Top 15 Supply Chain Events to Attend in 2023

Software and Technology, Supply Chain

Article | July 18, 2022

Oracle, a leading provider of computer technology, published a paper analyzing how supply chain managers should use change as a catalyst in "inspiring and engaging employees." In the report, Oracle highlights how organizations across the world are going through radical shifts in the way they operate. Customers need quick, convenient, and customized solutions today. Employees also have higher expectations, looking for companies that are a match for their values, provide flexible working arrangements, and offer cutting-edge tools. Shareholders and investors also want more, which forces businesses to focus on making money in ways that are sustainable and diverse. See Change as an Opportunity The companies that are most successful, according to Oracle, are those who see change as just another opportunity to reinvent, and the company lists four ways supply chain leaders might find such an opportunity: Boost employee engagement Aim for sustainability and responsibility in management Be quick to respond to disruptions in the supply chain Exceed consumer expectations In the paper, Oracle reports that instead of adapting to the change, organizations must be able to stay on top of challenges and prepare well in advance. Align with an Employee-Centred Culture Leaders must be able to attract well-matched talent, with the skills to not just fulfil job roles but also drive innovation. Today, people value a work-life balance where they have time to pursue their non-work interests, spend time with their families, and create a diverse, and inclusive world. According to Oracle, this is a significant consideration, and organizations that meet the demands of this new workforce will have a competitive edge in hiring the top talent. Looking Forward The Great Resignation has been a hot topic in HR, but the truth is it affects all aspects of business, and importantly, the supply chain, and in the end, the ability to provide smooth customer experiences. HR, customer experience, and supply chain leaders must synergize to become an employer destination to reckon with in order to succeed.

Supply Chain

Article | August 17, 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.

