Artificial Intelligence Archives

Building Profitability with Agility while Digitally Transforming the Supply Chain

Business Intelligence | By Terence Leung • 04/15/2021

Many companies were in the midst of digitally transforming their supply chain when the Convid-19 pandemic hits. During that time, with great volatility, many companies struggled to keep pace with increasing customer expectations around delivery on-time.

In my Logistics Viewpoints article in January 2021, “The New Definition of Supply Chain Agility and Resilience in an Unpredictable World”, I highlighted that modern supply chains must be built on a foundation of extreme agility and responsiveness. As the world is seeing evidence that we are closer to the light at the end of the tunnel and looking forward to the post pandemic recovery era: agility, resilience, and consistent (not just when absolutely needed) responsiveness will be the new competitive differentiators. In this part 2 article, let us continue to explore the concrete actions we can take in our Digital Supply Chain journeys.

Some companies chose to forgo the transformation initiatives to focus on dealing with disruptions to their business. Some chose to carry on with their digital journeys as they must find better ways as the physical and operational logistics footprint were changing rapidly to adapt to the new customer-first, eCommerce expectations. Almost a year after the outbreak, in their session about “GE Appliances’ High-Speed Upgrade of Its Digital Supply Chain” at the 25^th Annual ARC Industry Forum event, GE Appliances discussed how they continued to take on that Digital Supply Chain Journey at the outbreak, so that they can track shipments from manufacturing plants in real-time or anticipate disruptions with machine learning (ML) that could slow customer deliveries.

Plan and Execute for Success

Some manufacturing, consumer brand, retail and logistics service companies made ambitious goals to delight customers through digital transformation but in some cases significantly eroded profit margins. Some organizations invested in solutions that offer little more than knee-jerk reactions, resulting in not-obvious improvement to the bottom-line or even net losses.

Before the pandemic, in a study of logistics providers conducted by Fraunhofer IML, among those embarking on digitalization initiatives, only 25% of logistics providers in the Fraunhofer IML survey are leveraging digital technologies to think outside the box and reinvent their foundational delivery model. These forward-looking companies understand that digital transformation is their means to reinvent themselves, leapfrog the competition, increase agility, and establish themselves as strategic, long-term partners with their customers. While this is encouraging, 75% see digitization as a way to either replace existing analog processes with digital ones or support new processes for customers within their existing operations.

Now, logistics providers are accelerating the pace to adopt new technologies to serve customer-first and eCommerce expectations. At our Blue Yonder ICON event later in April this year and 3PL Execution Forum in June, 3PL and 4PL companies will explain how they are leveraging innovations as an advantage. The supply chain can increase its visibility by leveraging AI and analytics to identify internal or external anomalies that are the first signal of a disruption. What comes after that is the leveraging of AI and its ability to make autonomous decisions across the end-to-end supply chain when disruptions do occur. By leveraging the analysis of historic events and probabilistic outcomes, new technologies can pull the right levers to correct supply chain performance, with much less or no human intervention.

The Key to Long-Term Success: Build Agility, Resilience and Profitability Together

As supply chain managers decrease their focus on exception management and tactical intervention, they can devote their time and attention to more strategic activities such as market research, outsourcing and data science. In addition, the worlds of planning and execution is converging, with the gap between demand, production, and logistics closing.

From an inbound operations perspective, visibility continues to be a common thread in facilitating this convergence. From an upstream point-of-view, raw material availability, visibility, sourcing and timing will continue to be the primary areas of focus, particularly with organizations looking to mitigate any new market disruptions. Today, companies are realizing that having excess inventory, logistical expediting, and promotions without tight supply chain execution, without unifying logistics, and without a scientific basis may not be the solution and. In fact, it may lead to increased variable costs.

Ideally, with this convergence, the demand data should be shared upstream with suppliers and other trading partners, creating a new demand fulfillment strategy and a collaborative response to any deviations from plan. It should also be shared downstream. In the upcoming hyper-connected world, the entire network can proactively sense and respond to potential supply chain disruptions caused by major events such as natural disasters and pandemics, as well as smaller events such as local weather, port congestion, equipment failure, capacity shortages and labor shortages.

