Perspectives on Various Issues of Interest

Artificial Intelligence driven Supply Chain Planning Algorithms

AI-driven supply chain planning leverages complex algorithms to enhance efficiency, accuracy, and responsiveness across various supply chain functions. Organizations need to not only follow systematic steps to achieve performance outcomes, but also be cognizant of factors that present challenges in reaping associated benefits. 

The foundation of AI-driven supply chain planning lies in Data Collection and Integration, i.e., gathering vast amounts of data from diverse sources. Internal data sources include sales history, inventory levels, production rates, order fulfillment data etc. On the other hand, external data sources include market trends, supplier performance, economic indicators, weather conditions, social media sentiments etc. Data is integrated into a centralized system, often facilitated by cloud computing, to create a comprehensive dataset for analysis.

The next step involves Data Preprocessing to ensure quality and consistency before feeding the data into AI algorithms. In this stage the data is cleaned by removing duplicates, correcting errors, and handling missing values. Normalizing helps in scaling the data to a consistent range to improve algorithm performance. Categorical data is often transformed into numerical values using techniques such as one-hot encoding.

Feature engineering involves selecting and transforming relevant data features to enhance the predictive power of the model. Key variables that have significant impact on supply chain performance (e.g., lead times, demand patterns) are identified and new features are derived from existing data, such as calculating average lead times or seasonal demand variations.

After these initial steps are undertaken, Model Selection ensues depending on the specific supply chain task. For instance, demand forecasting calls for time series models (e.g., ARIMA, Prophet), regression models (e.g., linear regression, gradient boosting), and deep learning models (e.g., LSTM networks). Reinforcement learning models are used for inventory optimization where these models learn optimal stocking policies through simulations. Optimization algorithms (such as genetic algorithms, ant colony optimization) and neural networks are used for route optimization so that efficient delivery routes can be identified.

Once the models are selected, using historical data the Training phase enables the algorithm to learn patterns and relationships within the data using historical data, adjusting its parameters to minimize prediction errors and the Validation phase helps in evaluating the model's performance on a separate validation dataset to ensure it generalizes well to new data. 

Once trained, the AI models help with Prediction and Optimization of supply chain operations. These could include such areas a demand forecasting (predicting future sales based on historical data and external factors), inventory management (recommending optimal inventory levels to balance holding costs and service levels), production scheduling (allocating resources and scheduling production runs to meet predicted demand efficiently), logistics and distribution (optimizing delivery routes, shipment schedules, and transportation modes to minimize costs and delivery times) and others.

AI algorithms then enable Real-Time Decision-Making by continuously analyzing incoming data and updating predictions and recommendations. With adaptive learning, the models adapt to new data, improving their accuracy over time. Automated adjustments help the system to automatically adjust supply chain parameters (e.g., reorder points, production schedules) based on real-time insights.

The final step in AI-driven supply chain planning involves a feedback loop for Continuous Improvement. Through performance monitoring KPIs (e.g., order fulfillment rates, inventory turnover) are tracked to measure the effectiveness of AI-driven decisions. Periodically model retraining with new data helps in maintaining and enhancing performance. Running "what-if" scenario analysis prepares a firm for potential disruptions and optimizes contingency plans.

Notwithstanding these step-by-step approach for using AI algorithms for supply chain planning and their associated advantages, many firms fail to reap those benefits. These challenges often stem from several key factors. Many companies struggle with the quality and integration of data from disparate sources within their supply chain. Inconsistent or incomplete data can lead to inaccurate predictions and suboptimal decision-making. For instance, if historical data is incomplete or inconsistent, AI algorithms may produce unreliable forecasts, impacting inventory management and demand planning. As an example, a multinational consumer electronics company implemented AI-driven demand forecasting software to optimize inventory management. The software struggled with integrating data from various retail partners, resulting in inconsistent demand forecasts. Due to this shortcoming the company experienced issues with inventory levels, leading to excess stock in some regions and stockouts in others, impacting profitability and customer satisfaction.

