Supply Chain
Article | May 26, 2023
You might be wondering what the benefits are of benchmarking. Well, imagine you are training for a 100 metre sprint in your district. What would be the key number, or metric that you would need to know?
It would, of course, be what the winning time was when this race was last run in your district. Without that information, you don’t know what you’re trying to target. It would be impossible to know if you’ll have any chance at all of winning the race.
It’s exactly the same in business. If, for example, you are concerned about the pick rates in your warehouse, or your transport costs, or your inventory accuracy, benchmarking can help you because it can show you exactly where your performance is compared to others in your industry.
A few years ago, I was working with an automotive parts business. They had a little issue with their picking productivity in the warehouse. They wondered how good it was, whether they could improve it. They actually thought it was okay.
We looked at the figures and compared them with other businesses. This helped us realise that their picking productivity should be three times better than it was. And believe it or not, over a few months they did begin to improve their productivity.
Why? Because benchmarking opened their eyes to the fact that they were at a level quite far below others in the industry.
That’s the beauty of benchmarking. Until you know what others are doing, you can’t be sure how good your performance is.
If you’ve never tried benchmarking, there are three ways you could do it.
1. Informal Benchmarking
This exercise would involve you measuring particular functions or aspects of your business and comparing that against other parts of your business. Let’s say you have a warehouse operating in one city and another operating in another city. You might start to measure the same metrics and see which one is performing better.
You might know other people in the industry who are also operating warehouses so you might agree to share some data with them.
This is probably the easiest way to start off, but it has some downsides:
You’re only measuring against a very small sample size. If all of you in the pool are not that good, how would you know what good is?
You have to make sure that the businesses are similar and you are measuring things in exactly the same way. It’s very important in benchmarking to have a standard way of applying the metric.
2. Formal Benchmarking
This can work for much larger businesses. Perhaps you have operations in many different countries. You could agree a formal structure for how you are going to measure performance. You could do monthly or quarterly benchmarks with all the parts of your international organisation. You could learn from each other and share best practice.
This method is okay but you’re not getting access to a very large pool of results to measure yourself against. You will find that companies are very reluctant to give out benchmarking data. You might also be operating in an environment where the performance is quite low right across the business.
3. Hire a Professional Benchmarking Firm
This is the ultimate way to do it, although there are not a lot of professional benchmarking firms such as ours around. If you do manage to find one, you will quickly realise that there are significant benefits to be had by bringing in the professionals:
The metrics are put together in exactly the same way: When we do a benchmarking exercise for our consulting clients, we go through a very robust data-gathering process and then make sure all the costs, for example, are in the same buckets as everyone else’s in the database.
You gain access to a big pool of results: Professionals have measured hundreds, if not thousands, of companies. This enables you to say, ‘Our company is this size, it operates in this industry, these are the characteristics of our supply chain, who else in that pool of results is like us? We want to be measured against them.”
It’s no good measuring the performance of a grocery retailer, for example, against an industrial product supplier. They have different supply chains. You need to be measuring like with like.
Read More
Management
Article | June 21, 2023
Automated supply chain planning maximizes efficiency and helps achieve long-term success by addressing challenges, highlighting the benefits, and offering insights to optimize business performance.
Contents
1 Supply Chain Planning System Efficiency Maximization
2 Key Steps of Supply Chain Planning to Boost Efficiency
2.1 Implement Advanced Analytics Tools
2.2 Streamline Communication and Collaboration
2.3 Automate Processes
2.4 Consistency in Performance Improvement
3 Overcoming Major Challenges in the Process to Maximize Efficiency
3.1 Resistance to Change
3.2 Legacy Systems and Siloed Data
3.3 Inadequate Funding
4 Conclusion
1 Supply Chain Planning System Efficiency Maximization
To compete and succeed in an ongoing complex and dynamic global market, companies must maximize the efficiency of their supply chain planning systems, which help manage the flow of goods and services from suppliers to customers, optimize resources and information to meet customer demands and minimize costs and risks. An adequate supply chain planning system can increase customer satisfaction, profitability, agility, and risk management. Moreover, by reducing costs, increasing productivity, and enhancing responsiveness to market demands, maximizing efficiency can help businesses remain competitive. As a result, businesses can gain a substantial competitive edge and position the organization for long-term success by optimizing their supply chain planning systems.
