Supply Chain
Article | May 26, 2023
Order picking is the most resource-intensive operation of a warehouse or fulfillment center. More than 55% of the operating cost for a warehouse is related to order picking, and fulfillment centers, the number stands at 50%. It is the process that can bring in the most cost savings with an effective, streamlined and efficient order picking system. One of the most important components of your order picking system is the warehouse order picking cart. Order picking carts are used to move inventory from the warehouse shelves to sorting or packing stations. They make it easier for warehouse associates to carry multiple items at a time or to carry large, unwieldy items. When it is possible to carry multiple items on a trip, it drastically reduces the distance traveled by associates on foot. It also helps to reduce physical fatigue and improves efficiency dramatically.
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Warehousing and Distribution
Article | June 27, 2023
Enhance operational efficiency by implementing industry-approved methods for multi-channel inventory management. Taking a holistic approach to control inventory helps multiple sales channels grow.
Multi-channel inventory management is a crucial aspect of the supply chain process that ensures the goods are available to customers through different sales channels. However, with growing penetration of ecommerce technologies and the increasing complexity of supply chain networks, managing inventory across multiple channels has become daunting for businesses. The ability to accurately track inventory levels, ensure stock availability across channels, and optimize fulfillment processes has become critical to achieve success in today's competitive business landscape.
Managing inventory across multiple channels require real-time visibility and tracking of inventory levels which further streamlines the complex process. Inaccurate inventory data can lead to stockouts, overstocking, and lost sales, negatively impacting the business's bottom line. To combat these challenges, businesses must implement a robust multi-channel inventory management system to track inventory across all channels, synchronize stock levels, and automate order fulfillment processes.
An inventory management system can offer businesses a consolidated view of inventory at various locations, such as warehouses, stores, and even online channels. An organized approach is crucial while managing multi-channel inventory or keeping track of moving inventory. Implementing an effective inventory management procedure, managing multi-channel inventory becomes more streamlined and simplified, as well as provides a comprehensive overview.
In addition, as businesses continue to expand their sales channels, multi-channel inventory management has become a vital component of supply chain management. By adopting best practices in multi-channel inventory management, businesses can ensure on-demand access, accurate inventory data, and seamless order fulfilment processes. Additionally, implementing the right procedures will allow organizations to observe an increase in customer satisfaction and experience significant business growth.
The article takes an in-depth look at key benefits, potential challenges, procedural considerations, and the significance of multi-channel inventory management. It delves into the impact of this approach on supply chain performance while providing valuable insights into best practices.
1. Centralize Inventory Management Process
Centralizing multi-channel inventory helps manage supply chain businesses across various channels and locations. Businesses can gain better visibility and control over their inventory processes by consolidating inventory data. However, centralizing inventory management is not without its challenges. One of the major obstacles faced by organizations is ensuring the accuracy and consistency of data across different locations and channels.
Another barrier is integrating various inventory management tools and technologies into a single system. Despite these challenges, centralizing inventory management offers significant benefits, including improved efficiency and reduced costs. In addition, businesses can leverage cloud-based inventory management software and standard operating procedures to centralize and optimize inventory management processes effectively.
2. Adopt Lean Inventory Management Approach
The lean inventory management approach is adequate for managing multi-channel inventory in supply chain businesses. This approach involves reducing excess inventory and only stocking items in demand. While implementation of the approach is complex due to the need for accurate demand forecasting and inventory tracking, it offers multiple advantages, such as reduced inventory carrying costs, improved cash flow, and increased customer satisfaction. To implement a lean inventory management approach in the supply chain business, follow these steps:
Conduct inventory analysis
Categorize items based on value and demand
Implement just-in-time (JIT) replenishment
Leverage forecasting tools
Establish cycle counting and monitoring procedures
Strive for continuous process improvement
This approach helps businesses achieve better inventory accuracy, increase operational agility, and meet customer demands across multiple channels.
3. Utilize ABC Inventory Analysis
ABC inventory analysis is a widely used best practice for multi-channel inventory management in the supply chain. This method categorizes inventory based on its level of importance to the business. ABC inventory analysis categorizes goods into A, B, and C categories based on their impact on overall inventory cost. Category A consists of the most valuable products, category B includes items that fall in between, and category C covers small transactions that are vital for overall profit but have less individual impact. Supply chain businesses can prioritize their resources and make informed decisions by focusing on high-value inventory.