Companies face difficulties in implementing and fine-tuning complex AI models. These algorithms require specialized expertise in machine learning and data science to develop and maintain. Without sufficient internal expertise or resources, companies may struggle to effectively deploy AI-driven solutions and optimize them for their specific supply chain needs. Resistance to change within organizations can hinder the successful adoption of AI-driven supply chain planning. Employees may be reluctant to trust AI recommendations over traditional methods or may lack the necessary training to interpret and act upon AI-generated insights. Without buy-in from key stakeholders and adequate change management strategies, companies may fail to leverage AI's full potential. For example, a global pharmaceutical company adopted AI-powered supply chain optimization tools to streamline logistics and reduce costs; however, middle management and operational teams were resistant to AI recommendations, preferring traditional planning methods. Despite the potential for cost savings and efficiency improvements, the company failed to fully realize the benefits of AI, resulting in missed opportunities for operational optimization.

The upfront costs associated with implementing AI-driven supply chain solutions can be substantial. Companies may struggle to justify these investments without clear, measurable returns on investment (ROI). Moreover, accurately estimating the ROI of AI initiatives can be challenging due to factors such as implementation costs, ongoing maintenance, and the complexity of measuring intangible benefits like improved decision-making.

Integrating AI-driven algorithms with existing legacy systems and processes can be complex and time-consuming. Legacy systems may lack the flexibility or compatibility required to seamlessly integrate with AI solutions, leading to operational disruptions and delays in realizing benefits. For example, a leading automotive manufacturer invested in AI algorithms to optimize production scheduling and supplier management. Integration issues arose when attempting to link AI systems with existing ERP platforms and legacy systems. Delays in data synchronization and decision-making processes affected production timelines and supply chain visibility, impacting overall operational efficiency.

In industries with stringent regulatory requirements or ethical considerations, implementing AI-driven supply chain algorithms may raise concerns about data privacy, algorithm transparency, and compliance with regulations. Companies must navigate these challenges to ensure that AI solutions comply with legal and ethical standards while delivering operational benefits. For example, a global food and beverage conglomerate implemented AI algorithms to optimize its supply chain, including procurement, production planning, and distribution. The AI algorithms used by the company to optimize procurement decisions inadvertently favored suppliers with lower costs, sometimes sourced from regions with questionable labor practices or environmental standards. This raised ethical concerns within the company and among stakeholders, including customers and advocacy groups. Additionally, there were regulatory concerns related to compliance with labor laws, environmental regulations, and fair trade practices in different regions. The ethical and regulatory concerns posed reputation risk since negative publicity and stakeholder backlash affected the company's brand reputation and consumer trust. The company faced compliance issues since regulatory authorities scrutinized the AI algorithms and supply chain practices, leading to potential fines or legal repercussions for non-compliance. The company had to reassess its AI algorithms and supply chain policies to ensure alignment with ethical standards and regulatory requirements. This involved revising procurement criteria, enhancing supplier vetting processes, and implementing transparency measures in supply chain operations.

Overall, addressing these challenges requires a holistic approach that includes improving data quality, investing in AI expertise, fostering a culture of innovation and adaptability, managing costs effectively, ensuring regulatory compliance, and aligning AI initiatives with strategic business objectives. Companies that successfully navigate these challenges can harness the full potential of AI-driven supply chain planning to achieve competitive advantages in today's rapidly evolving market landscape.

Supply Chain Planning with Emerging Technologies

Supply chain planning has become increasingly sophisticated with the advent of new technologies. There are several technologies that are being used to improve planning. 

Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of modern supply chain planning. These technologies enable with demand forecasting by predicting future demand with high accuracy by analyzing historical data, market trends, and external factors. Inventory optimization is facilitated where these technologies help with balancing inventory levels to meet demand without overstocking or stockouts. Predictive maintenance is aided where these technologies monitoring equipment health and predicting failures before they occur to minimize downtime.

Big Data and Analytics are helping in supply chain planning by aiding with data integration to aggregate data from multiple sources (sales, market trends, supplier information) and thereby gain comprehensive insights. Real-Time Analysis enables making data-driven decisions on the fly to quickly respond to market changes. Performance Monitoring aids in tracking key performance indicators (KPIs) and identifying areas for improvement.