The Crucial Role of Trading Partners

An example is carrier network services for executing a cohesive set of first-, middle- and last-mile operations and optimizing common carriers and fleets. Connected via a common technology platform, the supply chain partners can respond to unexpected demand volatility caused by social media, news reports or special events. The traditional supply chain has often been characterized by blind spots, which are caused when a lack of collaboration makes trading partners unable to see key information such as product location, available-to-promise inventory or a realistic customer delivery date.

These blind spots can no longer be tolerated in today’s environment of extreme volatility and high customer expectations. In a survey published by the Council of Supply Chain Management Professionals (CSCMP), siloed systems and/or processes were named the single greatest barrier to driving supply chain innovation and improving the customer experience. In addition, 46% of the companies deemed “most innovative” in the study reported having 80-100% electronic connectivity with their trading partners. Supply chain partners that are unable to share data may struggle to find a common ground and collaboratively respond to demand and supply volatility as a single, linked entity.

Fortunately, IoT, AI and ML are converging to illuminate this kind of critical information and create true visibility, and responsiveness, across the supply network. All trading partners can see potential disruptions in the product flow to the marketplace, while also gaining a probabilistic view of the potential impacts. In addition to seeing upstream supply obstacles, all trading partners can also recognize downstream fulfillment issues such as low inventories or labor shortages. In the same Fraunhofer IML study cited earlier, 81% of logistics service providers say that market demand for digital collaboration and transparency along the supply chain is a “very strong” (36%) or “strong” (45%) influence on their business. It will be interesting to compare the results in future surveys as eCommerce propels better management of logistics operations each-es in additional to bulk.

At SodaStream, which provides 1.5 billion liters of homemade sparkling water to millions of homes globally, advanced warehouse solutions are leveraged to avoid delay to the plan-to-order process and enable more efficient order fulfillment and inventory management processes.

At Swedish appliance leader Electrolux, technology investments have been continuing to link its geographically distributed, highly complex worldwide supply chain and encourage close collaboration both internally and externally. Selling 60 million products annually in 150 countries, Electrolux has been viewed as a leader in adopting digital supply chain solutions that facilitate this collaboration and focus the entire value chain on the end consumer. A 2018 academic paper authored by researchers at the University of Southern Denmark noted, “Electrolux is the company in the worldwide household appliances industry with the widest geographic reach, also product-wise….Electrolux is balancing between globalization and localization in the different key value chain functions, searching to take the best from the two.”

Leverage Digital Journeys to Win

Both upstream and downstream signals will increasingly pull products from supplier warehouses and corporate distribution centers alike and affect tactical transportation and other logistics related plans. While the advanced technologies are available to support the level of agility required for an uncertain world, often the barrier to successful adoption is cultural. But the journey to improve must accelerate, unified logistics and advanced technologies will support the hyper-connected supply chain to come. We will continue to explore the steps in the digital journey (such as on-demand transportation, labor, and warehousing) and examples of determination from the top in addition to logistics operations.

Terence Leung is Senior Director, Solutions Marketing at Blue Yonder. He has a keen interest in digitalization and the value it generates throughout the supply chain. In this role, he leads his organization to drive thought leadership and go-to-market strategy for supply chain execution and logistics solutions. In addition, he works with customers to understand requirements and drive best practices.

Prior to joining Blue Yonder, Terence was the leader in product marketing and value engineering at One Network. Previously, he was in leadership positions in industry management at Savi Technology and solutions and management consulting at i2 and Deloitte Consulting respectively. Terence holds an MBA from the University of Texas, Austin and an Electrical Engineering degree at MIT.

ToolsGroup Discusses Supply Chain Planning, Machine Learning, and the Covid Pandemic

Supply Chain Planning | By Chris Cunnane • 03/10/2021

As part of ARC Advisory Group’s Supply Chain Forum last month, I had the opportunity to speak with Kathleen Geraghty, Vice President of North American Sales at ToolsGroup. During our conversation, we touched on a number of topics around the supply chain planning market. You can watch also the full interview below.

Specifically, I asked Kathleen to give me her insights on why the supply chain planning market has continued to grow during the ongoing pandemic while many other software markets have shrunk. I asked what other major market trends she is seeing right now. And finally, I asked her about the role artificial intelligence and machine learning play, and what should customers understand before selecting a supplier. Below are some key points from our discussion.

