Predictive Supply Chain

 

Predictive analytics is making a big splash in the logistics and supply chain industry. It provides information today on what we should be expecting tomorrow. One can imagine the benefit it applies to companies in retail or simply any company that faces challenges in logistics or supply chain. There are several predictions that can be done and how the supply chain is going to benefit from that.

Predict the demand of your products

Knowing the popularity of each of the products allows you to optimize your warehouse and the cost of your storage. High demand products, which are usually ordered frequently, should be put in the front of the warehouse, so that the time taken to pick and load reduces. On the other hand, products with lower demand which will not be ordered that often and therefore it can be put in the back of your warehouse. Also knowing the approximate demand of each of your products allows you to manage your inventory well. This will prevent over or under stocking.

Predict the demand of your customers.

Predicting the demand of your customers is slightly different from predicting the demand of your products, but it will give you a lot of new opportunities like knowing which customer will order which products on which day. This will give you more time to optimize your transport and one can make better decisions about outsourcing the orders to other parties. It also helps to optimize your human resource schedules. If you know peaks in your work load beforehand, you can choose to keep less people on standby. This reduces the costs and gives people a more predictable working environment.

Predict machine failure

Machine failure can cause part of the supply chain to slow down or stop completely until the problem is fixed. This can lead to severe costs. These days most machines are equipped with various sensors for various measurements such as temperature and voltage. These measurements can be combined with other information about the machine to predict whether the machine will fail. This allows you to schedule maintenance before the machine breaks. It also allows you to stall the maintenance on machines that are unlikely to fail in the near future. This reduces the cost of your operations. This is called predictive maintenance.

Investing in a predictive analytics solution is no longer an option, it has become a necessity to maintain competitiveness with all of the players who already benefit from emerging predictive technologies. Both consumers and organizations continue raising expectations to receive their shipments faster and cheaper. Therefore, those logistics and supply chain businesses that don’t invest in predictive technologies within their operations, might simply not survive in today’s demanding market.

Reference

https://transmetrics.eu/blog/how-predictive-analytics-is-transforming-logistics-and-supply-chain/

https://www.riverlogic.com/blog/supply-chain-predictive-analytics-what-is-it-and-whos-doing-it

How Data Analytics helps the improvement of Logistics Business?

 Data Analytics are started changing many industries, and logistics is not an exemption. The complex and dynamic nature of this sector, as well as the structure of the supply chain, make logistics a perfect use case for data. Valuable insights obtained through data leveraging allow industry players, for the benefit of both logistics and shipping companies. Although the data have to be highly processed and complex in nature,  it is worth the effort to embrace the data culture as advanced data analytics helps consolidate an industry that has historically been fragmented. The arrival and spread of the use of big data has changed the way organizations operate through their analytics drastically. 

According to the research, as much as 93% of shippers and 98% of third-party logistics companies believe that data analytics is critical to making intelligent decisions. 71% of them believe that big data improves quality and performance. 

Data and analytics are used by logistics firms to improve their activities for the following purposes:

1. Performance Management: Performance managers will turn data findings into actionable outcomes, such as resource use management or distribution paths. For example, shippers expect the drivers to arrive on time, maintain schedules for docking, and avoid wasted time. Data will enable us to understand the performance of the workforce and track it. When data is exchanged amongst partners, it can be used to increase the effectiveness and transparency of the entire supply chain or network.
2. Productivity Improvement: Real-time data sharing with all partners is essential. Especially for a logistics company and its partners, the experiences that a business collects are valuable. By capturing fluctuating customer demand, external factors, and the activities of the partners, this form of data sharing in logistics will help increase operational performance. It will improve accountability and help all stakeholders streamline their processes, thereby enhancing the efficiency of operational processes and the logistics company's overall results.
3. Order Processing Capabilities: Getting accurate, successful integration of data into the systems frees up additional space for new orders to be entered. This eventually leads to further orders being shipped, which further drives demand within the supply chain for the services. As a result, an organization is improving and the amount of logistics data is rising to expose issues within the current processes.
4. Route Optimization: The logistics industry uses data to improve delivery speed and provide real-time visibility of orders to customers. Consumers expect shipments to be fast and trackable easily. Continuously reviewing knowledge to optimize these organizational factors leads to higher quality relationships and enhanced customer loyalty.

