past, which may not be sufficient in the complex and rapidly changing business environment. Businesses might not observe an improvement in operations and profitability if they rely solely on conventional methods.
2. Navigating the Pitfalls of Traditional Demand Forecasting
As businesses strive to optimize their supply chain operations and meet customer demand, traditional demand forecasting methods can often hinder their efforts. In this context, it is essential to navigate the pitfalls of such techniques to achieve success in supply chain management.
2.1 Limitations of Manual Forecasting Methods
Manual forecasting methods have limitations that can affect demand forecasting accuracy in supply chain management. Frequently based on historical data, these methods can overlook emerging trends in supply chain management and alterations in customer behavior. In addition, manual processes are time-consuming, prone to error, and incapable of incorporating real-time supply chain data. As a result, businesses struggle to optimize supply chain operations and meet customer demand.
In addition, traditional forecasting methods can influence the ability to accurately predict demand, resulting in overstocked inventory, delivery delays, and, ultimately, poor customer satisfaction. Inaccurate demand forecasts can also result in poor purchasing decisions and increased carrying costs, negatively impacting profitability.
2.2 Inaccuracy and Inconsistency in Demand Prediction
Inaccuracy and inconsistency in demand forecasting pose significant obstacles in managing the supply chain. This is the case in the dynamic business environment, where market conditions can change rapidly, making it challenging for companies to keep up with shifting demand patterns. As traditional demand forecasting methods depend heavily on historical data, they produce inaccurate forecasts that do not reflect real-time market changes.
In addition, inconsistency in demand forecasting can also result in a mismatch between supply and demand, leading to missed opportunities or excess inventory. As a result, creating an effect on company’s bottom line in addition to customer satisfaction.
2.3 Multiple Products and Markets Challenges
Accurate demand forecasting is crucial to the success of supply chain management. When there are multiple products and markets to manage, it becomes a challenge for traditional demand forecasting. Different products and markets may have varying demand patterns and drivers, making it difficult for businesses to accurately forecast demand.
Manual processes and siloed data can hinder visibility and the ability to identify cross-product or cross-market trends, making supply chain optimization operations and meeting customer demand more complex. Managing multiple products and markets is one of the challenges of traditional demand forecasting when businesses operate in various markets with varying customer preferences and demand patterns for products.
2.4 Influence of External Factors on Demand Forecasting
External factors can significantly impact the demand forecasting accuracy for supply chain optimization. These factors are often unpredictable, and conventional methods may not account for them. The external factors affecting the supply chain include natural disasters, economic recessions, and sudden changes in consumer behavior.
In addition, political and regulatory modifications, such as tariffs or trade agreements, can affect the supply and demand of particular products. Therefore, businesses must incorporate these external factors into their demand forecasting models and advance the process, as traditional demand forecasting methods cannot predict accurate future demand patterns and ensure optimal supply chain operations.
3. Advanced Demand Forecasting Techniques for Supply Chain Management
To avoid the above-mentioned pitfalls, companies need to adopt advanced demand forecasting techniques that enable capturing and analyzing huge data from various sources to generate accurate and real-time demand forecasts.
3.1 Statistical Forecasting
Statistical forecasting is an advanced method for demand forecasting in supply chain management that utilizes complex algorithms and statistical models to analyze historical data, identify trends, and generate forecasts. This method employs numerous statistical techniques, including regression analysis, time-series analysis, and exponential smoothing, among others.
Statistical forecasting can help businesses overcome some of the limitations of traditional manual forecasting methods because it is more objective, data-driven, and capable of identifying trends and patterns which are not apparent with manual forecasting methods. As a result, by utilizing statistical forecasting, businesses can increase demand forecasting accuracy, optimize inventory management, and better align supply and demand, resulting in enhanced customer satisfaction, greater efficiency, and lower costs.
3.2 Collaborative Demand Planning
Collaborative Demand Planning combines intensive forecasting algorithms to predict future demand and a set of ML techniques to achieve better demand forecasting. It involves collaboration between suppliers, customers, and other stakeholders. The advanced data and insights sharing technique improve the comprehensive understanding of demand drivers and trends, leading to more accurate demand forecasting. The collaborative approach enables real-time adjustments to demand forecasts, which can help businesses respond promptly to market conditions and customer demand changes.
In addition, using advanced analytics and machine learning algorithms can help identify patterns and trends that would otherwise go unnoticed. That enables businesses to optimize inventory levels, reduce under and overstocking, and enhance customer service levels. In the dynamic business environment, it helps transform the supply chain that is better equipped to meet the ever-changing demands of customers.
3.3 Demand Sensing and Real-time Data Analytics
Demand Sensing and Real-time Data Analytics are advanced demand forecasting techniques that can assist businesses in overcoming the challenges that multiple products and markets pose to the supply chain. By utilizing real-time data from various sources, such as social media, point-of-sale systems, and weather reports, businesses can better understand customer demand patterns, adjust inventory and production planning, reduce delay, and increase responsiveness.
In addition to implementing demand sensing, businesses can begin with sell-in data obtained from supply chain planning or an ERP system in supply chain management and then incorporate all relevant data sources and external factors to broaden the forecasting horizon.
3.4 Agile Supply Chain Management Practices
Agile supply chain management practices are a collection of methodologies and strategies emphasizing supply chain operations' adaptability, responsiveness, and flexibility. These practices involve utilizing real-time data analytics, collaborative planning, and other advanced technologies to enable businesses to respond swiftly to changes in customer demand, market conditions, and other external factors.
Adopting an agile model allows the organization to act swiftly and decisively and achieve successful business outcomes despite adverse conditions. Agile supply chain management practices can give companies greater visibility and control over their supply chains, enabling them to adapt more effectively and efficiently to fluctuating market conditions in the context of external factors influencing demand forecasting. By cultivating a culture of continuous improvement, innovation, and customer value, agile supply chain management practices have the potential to transform into modern supply chain.
4. Summing up
Demand forecasting accuracy is crucial for supply chain management and profitability. Manual forecasting methods hinder operational optimization and customer demand fulfillment. Customer satisfaction, purchasing decisions, and carrying costs suffer from inaccurate forecasting. In order to avoid these pitfalls, businesses can leverage statistical forecasting and collaborative demand. These methods recognize trends and patterns, optimize inventory levels, reduce over- and under-stocking, and improve customer service using advanced analytics and machine learning algorithms.
As the supply chain evolves and becomes more complex, businesses must adopt advanced demand forecasting techniques. Implementing these techniques will enable businesses to optimize their supply chain management by better-aligning supply and demand, resulting in increased productivity, decreased costs, and ultimately increased profits.
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Warehousing and Distribution
Article | July 17, 2023
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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Supply Chain
Article | May 26, 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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Software and Technology, Logistics
Article | July 20, 2022
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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