Supply Chain Planning Market

The Covid pandemic hit supply chain markets quickly and shined a very bright light where there were vulnerabilities. Those companies that couldn’t react to disruptions were hit the hardest. In North America, that initial impact started with the offshore suppliers closing and they were unable to fulfill orders. Then there was a global logistics bottlenecks. At the same time companies were dealing with supply volatility that was impacting demand uncertainty. Covid has underlined the need to be resilient. There is now a keen awareness that disruptions can happen suddenly, and software can bring agility and resilience while providing visibility.

Major Market Trends

There are a number of other trends in the supply chain planning space. ToolsGroup recently released its annual predictions for the year ahead. The first one is around the trend of digital transformation to accelerate agility. Business models that eventually would have changed have accelerated, such as direct to consumer. This convergence is fueling multiple initiatives.

Planning capabilities continue to grow in adoption to build more resilience by expanding multi-echelon distribution networks. This is also centralizing planning and increasing simulation capabilities. This all introduces more complexity but can bring great value.

There is a focus on alternate sourcing and substitution options. Companies are looking to shorten and localize supply chains, which creates a tradeoff in higher manufacturing costs balanced against reducing inventory and lowering logistics cost.

Finally, there is a movement toward best of breed solutions at the forefront. Namely, companies are abandoning the fact that everything has to come from one solution or supplier. It is now about building more integrated sets of solutions.

Machine Learning

Machine learning and artificial intelligence continue to be a hot topic. Companies need to understand what machine learning and artificial intelligence are. In the end, companies cannot let a supplier shape their view of what it is and how they can use it.

About ToolsGroup

ToolsGroup is a global supply chain planning software company. ToolsGroup helps companies maintain or improve target service levels while minimizing inventory. It calculates the probability of demand to optimize inventory and delivers service levels companies can commit to customers. It comes down to having the right product at right time and right place while consuming least amount of working capital.

Digital Transformation Journey in Supply Chain Planning

Business Intelligence | By Asena Denizeri • 03/04/2021

Remember those times when we used to stroll down the block and find local stores such as the mom-and-pop diners and get the chance to relish the coziness and sense of family environment there. Even mom-and-pop stores and diners had to step up their digitalization game with the pandemic erupting. Being listed on a last-mile-delivery service platform and reaching a much broader customer base beyond the neighbors became a must-have for survival.

Digital commerce efficiently requires the digitalization of many customer-facing operations and sourcing and procurement. For businesses of all sizes, the digital transformation of supply chain planning became the most important initiative.

Considering this surge in digital transformation and the changing needs of 2021, here are some insights and tips for embarking on Supply Chain Digital Transformation projects.

Digital Transformation Journey

The goal of digital transformation in supply chain planning functions is to create a Digital Twin that is the digital replica of the supply chain. It includes all of its elements: customers, sales channels, products, warehouses, logistics network, and the interactions between them.

Digital transformation for supply chain planning consisting of three levels: Digital, Intelligent and Autonomous. This is a framework for defining the scope and phasing of the initiatives. Now let us dig into the dimensions of this digitalization journey.

Going Digital: Creation of the Digital Foundation

Supply chain planning involves interaction with different types of information based on internal and external data sources. These data sources are often spread across multiple platforms and come in various formats. Planners spend their precious time collecting and synthesizing the data to drive insights.

Here are the steps to take for going digital:

The First Step: Bring all the data together and ensure analytics and planning can happen on the same platform.

As a priority, bringing as much of the data for making the right daily decisions has a significant impact on agility and speed. This includes internal and external data sources. You can start with daily/operational decisions and work your way to tactical and strategic decisions to evaluate opportunities for integrating the data sources into your planning and analytics platform.

Keep in mind that you don’t have to wait to build a data-lake to consolidate all of the data. Planning platforms can pull data from multiple internal and external data sources. You need to accept that data will NEVER be 100% clean and consistent or maintained promptly. Ensure that, somewhere along the way, data diagnostic tools will be used to check for missing and inconsistent data automatically.

Second Step: Ensure data quality and consistency as they are the essential factors in driving automation. If your planning platform has inaccurate data and you don’t have visibility on the data’s quality, you will need to keep the outputs. Instead, the goal should be to focus on maintaining the inputs to ensure you are getting realistic insights and recommendations.

