Tag Archives: productivity

Unlocking the Value of Artificial Intelligence (AI) in Supply Chains and Logistics

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Speed in decision-making. Speed in reducing cycle-times. Speed in operations. And, speed in continuous improvement. The use of Artificial Intelligence in the supply chain is here to stay and will make huge waves in the years to come.

According to Gartner, supply chain organizations expect the level of machine automation in their supply chain processes to double in the next five years. At the same time, global spending on IIoT Platforms is predicted to grow from $1.67B in 2018 to $12.44B in 2024, attaining a 40% compound annual growth rate (CAGR) in seven years.

In today’s connected digital world, maximizing productivity by reducing uncertainties is the top priority across industries. Plus, mounting expectations of supersonic speed and operational efficiencies further underscore the need to leverage the prowess of Artificial Intelligence (AI) in supply chains and logistics.

Accelerating Supply Chain Success with AI in Supply Chains & Logistics

AI in supply chains can deliver the powerful optimization capabilities required for more accurate capacity planning, improved demand forecasting, enhanced productivity, lower supply chain costs, and greater output, all while fostering safer working conditions.

The pandemic and the subsequent disruptions has demonstrated the dramatic impact of uncertainties on supply chains and has established the need for smart contingency plans to help companies deal with these uncertainties in the right way.

But is AI the answer? What can AI mean for companies as they struggle to get their supply chain and logistics back on track? Let’s find out.

ACCURATE INVENTORY MANAGEMENT

Accurate inventory management can ensure the right flow of items in and out of a warehouse. Simply put, it can help prevent overstocking, inadequate stocking and unexpected stock-outs. But the inventory management process involves multiple inventory related variables (order processing, picking and packing) that can make the process both, time consuming and highly prone to errors.

WAREHOUSE EFFICIENCY

An efficient warehouse is an integral part of the supply chain. AI-based automation can assist in the timely retrieval of an item from a warehouse and ensure a smooth journey to the customer. AI systems can also solve several warehouse issues, more quickly and accurately than a human can, and also simplify complex procedures and speed up work. Also, along with saving valuable time, AI-driven automation efforts can significantly reduce the need for, and cost of, warehouse staff.

ENHANCED SAFETY

AI-based automated tools can ensure smarter planning and efficient warehouse management, which can, in turn, enhance worker and material safety. AI can analyze workplace safety data and inform manufacturers about any possible risks. It can record stocking parameters and update operations along with necessary feedback loops and proactive maintenance. This helps companies react swiftly and decisively to keep warehouses secure and compliant with safety standards.

REDUCED OPERATIONS COSTS

Here’s one benefit of AI systems for the supply chain that one simply can’t ignore. From customer service to the warehouse, automated intelligent operations can work error-free for a longer duration, reducing the number of human oversight-led errors and workplace incidents. Additionally, warehouse robots can provide greater speed and accuracy, achieving higher levels of productivity – all of which will reflect in reduced operations costs.

ON-TIME DELIVERY

As we discussed above, AI systems help reduce dependency on manual efforts, thus making the entire process faster, safer and smarter. This helps facilitate timely delivery to the customer as per the commitment. Automated systems accelerate traditional warehouse procedures, removing operational bottlenecks along the value chain with minimal effort to achieve delivery targets.

 

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Chinese New Year: Tips to Keep Your Supply Chain Efficient!

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Chinese New Year

Chinese New Year: Tips to Keep Your Supply Chain Efficient!

Chinese New Year is just around the corner, and more and more freight companies are working on how to sustain productivity and efficiency.

For small businesses that are new to experiencing this holiday, during Chinese New Year, some China-based companies are temporarily shutting down their activities to celebrate and administer different superstitions to have a healthy and prosperous New Year.

And this is also the time of year where freight demands shoot up, prices increase, and containers easily become full making it expensive and difficult to import.

In this infographic, we will discuss different tips on how your supply chain can keep up this Chinese New Year. Here are a few considerations that you can apply:

Confirm your Supplier’s Schedule

Making sure that you verify on your supplier’s schedule which days they would not be operating makes you also adjust the timing of your operations. Being mindful and alert with your suppliers especially in places where different holidays are celebrated gives you time to maneuver and interact smoothly with your supply chain.

Place your Orders in Advance

As mentioned earlier, consulting your suppliers beforehand with their schedules can help you adjust to their absence, and this also applies to the flow of your orders. Placing your orders in advance won’t only help you avoid delays, it will also help you manage your expenses and find space for your shipments.

Collaborate with a Trusted Local Freight Forwarder

As your company grows, more and more reliable freight partners are merging to aid your supply chain dilemma and goals. In times where different holidays are celebrated, it is essential to find help with local freight forwarders to help you cope up with your scheduled deliveries.

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How To Improve Supply Chains With Machine Learning: 10 Proven Ways

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Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionizing supply chain management in the process.

Machine learning algorithms and the models they’re based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. From Amazon’s Kiva robotics relying on machine learning to improve accuracy, speed and scale to DHL relying on AI and machine learning to power their Predictive Network Management system that analyzes 58 different parameters of internal data to identify the top factors influencing shipment delays, machine learning is defining the next generation of supply chain management. Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions. Gartner is also predicting by 2023 intelligent algorithms, and AI techniques will be an embedded or augmented component across 25% of all supply chain technology solutions.

