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How AI Can Help Overcome the “Great Supply Chain Disruption”



How AI Can Help Overcome the "Great Supply Chain Disruption"

As the mayhem at ports persists with no end in sight, a troubling realization is sinking in: This chaos will not subside with time alone, and the impacts of the “Great Supply Chain Disruption” are being felt across the country. For example, about 30% of baby formula brands could be sold out soon, causing retailers to ration how many containers customers can buy and leaving parents worried that they won’t have enough food to feed their babies. This issue spans industries, impacting automotive, healthcare, hospitality, IT, manufacturing, apparel, and more.

So, what’s the problem? Infrastructure and a lack of truck drivers are often blamed. U.S. trucking companies experienced a record deficit of 80,000 drivers in 2021. It’s a logical explanation because truck drivers move a considerable portion of American freight. However, it’s not the only cause of the supply chain issues.

Reasons for Supply Chain Challenges

Current inventory and planning systems operate on fixed lead times and demand forecasting, while the real world operates on dynamic lead times. As a result, poor decision-making and bad planning by procurement leaders and financial executives are driving the port congestion. To correct this, leaders must forgo planning initiatives and actively manage their shipments.

Every time a transportation medium is changed when shipping goods, there are long queues due to changeover, further aggravating the problem.

Although it might seem logical to think new means of transportation can help alleviate the congestion, this isn’t a practical solution.

Choke points can’t grow without a significant investment, so the port constraints are fixed from an infrastructure perspective. For retailers to change how they plan and prioritize shipments, however, they’ll need help.

How to Plan Shipments More Accurately

Retailers need real-time inventory visibility across their enterprises to plan more accurately. Ideally, stowage plan information can be shared with terminal and third-party logistics companies exiting the gate as one value chain. This helps improve the efficiency of the first-in, first-out process.

AI can help determine changes in transportation or routes early enough to ensure on-time delivery for critical items.

Although AI implementation is still new to supply chain management, early adopters see success. According to McKinsey & Co., enterprises that utilized AI-enabled supply chain management improved logistics costs by 15% and inventory levels by 35%. As AI technology continues to improve, more companies are interested in benefiting from its capabilities. As a result, Infoholic Research predicts that AI in the logistics and supply chain markets will grow at a compound annual growth rate of 42.9% until 2023.

Use Cases for AI to Overcome Supply Chains Disruption

As AI adoption increases, there’s hope that it can help ease supply chain issues. Here are a few critical use cases

1. Predict on-time, in-full rate drops.

Customers are used to receiving purchased goods in a matter of days. However, World Economic Forum data shows that delivery times across the U.S. and Europe will hit record highs toward the end of 2021. Moreover, the current environment indicates that those increased time frames will likely continue.

Even amid unforeseen circumstances such as natural disasters and poor weather conditions, buyers expect that the companies they purchase from will have backup plans to ensure timely deliveries.

AI can help companies predict on-time, in-full drops early using historical data to identify how vendors fulfill orders. This allows companies to set deadlines to switch modes of transportation for customers who generate the most significant profit margins. Furthermore, AI provides full visibility of materials across the entire value chain, making it easy to identify and eliminate bottlenecks quickly2. Deprioritize high-cost, poor-fit customers.

Not all business relationships are a great fit. Gartner predicts that 75% of companies will drop poor-fit customers by 2025.

Although some companies might not be ready to break up with costly clients, these loss leaders shouldn’t take up space at the top of their priority lists.

However, it can be challenging for businesses to identify these customers. With the help of sorting algorithms, AI can automatically identify customers at scale who are bad for market-share gains and drain precious capacity. Additionally, AI can identify new opportunities for improvement and uncover how these opportunities will impact the bottom line.

3. Increase profit margins.

Without a clear understanding of consumer demand, companies risk pushing products that don’t sell, costing businesses millions of dollars.

AI-powered forecasting can help companies sense demand changes early, allowing them to optimize products for the best profit margins.

According to McKinsey, AI-enhanced supply chain management provides a 65% reduction in lost sales caused by out-of-stock products. On the sales side, AI can help sales teams identify upsell and cross-sell opportunities for key accounts. Often, companies have limited knowledge of whom they should be upselling. However, because most sales tasks happen digitally, sales teams constantly collect data. AI can leverage this information to help teams sell more efficiently.

4. Ship faster

In a survey by Convey, 28.6% of respondents said they are more likely to place an order with companies that can deliver products within a week of purchase. That’s a pretty small window of time, so faster shipping is critical if companies want to encourage consumers to shop with them.

AI can identify shippers who slow down the supply chain. Once identified, companies can remove the players who aren’t keeping the pace and replace them with someone more efficient. Furthermore, suppliers can use AI to create simulations based on bottlenecks and disruptions.

Once the AI knows that a specific portion of the supply chain is bottlenecked, it can anticipate when companies can expect a shortage based on inventory stock levels or extending lead times.

It will take more than time to move past the “Great Supply Chain Disruption.” If businesses truly want to deliver products efficiently, they’ll need to change how they plan. By implementing AI technology, companies will be better equipped with the information necessary to ease today’s supply chain challenges.

Ali Hasan R. is the co-founder and CEO of ThroughPut Inc.the artificial intelligence supply chain pioneer that enables companies with predictive replenishment for complex supply chains.

Image Credit: thisisengineering; Unsplash; Thank you!

Ali Hasan R.

Co-founder and CEO of ThroughPut Inc.

Ali Hasan R. is the co-founder and CEO of ThroughPut Inc., an artificial intelligence supply chain pioneer that enables companies to detect, prioritize, and alleviate dynamic operational bottlenecks.


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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