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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.

 

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

EU Launches Estimated €400M Blockchain, AI Fund to Avoid Lagging US, China

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A new fund has been set up with the aim of preventing the EU falling behind nations like the U.S. and China on blockchain and artificial intelligence (AI) innovation.

The European Investment Fund (EIF) and the European Commission have together put up €100 million (over $110 million) for a dedicated investment scheme that will make capital available to AI and blockchain projects via VC funds or other investors, EIF, an EU agency set up to indirectly fund SMEs, said in a blog post on Wednesday.

With the “cornerstone” funding in place, the EIF said private investors are expected to bring up to €300 million ($331 million) into the fund, while the total could rise further from next year, with national promotional banks being able to co-invest under the scheme.

Sifted reports that the fund could ultimately raise up to €2 billion ($2.2 billion) under the InvestEU Programme.

According to the post, the EU already spends plenty on blockchain (expected spending for 2019 is $674 million), but that is mostly directed toward research and proof-of-concepts.

The U.S. is the biggest spender, with a $1.1 billion expected spend, and China is second with $319 million, according to cited numbers from the International Data Corporation.

The new fund is aimed to address the fact that not so much is spent in the EU on developing “larger scale projects.

“Investing in a portfolio of innovative AI and blockchain companies will help develop a dynamic EU-wide investors community on AI and blockchain. By involving national promotional banks, we can scale up the volume of investments at a national level,” the EIF said.

Read more at EU Launches Estimated €400M Blockchain, AI Fund to Avoid Lagging US, China

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Gartner: top 8 supply chain technology trends for 2019

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According to Gartner, while many of these supply chain technology trends have not yet been widely adopted, they will have a broad industry impact this year.

Gartner has highlighted the key supply chain technology trends which they warned must not be ignored. Christian Titze, research vice president at Gartner, said: “Within the next five years if half of the large global companies are using some of these technologies in their supply chain operations, it’s safe to say that the technologies will disrupt people, business objectives and IT systems.”

The top 8 supply chain technology trends in 2019 are:

#1 Artificial intelligence (AI)

According to Gartner, AI technology in supply chain operations is all about augmenting workers. Thanks do developments in self-learning and natural language processing, AI is now advanced enough to automate numerous supply chain processes such as predictive maintenance and demand forecasting.

#2 Advanced analytics

Thanks to the increase in IoT data and extended external data sources such as weather or traffic conditions, analytics is going to get a lot more advanced. Gartner predicted that organisations will be able to anticipate future scenarios and make better recommendations in areas such as supply chain planning, sourcing and transportation.

#3 IoT

Gartner has reported seeing more supply chain practitioners exploring the potential of IoT. However, according to Gartner, new IoT applications involve more than just passive sensors.

#4 Robotic process automation (RPA)

Excitement has been building around RPA for some time now, and its place in the enterprise has seen a lot of maturing this year. Like AI, RPA, according to Gartner, is about augmenting workers.

#5 Autonomous things

Autonomous things use AI to automate functions previously performed by humans, such as autonomous vehicles and drones. They exploit AI to deliver advanced behaviours that interact more naturally with their surroundings and with people.

#6 Digital supply chain twin

A digital twin is a digital replica of a physical asset, whether that is a product, person, place or system.

#7 Immersive experience

Augmented reality (AR) and virtual reality (VR) technologies have long been touted as the next big thing. For all its promise mass adoption by enterprises have, in reality, always seemed to be on the horizon.

Read more at Gartner: top 8 supply chain technology trends for 2019

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The Impact of Hurricanes on Transportation and How to Build a Storm Resilient Supply Chain

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This report looks at data before and after Hurricane Harvey in August 2017 and dives into the true cost and volume impacts experienced by logistics customers; it also shares advice on how shippers can prepare for another 2018 challenging storm season.

2017 Tropical Storm Harvey

Hurricanes have massive impacts on transportation capacity and spend.

To better understand true cost and volume impacts, Zipline Logistics evaluated a sample of 33,000 shipments, comparing data prior to the 2017 Tropical Storm Harvey with data after the event.

Access the full report and keep reading this post for the advice you can use to prepare your supply chain for the next tumultuous storm season (Note: the Atlantic Hurricane season runs from June 1 through the end of November.)