Internet of Things (IoT) devices collect real-time data from various points in the supply chain, enabling enhanced visibility for real-time tracking of goods and assets throughout the supply chain, condition monitoring of goods in transit (e.g., temperature, humidity) to ensure quality, and asset management for tracking the location and status of equipment and inventory.

Blockchain technology that offers transparency by creating an immutable ledger of all transactions, ensuring transparency and traceability. The technolgoy also enhances security by preventing tampering and fraud, and creation of smart contracts that automates contract execution when certain conditions are met, improving efficiency.

Robotics and Automation are used for warehouse automation where robots are used for sorting, picking, and packing goods, which increases efficiency and reduces labor costs. Automated Guided Vehicles (AGVs) helps in transporting goods within warehouses and production facilities without human intervention.

Cloud-based solutions that provide scalability that enables easily scaling up or down based on demand. It facilitates collaboration enabling seamless collaboration among supply chain partners through shared platforms and enhances cost efficiency reducing the need for on-premises infrastructure and maintenance.

Advanced Planning Systems (APS) that are designed to optimize production schedules to ensure that manufacturing processes align with demand forecasts and for efficient resource allocation to maximize productivity and minimize costs. APS also helps with scenario Analysis running "what-if" scenarios to plan for various contingencies.

3D printing is revolutionizing supply chains by helping with on-demand production, producing parts and products as needed, reducing the need for large inventories; customization, allowing for the customization of products to meet specific customer requirements; and reducing lead times, speeding up the production process by creating parts directly from digital designs.

Digital twin is a virtual replica of a physical supply chain that allows for simulation and optimization, testing different scenarios and optimizing processes before implementing changes in the real world. It also helps with predictive insights where data from digital twins is used to predict outcomes and improve decision-making and with proactive maintenance by simulating equipment wear and tear to plan maintenance activities proactively.

Finally, Augmented Reality (AR) and Virtual Reality (VR) technologies are used for training, providing immersive training experiences for supply chain workers.It helps with maintenance, assisting technicians with virtual overlays of instructions and equipment details. Digital twins helps with visualization of complex supply chain networks and operations.

Some real-world examples of AI-driven supply chain planning:

1. Amazon

Amazon leverages AI to optimize its vast and complex supply chain. The company uses machine learning algorithms to forecast demand, manage inventory, and streamline logistics. AI predicts consumer demand based on historical data, seasonal trends, and market conditions, ensuring that the right products are available in the right quantities. Additionally, Amazon's AI-driven robotics in fulfillment centers automate sorting, packing, and transportation of goods, significantly speeding up order processing and reducing operational costs.

2. Walmart

Walmart employs AI to improve its supply chain efficiency and customer satisfaction. AI-powered analytics help Walmart predict demand, manage inventory levels, and optimize routes for its delivery fleet. For instance, the company uses AI to anticipate stock shortages and automatically reorder products, minimizing out-of-stock situations. Moreover, Walmart's AI-driven supply chain visibility tools track shipments in real time, enabling proactive management of delays and disruptions.

3. Zara

Fashion retailer Zara uses AI to stay ahead in the fast-paced fashion industry. Zara's AI systems analyze real-time sales data and social media trends to predict fashion trends and consumer preferences. This information helps Zara rapidly adjust its inventory and production schedules, ensuring that popular items are available in stores quickly. The company's AI-driven logistics also optimize delivery routes and warehouse operations, reducing lead times and operational costs.

4. Procter & Gamble (P&G)

P&G utilizes AI to enhance its supply chain planning and efficiency. The company's AI-driven supply chain management platform, known as the Control Tower, provides real-time visibility into its global supply chain. AI algorithms analyze data from various sources to predict demand fluctuations, optimize production schedules, and manage inventory levels. This proactive approach helps P&G reduce waste, lower costs, and ensure product availability.

5. Coca-Cola

Coca-Cola employs AI to optimize its supply chain and improve sustainability. The company uses AI to analyze data from sales, weather patterns, and market trends to forecast demand more accurately. This helps Coca-Cola optimize production schedules and reduce excess inventory. Additionally, AI-driven route optimization ensures efficient distribution, minimizing fuel consumption and carbon emissions.