The ten ways that machine learning is revolutionizing supply chain management include:

  1. Machine learning-based algorithms are the foundation of the next generation of logistics technologies, with the most significant gains being made with advanced resource scheduling systems.
  2. The wide variation in data sets generated from the Internet of Things (IoT) sensors, telematics, intelligent transport systems, and traffic data have the potential to deliver the most value to improving supply chains by using machine learning.
  3. Machine learning shows the potential to reduce logistics costs by finding patterns in track-and-trace data captured using IoT-enabled sensors, contributing to $6M in annual savings.
  4. Reducing forecast errors up to 50% is achievable using machine learning-based techniques.
  5. DHL Research is finding that machine learning enables logistics and supply chain operations to optimize capacity utilization, improve customer experience, reduce risk, and create new business models.
  6. Detecting and acting on inconsistent supplier quality levels and deliveries using machine learning-based applications is an area manufacturers are investing in today.
  7. Reducing risk and the potential for fraud, while improving the product and process quality based on insights gained from machine learning is forcing inspection’s inflection point across supply chains today.
  8. Machine learning is making rapid gains in end-to-end supply chain visibility possible, providing predictive and prescriptive insights that are helping companies react faster than before.
  9. Machine learning is proving to be foundational for thwarting privileged credential abuse which is the leading cause of security breaches across global supply chains.
  10. Capitalizing on machine learning to predict preventative maintenance for freight and logistics machinery based on IoT data is improving asset utilization and reducing operating costs.

Read more at How To Improve Supply Chains With Machine Learning: 10 Proven Ways

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How Humans and Robots Will Work Side-by-Side in the Supply Chain

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Humans and robots can work in harmony to create a safer, more efficient working world, here’s what that world might look like.

Robots and Humans Working Together
In Robots in the Supply Chain: The Perfect Employee? Merril Douglas paints a picture of a time in the near future when robots and humans will work side-by-side to help companies gain speed, increase accuracy, cut costs, and handle the grunt work.

“We’re sitting in the middle of a perfect storm for robots in the supply chain. E-commerce sales continue to climb, forcing retailers to pick up the pace in their fulfillment and distribution centers,” Douglas writes.

“But these days, it’s hard to find workers to keep product moving in any kind of warehouse e-commerce or otherwise.”

We’re already seeing examples of robots being designed to take over the supply chain’s least attractive tasks. “In some cases, robotic systems do this work entirely on their own, freeing humans for more complex functions,” Douglas points out.

“In other instances, bots collaborate with humans. Whatever the scenario, proponents say that these automated solutions provide a big productivity boost.”

Some companies are deploying robots to perform repetitive, simple job tasks and allowing human laborers to focus on tasks that require deeper thinking and strategizing.

The new term for this collaboration, “cobot,” allows each type of worker to focus on the tasks they do best.

For example, bots can be used to deliver products from place-to-place in the warehouse, DC, or yard; autonomous drones can perform mundane and repetitive inventory management tasks (as well as tasks that are dangerous for humans, such as flying up to view inventory on high shelves); and robots can lift shelving units from densely-packed storage areas and then transport those goods to a picking station.

Read more at How Humans and Robots Will Work Side-by-Side in the Supply Chain

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Microsoft Reinvents its Supply Chain by Leveraging SAP Ariba & Intrigo Systems

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Microsoft Corp. has one of the most complex supply chains in the world.

And to keep it humming and ensure supply keeps up with demand for its hottest products, the company is reinventing its supply chain.

In a newly released Webcast (watch the video above), the company discusses how it is teaming with SAP Ariba and Intrigo Systems to create a scalable, modern platform to support the efficient, cost-effective manufacturing of its most popular products, including the Xbox and Surface.

“At Microsoft, our mission is to empower every person and organization on the planet to achieve more. And our strategy to achieve this is to build best-in-class systems and platforms and productivity systems,” said Ali Khaki, Principal PM, Supply Chain Engineering, Microsoft.

“When we looked at our supply chain, it was clear we needed to build a flexible, scalable platform that could support the complexity of our hardware business.”

And it is using SAP Ariba solutions for direct spend to do it.

“The Ariba® Network is the backbone for Xbox and Surface line of products supply chain,” Khaki said.

Through the Ariba Network and the cloud-based applications delivered on it – including SAP Ariba Supply Chain Collaboration™, Microsoft has created a modern platform from which it can safely and easily collaborate with multiple tiers of contract manufacturers and suppliers across key supply chain planning and execution processes, including:

  1. Sharing production forecasts, orders, quality, and inventory information.
  2. Anticipating and resolving supply assurance problems.
  3. Onboarding suppliers.

Read more at Microsoft Reinvents its Supply Chain by Leveraging SAP Ariba & Intrigo Systems

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The Analytics Supply Chain

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Businesses across many industries spend millions of dollars employing advanced analytics to manage and improve their supply chains. Organizations look to analytics to help with sourcing raw materials more efficiently, improving manufacturing productivity, optimizing inventory, minimizing distribution cost, and other related objectives.

But the results can be less than satisfactory. It often takes too long to source the data, build the models, and deliver the analytics-based solutions to the multitude of decision makers in an organization. Sometimes key steps in the process are omitted completely. In other words, the solution for improving the supply chain, i.e. advanced analytics, suffers from the same problems that it aims to solve. Therefore, reducing inefficiencies in the analytics supply chain should be a critical component of any analytics initiative in order to generate better outcomes. Because one of us (Zahir) spent twenty years optimizing supply chains with analytics at transportation companies, the concept was a naturally appealing one for us to take a closer look at.

More broadly speaking, the concept of the analytics supply chain is applicable outside of its namesake business domain. It is agnostic to business and analytic domains. Advanced analytics for marketing offers, credit decisions, pricing decisions, or a multitude of other areas could benefit from the analytics supply chain metaphor.

Read more at The Analytics Supply Chain

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