Most typical data related challenges to be addressed when going digital:

Inaccurate and incomplete product and location hierarchy and attribute data
Maintaining all past and future promotional events in a database
Accurate and timely reconciliation of purchase orders with receipts
Having accurate stock-out data
Having up-to-date supplier lead times
Maintaining business and commercial rules in a systematic manner
Maintaining outlier events that have influenced demand patterns or supply availability

One goal of these steps should be to provide end-to-end visibility across the organization through interactive dashboards and a single version of the truth. In doing this, you will uncover many data consistency and quality issues and lay the foundation for bringing in the intelligence layer.

Third step: Explore how you can expand supply chain visibility to your suppliers and logistics providers, and retail channel partners so you can start getting signals of unusual events that will impact your plans.

Fourth Step: Benchmark KPIs to understand limitations and discover opportunities. Creating dashboards in this step will also enable you to benchmark your KPIs before proceeding with the following steps on your journey and help you measure the before & after results.

Some helpful KPIs to benchmark at the beginning of your journey are:

Product Availability – being able to view the availability of different product segments to see products that matter most for your business
Service Levels by location/channel/customer and product hierarchy – being able to view these with the contribution to sales
On-time-in-full performance of suppliers and scorecards where multiple KPIs are combined
On-time-in-full performance of distribution centers
Customer Satisfaction scores side by side with the service level and availability metrics

In the process of benchmarking these KPIs, you will discover and have opportunities to assess the capabilities and the limitations of the existing systems and the processes, identify the data issues, improve the quality of your data and be in a better position to drive intelligent insights.

Fifth step: Internal & external digital collaboration is also a part of going digital. These capabilities can bring efficiencies to decision-making across the supply chain. The cross-functional and cross-enterprise collaboration will become easy when all stakeholders are looking at the same version of the truth.

Creating Intelligence

Once you have the core data and assess the quality and reliability, you can start adding the intelligence layer. Intelligence can come in many shapes and forms:

Diagnostic Alerts: will help you focus on the areas which need immediate attention or improvement, such as products or locations where you are experiencing availability problems.
Predictive alerts: will help you prevent potential issues such as stock-out risks
Analytical insights: will help you gain several insights such as the impact of price changes, the influence of weather, and other demand-drivers.

AI/ML technology will help with many aspects of your supply chain planning both on the demand and supply side.

Examples of building intelligence in your processes:

Automating product segmentation based on multiple dimensions including revenue, demand variability, supplier lead-times to manage different service level targets
Understanding the impact of the market price index on your demand
Analyzing the root cause of stock outs
Modeling the impact of weather events
Automatic identifying and removing outlier events from the historical data
Modeling impact of promotions and campaigns
Estimating revenue impact of lost sales when stock-outs occur
Uncovering halo and cannibalization effects across your product portfolio
Understanding the impact of external trends on your sales performance
Attribute-based forecasting when introducing new products
Having dynamic safety-stock calculations

During the COVID-19 pandemic, one important capability was enabling scenario-planning capabilities. Quick scenario planning has become one of the most sought-after capabilities in supply chain planning. Predictive analytics feeding scenario planning definitely gives a competitive edge when reacting to changes in the business environment. Once you have your process(es) modeled with real-life scenarios, parameters, and constraints, you have a digital twin that will save a lot of time and support fast-decision-making.

Scenario planning can happen at different levels in the organization. Your planning platform should support integrating operational, tactical, and strategic decisions to make daily operational decisions in line with the tactical and strategic targets and parameters.

Having an intelligence layer providing actionable insights will enable faster decision-making and agility during uncertain times.

Going Autonomous

Just like autonomous cars are now a reality, so is autonomous supply chain planning for most daily operational decisions. Replenishing stores to meet availability targets or adjusting prices to keep a certain competitive position in the market are just some examples. While the goal can be to automate many of the planning decisions, keep in mind that there will always be tactical and strategic decisions that will not be automated but can still benefit from digital transformation.

Many decisions made on a daily/weekly basis, such as inventory target setting, store replenishment, procurement planning, markdown optimization, dynamic pricing, order fulfillment, transportation planning, are candidates for autonomous planning. Of course, autonomous planning does not happen overnight, and it is not just about having the technology. Autonomous planning can happen in steps as the organization advances its digital maturity. When embarking on an autonomous planning project, it is essential to clearly define what you plan to achieve with supply chain planning automation.