6. Unilever

Unilever's AI initiatives focus on enhancing supply chain resilience and efficiency. The company's AI-driven demand forecasting tools analyze historical sales data, market trends, and external factors to predict consumer demand accurately. Unilever also uses AI to optimize its manufacturing processes and supply chain logistics, ensuring timely delivery of products while reducing operational costs.

7. Siemens

Siemens leverages AI to improve its supply chain and manufacturing operations. AI-driven predictive maintenance tools monitor equipment health and predict potential failures, reducing downtime and maintenance costs. Additionally, Siemens uses AI to optimize inventory management and production schedules, ensuring efficient use of resources and timely delivery of products.

8. DHL

DHL, a global logistics company, uses AI to enhance its supply chain operations. AI-driven analytics help DHL forecast demand, optimize warehouse operations, and improve delivery routes. The company also employs AI-powered robots in its warehouses to automate sorting and packing, increasing efficiency and reducing operational costs.

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These examples highlight how AI is revolutionizing supply chain planning across various industries. By leveraging AI technologies, companies can enhance demand forecasting, optimize inventory management, streamline logistics, and improve overall efficiency. As AI continues to evolve, its impact on supply chain planning will only grow, enabling businesses to achieve greater levels of agility, sustainability, and customer satisfaction.

The integration of these technologies into supply chain planning is transforming how businesses operate, making supply chains more efficient, responsive, and resilient. As these technologies continue to evolve, they will further enhance the capabilities of supply chain management, driving innovation and competitive advantage.

Taming the Counterfeiting Epidemic

In a recently published article, we present the findings of our research that suggests that successfully combating counterfeits requires the attention of a broad collection of organizational functions. It works best with a multilayered strategy encompassing diverse methods and engaging the entire organization and its partners. We recommend that organizations tackle counterfeiting with a cohesive plan for identifying, containing, and preventing it. This comprehensive process means routinely keeping tabs on contract manufacturers and charting how products move through the supply chain. It includes scoping out what is for sale in consumer markets, deploying covert markings, reviewing warranty claims, educating customers, and partnering with key agencies and competitors.

While companies may never completely eliminate bad actors from copying products or diverting goods from authorized channels, they can significantly reduce counterfeiters’ market penetration and restore lost revenue. Successful approaches may involve cutting off counterfeiters’ access to markets, eliminating their supply of unauthorized goods, or making a product more difficult to copy. Building on insights from our case studies and discussions with practitioners, we provide details on the three activities that together help in developing a robust action plan comprises: identification, containment, and prevention. Identification helps in gaining Insight Into the extent and nature of the counterfeiting problem. Containment helps in limiting the problem’s spread. And prevention helps in stopping future counterfeit operations before they start

Source: Taming the Counterfeiting Epidemic - A multilayered approach is essential to effectively combat counterfeiting and unauthorized sales. MIT Sloan Management Review, Forthcoming (Fall 2023).

 

The Impacts of digital technologies on coping with the COVID-19 pandemic in the manufacturing industry

The COVID-19 pandemic’s impacts have been devastating for the global economy, and particularly for manufacturing companies. Many firms were unprepared for a crisis of this magnitude and adapted their operations in an ad-hoc manner. Some of these adaptations were facilitated by digital technologies (DTs). In a recently accepted article, my co-authors and I examine extant literature using a systematic review methodology in order to extend our understanding of what DTs have been used in manufacturing companies during the pandemic, how DTs have helped manufacturing companies cope with the pandemic, and how these innovations can be used in the post-pandemic world. The major outcome of our study is a novel classification of DT applications in the pandemic setting in the manufacturing industry. In addition, we propose an agenda for future research.

Source: Ardolino, M., Bacchetti, A., Dolgui, A., Franchini, G., Ivanov, D., & Nair, A. (2022). The Impacts of digital technologies on coping with the COVID-19 pandemic in the manufacturing industry: a systematic literature review. International Journal of Production Research, 1-24.