Software and Technology, Supply Chain

Article | August 3, 2022

Leveraging technology and resources within a network is key to supply chain optimization. While supply chains are inherently complex, this complexity can lead to significant technological benefits. Contents 1 Overview and Importance of Emerging Technologies in Optimizing Supply Chain 2 Advantages of Incorporating Emerging Technologies in Enhancing Optimization 2.1 Autonomous Delivery 2.2 Cognitive Automation 2.3 Blockchain-enabled Traceability 2.4 Predictive Maintenance 3 Key Challenges in Adopting Emerging Technologies 3.1 Cost and Budget Constraints 3.2 Skills Gap in Talent 3.3 Privacy and Data Security Concerns 4 Overcoming Challenges 4.1 Adopting Technologies for Managing Budget and Cost 4.2 Developing Talent Pipeline 4.3 Implementing a Zero Trust Security Model 5 Future Outlook Supply chain optimization involves maximizing the utilization of technology and resources within a supply network. Although supply chains are inherently complex, this complexity can yield significant technological advantages, particularly when leveraging the combination of blockchain, artificial intelligence (AI), and Internet of Things (IoT) technologies. 1 Overview and Importance of Emerging Technologies in Optimizing Supply Chain Emerging technologies have transformed the supply chain industry and revolutionized business operations. AI, IoT, blockchain, and robotics are getting prominence with the ability to streamline supply chain processes, reduce costs, increase efficiency, and ultimately boost customer satisfaction. Implementing these technologies can give businesses real-time supply chain visibility, reducing waste and enhancing inventory management. Understanding the potential benefits of these emerging digital supply chain technologies and how they can be implemented within the supply chain is essential for any business that intends to stay in a competitive and rapidly evolving market. 2 Advantages of Incorporating Emerging Technologies in Enhancing Optimization Blending operations with emerging supply chain technologies can significantly improve the speed and accuracy of information flow, minimize manual intervention, and reduce lead times. Additionally, these technologies can provide enhanced visibility into supply chain operations, enable effective risk management, and facilitate proactive decision-making. 2.1 Autonomous Delivery Incorporating autonomous delivery that comes with self-driving vehicles benefits businesses beyond faster delivery times, lowers costs and reduces human error. It offers increased safety, greater flexibility, and improved resource management. It benefits industries like e-commerce and logistics, where quick and efficient delivery is crucial. 2.2 Cognitive Automation Businesses face significant challenges due to unpredictable fluctuations in supply and demand, which can strain their existing technology. To mitigate these risks, executives have increased their investments in risk management. Cognitive automation offers three key benefits in supply chain management: identifying challenges and opportunities, gathering demand signals, and utilizing data for decision-making. Cognitive automation makes balancing supply and demands more efficient and effective, allowing businesses to act faster. 2.3 Blockchain-enabled Traceability Blockchain technology, a distributed ledger system, enables secure, transparent, and traceable record-keeping across a supply chain network. By providing a tamper-proof record of product movement and quality, blockchain technology can enable businesses to verify the authenticity and integrity of their products at each stage of the supply chain. In addition, blockchain technology allows businesses to quickly trace product origins and identify affected batches during recalls. 2.4 Predictive Maintenance Predictive maintenance is a technology that uses machine learning algorithms and Internet of Things sensors to predict impending equipment failures. By analyzing equipment performance data, predictive analytics enables businesses to reduce equipment downtime, lower maintenance costs, and increase reliability. With predictive maintenance, businesses can transition from reactive to proactive maintenance, preventing equipment failures and extending equipment lifecycles. 3 3 Key Challenges in Adopting Emerging Technologies 3.1 Cost and Budget Constraints The executives in the supply chain industry face a significant challenge when adopting emerging supply chain technologies due to the associated costs and budget constraints. While these smart supply chain technologies offer long-term benefits, the upfront investment can deter businesses. Businesses need to consider the total cost of ownership, including implementation, training, ongoing maintenance costs, and the potential return on investment. 3.2 Skills Gap in Talent Incorporating emerging technologies and trends in supply chain operations management is a complex and costly investment that demands a highly skilled workforce to implement and operate such supply chain technologies successfully. A significant skills gap while adopting technology in the supply chain industry poses a challenge for businesses in finding and training competent personnel with technical, analytical, and business skills required to handle emerging technologies. 3.3 Privacy and Data Security Concerns As supply chain operations adopt cutting-edge technologies, companies must address privacy and data security issues. The use of technology requires the collection and dissemination of sensitive data across multiple parties, which raises security and privacy concerns that can be exploited by cybercriminals or unauthorized personnel. Failure to adequately address these issues may result in reputational harm, legal and financial penalties, and a loss of customer confidence. 4 Overcoming the Challenges 4.1 Adopting Technologies for Managing Budget and Cost To overcome the challenge of budget and cost constraints in adopting technology in the supply chain, businesses can leverage innovative tools, such as cost management software and advanced analytics tools, which can provide real-time visibility into cost drivers and enable better decision-making to optimize resource utilization. With the top three technologies in supply chain such as AI, IoT and blockchain, businesses can reduce costs, boost supply chain performance, and maintain market competitiveness. AI predicts demand, maximizes inventory and improves transportation; RPA automates manual tasks, reduces labor costs, and cloud computing provides a flexible and scalable IT infrastructure with reduced upfront investments. 4.2 Developing Talent Pipeline Businesses must invest in building a talent pipeline to ensure a steady supply of skilled employees to narrow the skills gap in the supply chain industry. Collaboration with educational institutions, in-house training programs, and managed service providers from the technology industry can all be part of the answer. The organization's competitiveness and success can be increased by creating a talent pipeline to fill the skills gap between the current workforce and the needs of emerging technologies. Businesses can keep their workforce current and ready to adopt new technologies in supply chain by investing in a talent pipeline. 4.3 Implementing a Zero Trust Security Model As businesses adopt emerging technologies for supply chain operations, privacy, and data security, concerns have become a formidable obstacle. The implementation of a zero-trust security model can aid in addressing this difficulty. Before gaining access to any data or system, all users and devices in this model must be authenticated as potential threats, per this model. This strategy protects data and systems from unauthorized access and enables businesses to comply with regulations such as the GDPR and CCPA. In addition, it can provide supply chain visibility and control over data access in real-time, making it more effortless to detect and respond to security threats. 5 Future Outlook Supply chain leaders view emerging supply chain technology as a competitive advantage and as a means to address digital transformation. In addition, there is a focus on supply chain technologies that improve human decision-making and manage assets at the edge. Organizations should unify their technology portfolio and update legacy systems for greater efficiency. As supply chain complexity increases, we can expect even more advanced technology solutions leveraging big data, machine learning, and robotics to create agile, flexible, and sustainable supply chains.

Article | April 15, 2020

The rapid growth of e-commerce continues to create new challenges for retailers as they plan distribution strategies. One of those challenges is managing the high volume of returns. One in three shoppers returns items, and more than half read a company’s returns policy before making a purchase. Retailers lose $50 billion annually due to inefficiencies in processing returns, and distribution centers handling returns need 15% to 20% more space than a traditional facility.