2 Key Steps of Supply Chain Planning to Boost Efficiency
Businesses can significantly boost efficiency in their supply chain planning by implementing advanced analytics tools, streamlining communication and collaboration, automating processes, and ensuring consistency in performance improvement.
2.1 Implement Advanced Analytics Tools
Implementing advanced analytics in supply chain planning is key to improve supply chain efficiency. Advanced analytics tools, including demand forecasting, production planning and inventory management, can help organizations leverage large volumes of data to extract insights that enable better decision-making. The insights can be used to optimize production planning, reducing costs and increasing efficiency. In addition, it also enables businesses to detect and respond to supply chain disruptions on operations.
2.2 Streamline Communication and Collaboration
Managing and streamlining communication becomes essential for supply chain businesses, as it leads to greater agility and enables pipelines to adapt to changes in organizational structures. Leveraging cloud-based communication platforms, video conferencing, and collaboration tools enable real-time information sharing and collaboration across different teams and stakeholders. By enhancing communication and collaboration, businesses can better align their supply chain objectives, reduce communication gaps, and enhance decision-making.
2.3 Automate Processes
The integration of technologies such as order processing, inventory management, and shipment tracking under warehouse automation and logistics automation produces a vast amount of data, making it challenging for businesses to process data manually. To enhance efficiency, automating supply chain planning processes has become essential. Automating the process has eliminated multitasking, including managing goods flow, tracking road progress, and ensuring safe delivery, which was previously required in the manual process. By automating processes, supply chain management can be streamlined, leading to reduced lead times, minimized costs, and improved efficiency.
2.4 Consistency in Performance Improvement
Improving the supply chain is not a one-time fix, but a process that must be reviewed and optimized frequently. By implementing technology, businesses can continuously collect and analyze warehouse inventory management performance to identify areas for further efficiency gains and improved order accuracy. In addition, establishing a framework for continuous optimization involves regular performance reviews, feedback mechanisms, and benchmarking against industry best practices to help identify and address inefficiencies.
3 Overcoming Major Challenges in the Process to Maximize Efficiency
3.1 Resistance to Change
Supply chain planning systems are hindered by change resistance. Employees may resist change who are comfortable with the status quo and adopt new technologies and processes less often. Organizations need a comprehensive change management plan to address stakeholder engagement, communication, and training. Implementing a change management plan starts with identifying the key stakeholders and involving them in planning to gain their buy-in and support for the changes, implementing the process of the changes using different channels to reach all stakeholders and in addition, developing training programs to prepare employees for the changes and enable them to use new technologies and processes effectively.
3.2 Legacy Systems and Silos Data
Data silos and a lack of supply chain visibility are two problems that can arise when legacy systems and data are used. It also adds roadblocks in maximizing efficiency through supply chain planning software. Investing in older systems makes it challenging to gain a comprehensive view of the supply chain and informed decisions making. In addition, the systems are non-compatible with modern technology and data is stored in disconnected systems. With the help of an integrated system, all relevant information can be collected in one place, streamlining monitoring and decision-making. A data governance policy should be implemented to guarantee data quality and uniformity across all platforms. Data management, data storage, data sharing, regular monitoring and reporting on data quality are all essential components of this policy.
3.3 Inadequate Funding
Insufficient funding can affect supply chain planning system efficiency; with budget constraints, organizations may struggle to invest in new technologies, hire skilled workers, or improve processes. Thus, the supply chain planning system may become obsolete, increasing costs, lead times, and customer dissatisfaction. To overcome the challenge of inadequate funding in supply chain planning, organizations must prioritize funding and strategically allocate resources by identifying the areas that require the most investment. Exploring alternative funding sources, such as grants and partnerships, can supplement existing funding and enable organizations to invest in vital initiatives that may not have been possible with limited resources. In addition, cost-cutting measures, such as process optimization and automation, can help to stretch existing funds and boost productivity.
4 Conclusion
The supply chain planning system will continue to play a critical role in maximizing efficiency to revolutionize the supply chain professionals leverage emerging technologies such as AI, ML, and blockchain; understanding the process, identifying the challenges and overcoming them using the right strategies helps businesses in effective supply chain planning systems, gain a competitive advantage, improve supply chain performance and position themselves for long-term success. Furthermore, adopting a data-driven approach and a culture of continuous improvement in supply chain management planning can help organizations plan according to the future of supply chain and compete in the ever-changing global market.
Read More
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.
Read More
Transportation
Article | April 26, 2023
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.
Read More