Hurricane Impacts on Transportation

We leveraged our KanoPI shipper intelligence platform to dig deep into hurricane impacts. Here’s what we found;

Market surcharges due to hurricane activity were the costliest of added fees in 2017 with a total cost of $673,000.91.

Data shows that the Average Cost Per Load after the 8/26 hurricane went up by $159.58, or 11% and that the Average Cost Per Mile increased by 15%.

915 fewer loads moved after the hurricane (date of 8/26/2017) when compared to previous four-month period. This tells us that people were holding on to shipments that would typically have moved into key areas like Florida, Texas, and surrounding states.

Looking specifically at Florida, there was an 8% drop in volume and 3.4% drop in spending. This shows that for shipments still moved, rates were higher.

Read more at The Impact of Hurricanes on Transportation and How to Build a Storm Resilient Supply Chain

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A Case Study on Leveraging Supply Chain Risk Management Solutions to Drive Revenue for a Leading Consumer Packaged Goods Firm

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SpendEdge, a global procurement intelligence advisory firm, has announced the release of their new ‘supply chain risk management study on the consumer packaged goods industry’. A well-known consumer packaged goods company with a considerable number of manufacturing units spread across economies was facing difficulties in identifying the potential opportunities in the market. The CPG sector client wanted to leverage the use of supply chain risk management solutions to achieve a more robust supply chain network. The consumer packaged goods client was also looking at devising an effective risk treatment plan including measures to protect the supply chain.

According to the procurement analysts at SpendEdge, “The CPG industry acts as a foundation for the modern consumer economy as it drives not only huge amounts of money into other businesses like retail and advertising but also generates a massive portion of the gross domestic profits (GDP) for countries across the globe.”

In the consumer packaged goods industry, leading firms are looking at leveraging the use of supply chain risk management solutions, as it helps them integrate several previous or ongoing initiatives, including those for business continuity and supply-chain security. Our supply chain risk management solutions assist clients in the consumer packaged goods market space to align their risk management strategies with supply chain risk exposure.

The supply chain risk management solutions offered by the experts at SpendEdge helped the consumer packaged goods client to monitor the complete process, starting from risk analysis and risk evaluation through risk management and right up to residual risk control. This helped the CPG sector client to achieve productivity and avoid sales losses.

Read more at A Case Study on Leveraging Supply Chain Risk Management Solutions to Drive Revenue for a Leading Consumer Packaged Goods Firm

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Scientist Ng brings AI to manufacturing

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Artificial intelligence pioneer Andrew Ng launched a new AI company Landing.ai on Thursday.

On the same day, the company announced a strategic cooperation with electronics contractor Foxconn to develop a program that aims to bring AI and machine learning technologies to the manufacturing industry.

According to Ng’s statement, his company is developing a series of programs to help enterprises transform for the age of AI, including providing new technologies to optimize companies’ organizations structures, train employees, and more. The company’s businesses will start in the manufacturing industry.

Ng said the AI technology is conductive to manufacturing enterprises to improve quality testing process, shorten products’ design cycle, remove bottleneck of supply chain, reduce waste on materials and energy and raise output.

AI will revitalize manufacturing industry and generate jobs in the industry, he said. I In the age of AI, the employees need to accept new skills training to fit jobs that will be more complex than before, Ng added.

Landing.ai will provide solutions to some employees who are likely to be laid off, Ng said. Currently, the company is discussing the training plan with some potential partners including local governments.

Read more at Scientist Ng brings AI to manufacturing

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Transforming Integrated Planning & Supply Chain Processes with Augmented Intelligence Capabilities

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In conjunction with the announcement, o9 released an eBook titled, “Who Gets the Cheese?”

Aptly named after one of the greatest business books of all time (Who Moved My Cheese?), this resource details one of o9’s systems for optimally allocating resources across initiatives and brands at consumer goods companies.

Founded by executives, practitioners and technologists that have led supply chain innovations for nearly three decades, the o9 team has been quietly developing a game-changing Augmented Intelligence (AI) platform for transforming Integrated Planning and Supply Chain processes.