The logistics industry is experiencing many changes and is adapting to the modern digital world, like many other industries. Leveraging data through disruptive innovations that allow businesses to provide better and new data and to use it in more robust applications is accelerating the road to a supply chain that is more productive and sustainable.

How technology trends in the supply chain impact businesses

 

Hello all, I am Vikas S Menon and I am a 2^nd year MBA student at Amrita school of business. Hope all are doing well and today’s blog is a sequel to a previous blog I did. If you haven’t read, go through the link below first and read this post.

Link: https://logisticsmatters.blogspot.com/2020/08/eight-technology-trends-in-supply-chain.html

 

So in the previous blog, I have introduced the Eight technology trends in the supply chain. Now I going to explain what it does and the benefits side when business and customer come into the picture.

 

Hyper-Automation: Hyper-Automation is connected with the use of emerging technology, including artificial intelligence and machine learning, to increasingly automate work and improve individuals. Hyper-automation ranges to a variety of tools which can be automated, but also applies to the complexity of the automation that is discovered, analyzed, designed, automated, measured, monitored and reassessed. In plain, hyper-automation refers to the combination of automation technologies that exist to improve and expand human capabilities. Hyper-automation takes on an environment of technologically advanced technologies and integrates them to create a new approach, which ensures that low-value processes are executed optimally using automation tools, machine learning, and advanced artificial intelligence so that results can be generated automatically and run efficiently with very little human involvement. Hyper-automation along with humans can create a working environment that is always informed, agile, and able to use information and insights for quick and accurate decision-making. The benefits of hyper-automation will make it possible for the workforce to learn the latest business and market information so that they can perform their roles efficiently. Some of the other benefits of Hyper-automation in business are increased employee satisfaction and motivation, reduced risk, and greater productivity, accurate insights, and increased team collaboration.

 

Digital supply chain twin: A digital twin is a complete digital version of a physical object or a process in the real world, such as a plant or a supply chain. The benefits of having a digital twin are significant for supply chains. Since it represents the properties, purchases, relationships with third parties, and other operational details of the supply chain, the digital twin allows advanced real-time tracking and adjustment. It offers a comprehensive and in-depth view of the supply chain, enabling the company to rapidly model future scenarios involving changes in production lines, availability of products and personnel, and modification of delivery flows or proactive risk management. The digital twin allows a parallel version of the supply network with the same supply entities, parameters, and financial goals to identify issues and responds to help prescriptive decision-making. This helps management to make fast decisions with a high level of trust in outputs. As industries evaluate how to scale up operations or even move mass production to smaller, more customizable manufacturing, digital twins will help to make supply chain decisions that could allow competitive agility and align with consumer preferences. For example, using digital twins capable of creating improved production schedules with high-speed agility to respond to events in real-time. The Capital intensive industries with complex and highly advanced manufacturing processes are best suited for both supply chain and factory-level digital twins. In the design and investment phase of costly assets, the digital twin could be used to evaluate design possibilities before capital commitments, optimizing productivity and profitability and minimizing risk. The same digital twin can also be used to operate a plant using detailed production planning, that is capable of handling extremely complex and time-dependent procedures that often change with variability in the availability of equipment and people.

 

Continuous Intelligence: Continuous intelligence is a seamless AI-driven solution that enables businesses to benefit from continuous, useful information from all sources. It digs out trends and patterns that allow the company to link intelligent data with the constant goal of discovering new insights. Supported by Artificial Intelligence, Machine Learning, and the right training data, continuous intelligence can also reduce human bias in the process. CI can help an organization in more than one way I.e. by streamlining data to obtain continuous insights, Increases the IT team efficiency, and strengthen the cybersecurity strategy of the organization.

 

Supply chain governance and security: Supply Chain Management and Security is part of Supply Chain Management, which focuses on minimizing risk to supply chain, logistics, and transport management systems. The aim is to identify, evaluate, and prioritize risk management activities through structured defenses in an agile manner. This involves a multi-faceted approach to the security of checkpoints, assets, and infrastructures involved in the manufacture of a product. The benefits in having responsible supply chain governance and security system are verifying proper credentials for all participants in the supply chain, completing background checks on all employees, Training employees to identify and resolve supply chain security risks, conducting a frequent risk analysis of supply chain segments, suppliers and stakeholders, educating staff to identify and fix security risks in the supply chain, monitoring at each point of the supply chain including product quality, and promoting the production of more sustainable goods.