Consider the following as different levels of complexity you can achieve:

Covering existing orders and prevent supply shortages
Having a volume-based operational plan using sales forecast and constrained supply capability
Optimizing supply and demand matching across the end-to-end supply chain
Making demand-driven, profitable supply response to anticipated demand across the extended supply chain (e.g., key customers and/or suppliers)
Strategically aligning value network plan supporting growth, identifying new demand channels, and speed to market.

Regardless of the complexity of the autonomous planning capabilities, there will always be a need to monitor the system and quickly identify exceptions that need to be addressed and manage overrides when needed. Therefore autonomous planning should not be treated as just a black box running your operations. Data diagnostics to ensure the inputs are accurate, KPI monitoring and alerts for intervention and root-cause analysis are essential components to guide the planners.

Keep in mind that while big data and advanced technology can drive autonomous planning, there are still organizational change management aspects that need to be planned and executed. Measuring user adoption is a good idea to quickly diagnose and address the various issues that get in the way of fully autonomous planning.

If you would like to learn more about becoming your partner in this journey, go ahead and book a meeting with me!

Also, follow us on LinkedIn and YouTube for more information and read our customer case studies on the digital transformation of supply chain planning.

Asena Yosun Denizeri is the Head of Retail solutions at Solvoyo and has over 20 years of experience in implementing Planning, Pricing, and Optimization solutions in global companies in the U.S. and Europe. She has led cross-functional teams in large-scale digital transformation projects touching Category Planning, Assortment Localization, Demand Planning, Promotion Planning, Allocation and Replenishment, Price Optimization, and S&OP.

Following her consulting tenure with Silicon-valley based software companies, she brought her Advanced Analytics and Business Process Engineering experience to Apparel Retail where she worked at Gap Inc. and Cache, where she led Merchandise Planning and Distribution teams to advance analytical capabilities in Forecasting, Assortment Planning and Price Optimization to improve sales and profitability.

Yosun holds B.S. and Master of Engineering degrees in Operations Research and Industrial Engineering from Cornell University. She is one of the contributing authors in the Oxford Handbook of Price Management and has been a guest lecturer in San Francisco State and Columbia University business school on multiple occasions.

Using AI & ML in Retail Supply Chain Planning

Business Intelligence | By Asena Denizeri • 09/24/2020

Companies like Amazon, Walmart, Alibaba, and Zara are leading the path in the use of technology and advanced analytics in managing supply chains. Artificial Intelligence (AI) and Machine Learning (ML) are of the hot topics being discussed in the retail world. Across the globe, whether they are grocery, mass merchant, or fashion, retailers are looking for ways to make faster and smarter decisions using this technology. Among the leading applications of AI & ML in planning are forecasting and replenishment processes.

Getting Closer to the Customer

This is now part of everyday conversation, and those who are pushing the envelope on that front know it takes more than just getting customer insights reports out of CRM systems.

In order to turn those insights into actions; delight the customers and ultimately make an impact on the bottom line, companies need smarter and more agile supply chain capabilities.

For retailers, customer-centric inventory management is the key to maximizing sales potential. To do that, they need smarter and more agile forecasting and replenishment systems that can address fluctuations and variances in customer preferences at more and more granular levels. For brick and mortar stores, this means getting down to the location level, for e-commerce, this means getting down customer segment and even to the individual customer level.

Agile Forecasting & Replenishment

When asked about the top organizational inhibitors preventing retailers from innovating, 60% of the RSR research respondents called out legacy technologies as the main challenge. No wonder, retailers determined to rise to the competitive challenges are constantly looking for ways to improve their technological capabilities.

According to CBInsights research, funding to supply chain & logistics tech continued to rise. So what of the new technologies makes it worthwhile to spend time and effort to upgrade from legacy systems?

AI & ML for Retailers

AI and Machine-learning are quickly becoming differentiating capabilities for Demand Planning and Replenishment solutions.

As retailers explore these types of capabilities, they need to keep their focus on the business impacts. Ultimately, these need to serve their business goals and priorities:

Keep up with customer demands and delight customers
Improve service levels
Reduce inventory and/or logistics costs
Improve the speed in decision making and fuel innovation

Asena Yosun Denizeri is the Head of Retail Solutions at Solvoyo. Asena has more than 20 years of experience in implementing Planning, Pricing, and Optimization solutions in global companies in the U.S. and Europe. She has led cross-functional teams in large-scale implementation projects touching different aspects of Retail Management, including Product Lifecycle Management, Category Planning, Assortment Localization, Demand Planning, Size Optimization, Promotion Planning, Allocation & Replenishment, Markdown Optimization, and Supply Chain Management. Following her tenure with Silicon-valley based software companies, she brought her Advanced Analytics and Business Process Engineering experience to Apparel Retail where she worked at Gap Inc. and Cache. She led Merchandise Planning and Distribution teams to adopt new capabilities in Forecasting, Assortment Localization, and Price Optimization to improve sales and profitability.