However, implementing this method can be challenging, especially when dealing with extensive inventory data. To successfully address challenges associated with implementing ABC inventory analysis for multi-channel inventory management, businesses must focus on accurate data classification, utilization of advanced analytics tools, and fostering effective team collaboration.
4. Optimize Order Management Process
Optimizing order management involves automating and streamlining order fulfilment for efficient and accurate processing across sales channels. The process ensures optimal inventory control, minimizes fulfilment time, and enhances customer satisfaction, providing a competitive advantage. Aligning inventory levels with actual demand prevents overstocking and reduces holding costs. Additionally, businesses can efficiently allocate inventory from various sources to fulfil orders, reducing the need for excess storage and transportation. The optimization is achieved by adopting automation, system integration, and data analysis. In addition, comprehensive multi-channel order management system offers multiple benefits, including native e-commerce integrations, flexible order fulfilment options, multi-location inventory management, integrated POS capabilities, data-driven inventory planning, and workflow automation, among others.
5. Integrate Sales Channels
Integrating sales channels provides businesses with a unified view of inventory, sales, and customer data, enabling informed decision-making based on real-time information. It helps accurately track products across channels as well as adjust inventory levels based on individual selling rates. The process involves synchronizing channels through a centralized system, ensuring seamless data flow and consistent product information. It includes setting up API integrations, mapping inventory, and conducting thorough testing for smooth order processing. To implement the integration, businesses must utilize technology solutions like inventory management software and enterprise resource planning (ERP) systems. Additionally, it establishes clear communication channels among teams managing different sales channels.
6. Set Cross-Channel Metrics
Cross-channel metrics measure and analyze each sales channel's performance, including online & offline sales, and identify areas for improvement. To set cross-channel metrics for multi-channel inventory, businesses must identify relevant metrics, establish benchmarks, and regularly monitor and evaluate performance. Implementing cross-channel metrics allows businesses to make data-driven decisions based on actual performance rather than relying on assumptions or incomplete data. In addition, supply chain businesses can leverage technology solutions, such as cloud-based inventory management software, to manage and consolidate their data sources effectively. Enforcing cross-channel metrics in multi-channel inventory management helps overcome several challenges, such as lack of visibility across sales channels, difficulty in identifying slow-moving products, and inefficiencies in resource allocation.
7. Automate Supply chain
Automating the supply chain and implementing advanced software systems helps businesses to optimize supply chain processes. Automation reduces manual errors, enhances efficiency, and improves overall productivity. It enables real-time inventory tracking, seamless order processing, and accurate demand forecasting. Businesses can easily overcome manual inefficiencies, bottlenecks, and data discrepancies by automating the supply chain process. The process includes integration of automation tools like inventory management software, order management systems, and warehouse management systems. The systems integrate with sales channels, suppliers, and logistics partners to automate order processing, inventory tracking, and shipment management tasks. Ultimately, businesses achieve better inventory control, faster order fulfilment, and increased customer satisfaction by automating supply chain operations.
Final Thoughts
As the supply chain market evolves, businesses must adopt innovative approaches for multi-channel inventory management. Incorporating additional sales channels into conventional brick-and-mortar operations presents a valuable opportunity to expand customer reach, boost sales, and enhance the overall customer experience. To effectively implement multi-channel sales and inventory management within a retail organization, acquiring a robust retail management system capable of efficiently monitoring inventory levels and facilitating business growth becomes essential. The adoption of an effective system can assist businesses to ensure seamless inventory control and propel sustained success in the competitive market.
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Warehousing and Distribution
Article | July 11, 2023
Transportation has always been the cornerstone of the supply chain and arguably its most targeted area when something goes wrong with a shipment. Why is my package late? What is my load’s current location? What is the ETA for my order? These are the daily questions that come from warehouses, distribution centers, and their end consumers – and they’re being asked now more than ever. Answering these questions requires holistic visibility into your supply chain that can only be achieved with the right mix of transportation technology and data management.
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Supply Chain
Article | May 22, 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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