 

Edge computing and analytics: Edge computing is a new and exciting approach to network architecture that helps businesses overcome the limitations imposed by traditional cloud-based networks. Edge computing networks have greatly helped to reduce latency and increase performance. The speed and flexibility of this data handling approach offer an exciting range of choices for organizations. The best benefits of edge computing are Speed (ability to increase network performance by reducing latency), Security (offer a variety of tools clients can use to secure and monitor networks in real-time), Scalability (allowing companies to expand the computing capacity of organization through a combination of IoT devices and edge data centers), Versatility (partnering with local edge data centers - a huge benefit for industries looking to expand network reach into regions with limited connectivity) and Reliability (ensure users retain access to the products and information they need with disruption or by rerouting the data through multiple pathways). The benefits of edge computing in various business are improved healthcare device performance and data management, local & real-time retail data analysis, more vivid augmented reality, accelerated data analytics, smart manufacturing, elimination of excess data, more efficient security systems, real-world data collection, lower operational costs and decreased storage needs, better medical diagnosis and treatment, and customized solutions.

 

Artificial intelligence: AI is the analysis of data to detect trends and anomalies. AI technology gathers and maintains large quantities of data to generate information that will improve or transform operations efficiently and effectively. Technologies that use AI can analyze and model human behavior by recognizing and simulating behavior patterns. Over time, it can predict needs and make appropriate decisions based on its learning and observations. The ways AI impacts business operations are

• Improve Customer Communications and Save Costs: AI-driven chatbots enable companies to provide 24/7 customer service by automating customer conversations, making the experience more personal
• Strengthen Brand Loyalty with Personalization: To provide a customized experience, organizations need to map out individual customer journeys and forecast moments and offers that will improve engagement and drive sales. Customization requires the ability to predict the desires of each consumer. Artificial intelligence can completely automate this process, recognize decision-making trends, and build an identity based on these, and then drive the content that AI has learned is the most appropriate for each individual.
• Streamline the Hiring Process: In highly competitive fields with a limited pool of talent, AI technology decreases the time required to fill open positions, evaluating candidate applications at a faster pace than humans can. 
•  Increase Forecasting Accuracy by decreasing human error with the help of AI.
• AI Unlocks Opportunities: AI would add value to customer service, help create new revenue, and minimize costs.

 

5G Networks: 5G is the next step I.e. the fifth generation of mobile networks. As well as being much quicker than previous G's, it is also expected to open up several new mobile data use cases and potentially new business opportunities. These include the opportunity to introduce brand new products and services that have not been feasible before, migrate to new markets, and improve productivity. The key features of 5G technology are faster network speed, Lower latency, Greater capacity like coping with high demand applications, Ultra-reliable, Flexible, and improved battery life. The benefits of 5G technology in businesses are increased productivity, remote working, Rural innovation, AR or VR support, Low cost for mobile operators, flexible office spaces, Easier to communicate.

 

Immersive experience: Immersive technology include virtual reality, augmented reality, and mixed reality, all of which combine the physical and digital worlds to make a special user experience. The seven ways VR, MR, and AR segments are impacting business operation are,

• Training: Immersive technologies may provide new opportunities to learn; historically, factors ranging from cost to health and safety hindered large-scale adoption or rapid implementation. The key advantage is the low cost and no risk with a high return on investment.
• Prototyping: The ability to build a virtual prototype easily and cheaply, and to work collaboratively, would revolutionize product creation. The key attributes here are speed and ease of use. Adding these considerations to the timeline for product development opens up a tremendous opportunity to try out concepts that were previously overlooked due to cost, time, or both.
• Virtual visits: Immersive technology enables the discovery of previously inaccessible environments. Touring factories that do not yet exist, or pursuing a cellular pathway across the human body which learned in textbooks are two perfect examples.
• Data visualization: Companies use AR to visualize, analyze, and manipulate large data at the workplace. The aim is to increase the toolbox of the data scientist and improve the efficiency and depth of the analysis.
• Gamification: The entire environment was created in an illustrative style, similar to a graphic novel. Students prefer to hold more information when their learning experience is enjoyable and immersive.