Editor’s Choice: 5 Ingredients for Predicting Accurate Shipment ETAs

Business Intelligence | By Chris Cunnane • 07/30/2020

Note: Today’s post is part of our “Editor’s Choice” series where we highlight recent posts published by our sponsors that provide supply chain insights and advice. This article comes from Vivek Vaid, CTO at FourKites, and examines how to predict accurate shipments ETAs.

Predictive intelligence is a big deal these days. In talking to one of our customers, it occurred to me that despite the advances FourKites has demonstrated in machine learning and data science, the concept is still a black box to many of our stakeholders. We thought we would take this opportunity to start unpacking some of that and communicating how we are able to do the things we do.

Let’s start with the basic question: What exactly is predictive intelligence? And how does that differ from traditional business intelligence?

AI is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals who have a cognitive ability to get better through experience. What this means in the world of FourKites’ real-time supply chain visibility is to learn that mechanical breakdowns or busy rest areas will result in longer transit times. This may seem obvious, but when you are looking across 100 countries, the number of these learnings quickly outgrows what a human can keep track of, e.g. idiosyncrasies of hours of service (HOS) regulations, commercial traffic hours, warehouse congestion, individual driver, route or carrier learnings, and the list goes on.

In the landscape of data science applications, predictive analytics is a special class of algorithms that tell you what will happen vs. other techniques that may focus on explaining why something that happened in the past occurred.

Predictive analytics at FourKites is primarily about solving customer issues in anticipation of a problem. For instance, a basic use case might be that unusual traffic causes a change in the ETA (estimated time of arrival) which could cause a shipment to miss its anticipated delivery window. You might be thinking, “That’s not data science!” – and you would be right if the mechanism for doing this work was simply rule-based.

To read the full article and learnt the top five ways to predict accurate shipment ETAs, click HERE.

This Week in Logistics News (June 6 – 12)

logistics news | By Chris Cunnane • 06/12/2020

Artificial intelligence has been applied to just about every supply chain application imaginable, including transportation management and execution, demand planning, supply chain planning, warehouse management, and order management. It has also been embedded in autonomous trucks, robots, and drones for navigation. There are myriad applications outside of the supply chain world as well, but I saw a new one this week: writing a Metallica song. Metallica is one of my favorite bands, so this application intrigued me. Last month, satirist Funk Turkey created an AC/DC song using AI; and he is at it again. To create the song, he used lyrics.rip to scrape the Genius Lyrics Database and made a Markov Chain write Metallica lyrics. He then wrote the music, recorded, and mixed it in his house. The end result was the song “Deliverance Rides.” While it may not be the best song in the world, it is an impressive use of AI for musical sake. And now on to this week’s logistics news.

Historically, the packaged food industry has relied on just-in-time inventory practices to minimize storage costs. However, there has been a drastic shift in the market. Now, these companies are spending cash to stock up on ingredients as fears of more supply chain disruptions grow. The coronavirus turned the supply chain upside down as key ingredients saw shortages, resulting in less production and products on supermarket shelves. Companies like Campbell’s and Bobo’s are stocking up on products like oats and sugar to ensure they can maintain production in the event of more supply chain disruptions. By buying 50 percent more ingredients, these companies have a 90-day safety stock of ingredients for core products. Additionally, supplies may be diverted from items that are not selling as well to better selling products. This is all part of the industry’s contingency plan in case the country sees another spike in coronavirus cases, either when economies re-open or cooler weather hits at the end of the summer.

On July 1 many US shippers will see an increase in cross-border shipping rates. This is due to the fact that countries can begin to self-declare postal rates as part of a deal reached by the Universal Postal Union (UPU) back in September. Cross-border postage rates represent the combination of three services: domestic service by the postal carriers in the country of origin; foreign postal service that takes over the parcel or mail after it crosses the border into the destination country; and handling costs of the service provider. These new shipping rates will be highly variable, but initial estimates see USPS inbound rates from China increasing 100 percent and shipping costs to Canada increasing about 50 percent. Among the companies that have received new contracts with the USPS are DHL eCommerce, FedEx Cross Border, Pitney Bowes, Stamps.com, and UPS Mail Innovations.