The team has deployed the AI platform with select clients, including:

  1. Bridgestone Tires
  2. Asian Paints
  3. Restoration Hardware
  4. Party City
  5. Del Monte
  6. Aditya Birla Group
  7. Caterpillar
  8. Ainsworth Pet Foods

Speaking on behalf of o9 Solutions, Co-founder and CEO Chakri Gottemukkala said, “While executives we work with hear the buzz around technologies for data sensing, analytics, high performance computing, artificial intelligence and automation, they are also living the reality of slow and siloed planning and decision making because the enterprise operates primarily on spreadsheets, email and PowerPoint.”

Read more at Transforming Integrated Planning & Supply Chain Processes with Augmented Intelligence Capabilities

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One-Page Data Warehouse Development Steps

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Data warehouse is the basis of Business Intelligence (BI). It not only provides the data storage of your production data but also provides the basis of the business intelligence you need. Almost all of the books today have very elaborated and detailed steps to develop a data warehouse. However, none of them is able to address the steps in a single page. Here, based on my experience in data warehouse and BI, I summarize these steps in a page. These steps give you a clear road map and a very easy plan to follow to develop your data warehouse.

Step 1. De-Normalization. Extract an area of your production data into a “staging” table containing all data you need for future reporting and analytics. This step includes the standard ETL (extraction, transformation, and loading) process.

Step 2. Normalization. Normalize the staging table into “dimension” and “fact” tables. The data in the staging table can be disposed after this step. The resulting “dimension” and “fact” tables would form the basis of the “star” schema in your data warehouse. These data would support your basic reporting and analytics.

Step 3. Aggregation. Aggregate the fact tables into advanced fact tables with statistics and summarized data for advanced reporting and analytics. The data in the basic fact table can then be purged, if they are older than a year.

Read more at One-Page Data Warehouse Development Steps

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Why Supply Chains Need Business Intelligence

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Companies that want to effectively manage their supply chain must invest in business intelligence (BI) software, according to a recent Aberdeen Group survey of supply chain professionals. Survey respondents reported the main issues that drive BI initiatives include increased global operations complexity; lack of visibility into the supply chain; a need to improve top-line revenue; and increased exposure to risk in the supply chain. Fluctuating fuel costs, import/export restrictions and challenges, and thin profit margins are driving the need for businesses to clearly understand all the factors that affect their bottom line.

Business Intelligence essentially means converting the sea of data into knowledge for effective business use. Organizations have huge operational data that can be used for trend analysis and business strategies. To operate more efficiently, increase revenues, and foster collaboration among trading partners companies should implement BI software that illuminates the meaning behind the data.

There is a vast amount of data to collect and track within a supply chain, such as transportation costs, repair costs, key performance indicators on suppliers and carriers, and maintenance trends. Being able to drill down into this information to perform analysis and observe historical trends gives companies the game-changing information they need to transform their business.

Read more at Why Supply Chains Need Business Intelligence

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Artificial Intelligence: The next big thing in Supply Chain Management

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Imagine the endless possibilities of learning from 2.5 quintillion bytes of data generated every day. Artificial intelligence (AI), which began its journey 60 years ago is well on its course to make this implausible scenario a reality. Artificial Intelligence, is slowly taking over our lives.

From personal assistants like Siri in Apple products to stock trading to medical diagnosis, AI is able to learn from seemingly unstructured data, take decisions and perform actions in a way previously unimagined.

Businesses too are undergoing digitization rapidly. They are using AI – capable of performing tasks normally requiring human intelligence – to create a significant impact in the way businesses operate. In an increasingly dynamic environment comprising demanding customers and the need for speed, it was only a matter of time before the businesses embraced AI to obtain much needed agility. According to Accenture’s Technology Vision 2016 survey spanning 11 countries and 12 industries, 70 percent of corporate executives said they are significantly increasing investments in AI.

Artificial Intelligence in Supply Chain

Organizations are increasingly digitizing their supply chains to differentiate and drive revenue growth. According to Accenture’s digital operations survey 85 percent of organizations have adopted/ will adopt digital technologies in their supply chain within 1 year.

The key implication of this change is that the supply chains are generating massive amounts of data. AI is helping organizations analyze this data, gain a better understanding of the variables in the supply chain and helping them anticipate future scenarios. Thus, the use of AI in supply chains is helping businesses innovate rapidly by reducing the time to market and evolve by establishing an agile supply chain capable of foreseeing and dealing with uncertainties.

Read more at Artificial Intelligence: The next big thing in Supply Chain Management

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