Adapting supply chain operations in anticipation of and during the COVID-19 pandemic

In a recently accepted article, my co-authors and I investigate the impacts of the COVID-19 pandemic and their proactive mediation by adaptive operational decisions in different network design structures in anticipation of and during the pandemic. In generalized terms, we contribute to the understanding of the effect of preparedness and recovery decisions in a pandemic setting on supply chain operations and performance. In particular, we examine the impact of inventory pre-positioning in anticipation of a pandemic and the adaptation of production-ordering policy during the pandemic. Our model combines three levels, which is not often seen jointly in operations management literature, i.e., pandemic dynamics, supply chain design, and operational production-inventory control policies.

The analysis is performed for both two- and three-stage supply chains and different scenarios for pandemic dynamics (i.e., uncontrolled propagation or controlled dispersal with lockdowns). Our findings suggest that two-stage supply chains exhibit a higher vulnerability in disruption cases. However, they are exposed to a lower system inertia and show positive effects at the recovery stage. Supply chain adaptation ahead of a pandemic is more advantageous than during the pandemic when specific operational recovery policies are deployed. We show that it is instructive to avoid simultaneous changes in structural network design and operational policies since that can destabilize the production-inventory system and result in higher product shortages. 

Source: Rozhkov, M., Ivanov, D., Blackhurst, J., & Nair, A. (2022). Adapting supply chain operations in anticipation of and during the COVID-19 pandemic. Omega, 110, 102635.

Thermal management technologies - Supply chain and operational issues

In this post, I cover supply chain and operational issues faced by a small and medium enterprise providing thermal management technology for consumer electronics, lithium batteries, and electric vehicles. I will also allude to actions that are being taken to address supply chain issues. I would be interested in hearing your thoughts on the outlook for small and medium enterprises operating in this space in light of prevailing operational and supply chain challenges.

The thermal management technologies market is evolving rapidly, especially in the case of consumer electronics and lithium batteries use. Increasing adoption of renewable energy resources is the major factor driving the thermal energy storage market with the rapid industrialization across the world has increased the need for continuous power supply, which positively leads to the growth of the overall thermal energy market during the forecast period. Developments in the electronics industry have culminated in a considerable surge in the power densities, which have led to the introduction of smaller, smarter products. These advancements in the industry have led to an increased need for innovative thermal management technologies as they improve the system performance and reliability by avoiding the heat generated by the devices. The electronic packaging trend has increased the performance and reduced the size of the product. This has led to a significant increase in the power consumption of the system. A report from Grand View Research said that the global thermal management technologies market size is expected to reach USD 20.14 billion by 2024, according to a new report by Grand View Research, Inc. The industry is primarily driven by the growth in the emerging trend of miniaturization of electronic devices and components.

The Grand View research report said: "Advanced technological research is expected to produce more efficient and cost-effective thermal management solutions in the future. The key industry participants are extensively focusing on the development of optimized thermal management solutions that are cost-effective and are applicable across a range of end-use applications. However, the industry is anticipated to witness various issues associated with modularity in designing and reliability of modeling, which are presumed to challenge the growth over the forecast period. Current cooling technologies, standard heat sinks, and fans are rapidly approaching their cooling capacity limit, and thermal management is becoming a critical step in enabling enhanced product functionality. The thermal management software is anticipated to exhibit a significant growth in the near future owing to the increasing adoption of the software heat removal techniques and simulations to reduce moments of peak heat impact and reduce the risk of failure."

Several companies compete in this sector including Arkema S.A., BorgWarner Inc., Continental AG, Dana Limited, Gentherm Incorporated, Grayson, Hanon Systems, Kendrion N.V., Lord Corporation, MAHLE GmbH, Marelli Corporation, Modine Manufacturing Company, NORMA Group, Orion BMS by Ewert Energy Systems, Inc., Polymer Science, Inc., Renesas Electronics Corporation, Robert Bosch GmbH, Samsung SDI Co. ltd., Tesla, Inc., Valeo S.A., VOSS Holding GmbH + Co. KG. and KULR. Given that many of the competitors are OEMs or diversified corporations, focusing on a small and medium enterprise offers some insights into key supply chain pain-points in this sector. I am focusing on the 2022 Q1 experiences of KULR Technology Group, Inc. (ticker symbol: KULR:US) to identify some of the supply chain and operational issues in this sector.