The Federal Motor Carrier Safety Administration (FMCSA) has extended its national emergency exemption for hours of service (HOS) to July 14. However, not included in that exemption are grocery restocking, fuel, and precursor raw materials. The extension was passed because a presidential national emergency remains in place. The new extension applies to only three categories of items that are deemed essential: livestock and livestock feed; medical supplies and equipment related to the testing, diagnosis; and treatment of COVID-19; and supplies and equipment necessary for community safety, sanitation, and prevention of community transmission of COVID-19 such as masks, gloves, hand sanitizer, soap and disinfectants. The FMCSA has decided that other items that were previously included are no longer needed for emergency relief, such as food, paper products and other groceries; fuel; precursor raw materials; and liquefied gas to be used in refrigeration or cooling systems.

DPWorld, a Dubai-based logistics company that specializes in cargo logistics, port terminal operations, maritime services and free trade zones, will equip the Jebel Ali Port with a fleet of Autonomous Internal Terminal Vehicles (AITVs) as part of a contract with DGWorld. Autonomous vehicle, robotics and AI specialist DGWorld will deliver and integrate their autonomous technology at the existing ITV fleet in multiple phases, with the goal to further increase the overall efficiency of the terminal and reduce the overall size of the currently used fleet, at the same time. The goal is to create more efficiencies within port operations, and previous trials of the technology have shown that this is an increasingly economical form of automation at ports.

As online grocery shopping continues to grow during the coronavirus pandemic, Instacart is reaping the rewards. The company has surged past Walmart in online grocery market share, and now accounts for more than 50 percent of the market. This is mainly due to the fact that it partners with many different retailers, from local to national chains. And the company has just added a new partner: Home Goods. This also puts Instacart into a new space with the home goods selection, putting it in direct competition with Amazon (I’m guessing Instacart can’t help but smiling at that fact considering their relationship disintegrated quickly after the Whole Foods acquisition). In addition to all of Big Lots’ grocery and pantry staples, customers shopping via Instacart will be able to select from a variety of Big Lots aisles, including home goods, kitchen and dining, beauty, pet, personal care, office and craft supplies, toys and more. While Instacart previously offered select home items from a number of different retail partners, Big Lots has one of the largest selections on the platform.

We have written a lot about food waste here in the past. One company that has made it its mission to combat food waste is Imperfect Foods, which is a subscription-based food service company specializing in “ugly” foods. Ugly foods are generally produce that have imperfections or come from a surplus crop that end up going to waste. With the coronavirus pandemic in full swing, and online grocery ordering soaring, the company has seen order volumes double. According to the company, it is on track to save more than 200 million pounds of food going to waste in 2020.

The latest Global Port Tracker report released by the National Retail Federation (NRF) and Hackett Associates shows that the impact of the COVID-19 pandemic on retail imports may not be as bad as previously expected. US import numbers have fluctuated wildly over the past few months due to capacity constraints amid the coronavirus pandemic. As a result, forecasts for the months ahead have been adjusted once more, reflecting the assumption that shipments to ports will remain below 2019 levels, but not as low as the previous models indicated. According to NRF Vice President for Supply Chain and Customs Policy Jonathan Gold, “the numbers we’re seeing are still below last year but are better than what we expected a month ago. It may still be too soon to say, but we’ll take that as a sign that the situation could be slowly starting to improve. Consumers want to get back to shopping, and as more people get back to work, retailers want to be sure their shelves are stocked.”

And finally, even as the economy continues to open, many consumers may not feel comfortable going out to a bar for a drink. Patrón has you covered as it has launched a cocktail pantry on Amazon. For the at-home mixologists, Patrón Pantry allows consumers to choose from three cocktail recipes created by mixologist from a Patrón Perfectionists cocktail competition: London-based Giulia Cuccurullo, Vancouver resident Jared Schmidt, and Allan Suárez from Mexico City. Shoppers can select their cocktail of choice and have the ingredients delivered to their door to shake up and enjoy at home.

That’s all for this week. Enjoy the weekend and the song of the week, Metallica’s Fade to Black.

A complete analysis of logistics trends, technologies, and services