KULR Technology Group, Inc. (ticker symbol: KULR:US), through its subsidiary, KULR Technology Corporation, develops and commercializes thermal management technologies for batteries, electronics, and other components applications in the United States. It offers lithium-ion battery thermal runaway shields; fiber thermal interface materials; phase change material heatsinks; internal short circuit device; KULR battery cell screening and testing automation system and tech safe case; cellcheck; and CRUX cathodes. The company's technologies are used in electric vehicles, energy storage, battery recycling transportation, cloud computing, and 5G communication devices. It sells its products for applications, such as lithium-ion battery energy storage, electric vehicles, 5G communication, cloud computer infrastructure, consumer, and industrial devices. The company was formerly known as KT High-Tech Marketing Inc. and changed its name to KULR Technology Group, Inc. in August 2018. KULR Technology Group, Inc. was founded in 2013 and is based in San Diego, California.

In 2021 the company increased its revenue by 287% as compared to 2020, mainly reflecting expansion in the commercialization roadmap. Shareholder equity was increased to $16.4 million in the year ending December 31, 2021, from $6.1 million in the year ending December 31, 2020. Gross margins decreased to 54% in the year ending December 31, 2021, from 70% in the year ended December 31, 2020, primarily due to a change in product mix from higher margin products to lower margin services. Selling, General and Administrative (SG&A) Expenses in the fourth quarter of 2021 increased to $3.8 million from $768,000 in the corresponding period in 2020 due to the addition of management and operations team members, sales and marketing activities, and non-cash stock-based compensation paid to employees and consultants. R&D expenses in the fourth quarter of 2021 increased to $705,000 from $68,000 in the same period last year, reflecting a combination of new engineering hires, investments in manufacturing automation, new product developments, and research in high-areal capacity battery electrodes and solid-state electrolyte. Loss from operations was $4.0 million for the fourth quarter of 2021, compared to $677,000 from the same period in 2020. Higher SG&A costs offset higher sales while the gross margin decreased from 76% in the fourth quarter of 2020 to 70% in the comparable 2021 quarter, as a result of lower margins on some larger jobs. Net loss for 2021 increased to $11.9 million or a loss of $0.15 per share, compared to a net loss of $2.9 million, or a loss of $0.03 per share in 2020. The Company reported cash balances of $14.9 million as of December 31, 2021, compared to $8.9 million in the same period in 2020. 

In the first quarter of 2022, KULR's sales reduced by 52%, from $418,000 in 2021, to $200,000 this year. General and admin expenses increased to $3.5 million in the first quarter of 2022, from $1.5 million in the corresponding quarter last year. The increase of 136% was due to additional marketing and advertising expenses, consulting fees, and non-cash stock compensation pay for employees and consultants, and the expansion and kiting out of new office facilities. R&D expenses increased 486%, from $123,000 in the first quarter of 2021, to $721,000 in the first quarter of 2022. The loss from operations increased 141%, from $1.5 million for the first quarter of 2021, to $4.1 million for the first quarter of 2022. The increase in the operating loss included 0.9 million increase in non-cash stock-based compensation expense, and increases in payroll, advertising, and marketing expenses, as well as professional fees and research and development projects. The company's net loss increased by 141%, from $1.7 million in the first quarter of 2021, to 4.2 million in the first quarter this year. The net loss per share for the first quarter of 2022 was four cents, compared to two cents for the comparable period last year. As of March 31st, 2021, the company reported cash balances of $10.1 million, compared to $6.2 million on March 31st, 2022. The company raised over $7 million from the issuance of warrants and promissory notes and have established a $15 million standby equity purchase agreement. 

Over the course of past five years, the company's sales, cost of goods sold and profit margins saw major increases in 2018, followed by two years of decline (2019 and 2020) and then an increase in 2022. Except for 2019, the sales, general and administrative expenses have increased as would be expected for a growing company in a growing sector. Similar trend can be observed in R&D expenses to keep up with new innovations and product development.

The company's earnings before interest, taxes, depreciation and amortization are negative.

Supply chain disruptions and action plan

Based on the information available for 2022 Q1 earnings call, the following supplier chain issues and remedial actions were highlighted.

• supply chain disruptions resulted in over $325,000 worth of inventory that couldn't be shipped due to the COVID lockdown
• COVID lockdown that occurred in Shanghai, China at the end of March, left KULR production on the dock with no option to ship.

To respond to these issues primary following initiatives were taken:

• secured $55 million in additional capital to drive two key initiatives
  • securing battery cell supplies of over 500 megawatt hours in energy capacity from tier one battery manufacturers, who are securing the inventory in anticipation of fast-growing demand from key end markets in energy storage and e-mobility.
  • control supply chain and manufacturing costs and reduce disruptions risk by bringing much of the supply chain and production capabilities to North America
• maintain its margins through improvements in logistic flexibility and response times that can offset potential increase in labor costs.
• create a buffer stock of materials, which the company is in negotiations to have its customers take immediately as a hedge against future potential lockdowns
• continue investment in new and automated test and production equipment first implemented in the Q4 of 2021.
• onboarding new tier one battery manufacturers to obtain battery cell supplies of over 500 megawatt hours in energy capacity.
• multisourcing
• geographical diversification of suppliers
• onshoring production in North America
• creating a buffer stock of materials
• developing modular platforms for new product development
• expand operations and support new business

Information on accounts receivables indicate a growth in the past two years. Finished goods inventories and investments in plant, property and equipment have been growing

Past five year balance-sheet:

The accounts payables saw a decline in 2020 but then increased in 2021, reflecting expanding operations.

For the fiscal year ending 2021, the return on assets were -50.60% and return on equity was -105.95%. Total debt to equity ratio was 5.04, current ratio was 6.41 and book value per share was 0.16.

Below, I present the summary of stock market performance:

 

Strengthening the Personal Protective Equipment Supply Chain

The vulnerabilities of global supply chains were exposed by the COVID-19 pandemic. In this post I first consider the geopolitical landscape and disruptions in PPE supplies by reflecting on the conditions before the pandemic until the time when countries started to take steps toward managing the crisis. Next, I discuss prevailing contextual conditions, future demand and supply trends, and directions for risk management through government interventions, public-private partnerships and organizational best practices.

It is instructive to start from pre-COVID time to understand the distribution of various PPE products and global demand. Before COVID-19, the global PPE market was worth roughly $60 billion. PPE products are destined for numerous different economic sectors such as healthcare, mining and construction. According to an April 2020 analysis by the Asian Development Bank, the healthcare sector PPE market alone was estimated at $2.5 billion in 2018 as shown below where the revenue is in $ millions.

As for 2020, the United States (US) was a major manufacturer, accounting for 20 % of the global production of every category apart from gloves.

Source: Mordor Intelligence (updated in November 2020 ), Statista research department, COVID-19 PPE demand and supply perspectives, Industry experts interviews (November 2020)

Despite being a major PPE producer, the US relied heavily on imports to meet local demand.

Source: ITC Trade Map

The global trade network in 2018 shows high geographic and regional concentration in the PPE supply chain. There are three regional clusters: Asia, Europe, and the US. Among countries making these products, China (PRC) clearly plays a central role in the trade network (except for gloves where countries such as Malaysia, Thailand, Indonesia are dominant due to abundance of rubber).

Source: ADB calculations using data from United Nations. Commodity Trade Database.

In fact, PPE concentration in Asia has intensified in the past decade or so.

Source: Asian Development Bank (2020)

To counter the supply shortage of PPE during pandemic, several nations had instituted export restrictions. The efficacy of these measures could be debated since they also could have resulted in less optimal investments in new capacity (since manufacturers would take the restricted market into consideration when taking capacity decisions), high burden on public finances (since governments had to provide greater fiscal inducement to encourage domestic manufacturers to increase capacity aimed at the restricted market), and loss of cooperation as well as potential retaliation by nations.

Source: International Trade Center website (in November 2020)

Source: Global trade alert                                                                                   Source: : Committee for the Coordination of Statistical Activities (2020)

Considering product shipments from China to US, once China was able to control its own pandemic, supply chains for garments, visors, thermometers, gloves, simple masks and N-95 masks linking China to the US adapted very well. The need for gloves in the US market was served by other countries such as Malaysia, Thailand, and Indonesia, since the plastic gloves from China are relatively less in demand in the US. Technological sophistication of ventilators made in China also were not compatible with the US needs, which reduced the adaptive ability of this supply chain.

Source: Dallas, M. P., Horner, R., & Li, L. (2021). The mutual constraints of states and global value chains during COVID-19:The case of personal protective equipment. World Development, 139, 105324.

There was indeed a component of luck in that the pandemic in China had eased as it spread to the west. Future pandemics may not reflect such a temporal dynamic. Additionally, the phenomenal increase in the exports of simple masks and N-95 masks could have been a result of mislabeling and customhouse chaos during the pandemic.

The PPE supply chain is faced with several bottlenecks as shown in the following illustrative example.

Medical supplies were delayed due to shipping challenges. Demand for shipping and transportation services had increased significantly, but the labor available to provide these services had reduced. The backlogs and congestion produced significantly delays, uncertainty and cost increases.

To respond to the crisis, several countries boosted their domestic production base. In the US, the Defense Production Act was activated to mobilize domestic industrial base. The EU accelerated joint procurement procedure with 26 member states to ensure supply of medical equipment across Europe. Structural funds were directed to the supply of medical equipment. In India, financial incentives were provided for the production of critical supplies. Digital platform was developed to identify and fill the shortage of critical supplies. Japan provided subsidies for the production of face masks. State-owned firms in China were repurposed to supply medical materials. Loans and subsidies were provided to firms producing critical supplies.

In a survey, over half of respondents expected a significant or somewhat decreased presence of supply chain components in China, while 75 percent expected a significant or moderate increase in the United States. Similar expectations emerged for the European Union, the UK, Canada, Australia, and New Zealand, for which half of respondents expect an increase in components.

Source: Atlantic Council

44 percent and 53 percent of respondents cited inadequate planning for both near and long-term disruptions as the top vulnerability in their supply chains, respectively. In addition, over 40 percent of respondents listed geographic or regional concentrations as well as bottlenecks and single point dependencies as core vulnerabilities.

Source: Atlantic Council

Over 60 percent of respondents foresee more prioritization of contingency planning and crisis modelling in response to the pandemic’s disruptions. In addition to planning, they ranked location diversification of their supply chains as a top priority, followed by relocating them within the borders of the primary country of operation.

This focus on re- or onshoring due to the growing concern about foreign dependencies and increasing demand for self-sufficiency resulted in several new manufacturing sites being established for the production of PPE products.

Source: Health Industry Distributors Association

Going forward, PPE spending is forecasted to nearly triple by 2027. Demand for N95 respirators will continue to grow more than 5% per year through 2024. Increased demand and limited manufacturing capacity combined to create a predicted 37% shortfall in nitrile gloves in 2021. Raw material shortage used in making isolation gowns will continue to impact prices.

 

The US PPE market is expected to group 12.5% a year through 2024, with 80% of sales in four highly fragmented product segments.

 

Increased focus on workplace safety, product usage to encourage end-user adoption, growth in industries that are heavy PPE users, and shift to online sales will act as tailwind in this market. On the other hand, competition from private labels and low-cost producers as well as uncertain raw material availability will act as headwinds. Some of the price-sensitive segments will witness disruptions while others will need to differentiate in this market.

Government can play an important in strengthening the PPE supply chain by means of reforms to domestic and international trade rules and agreements. It can take necessary diplomatic, economic, security, trade policy, informational, and other actions. Frequent supply chain review and reforms to make supply chain analyses and actions more effective could help. Government can also help in fostering innovation, developing world-class American manufacturing base and ensuring adequate stockpiles in the future.

Public-private partnership can help with coordinating various aspects within the PPE supply chain. These include establishing policies, incentives, and focused federal procurement guidelines; guiding input, development timelines, and product portfolios; initiating combined exercises and planning efforts; incentivizing emergency essential businesses’ use of federal purchasing vehicles; and enabling vertical and lateral supply chain distribution activities. The partnership can help with managing pricing by assessing and maximizing the value and efficacy of federal investments in latent manufacturing capacity. Increased supply chain visibility and data sharing as well as cost-efficient maintenance of inventories could be part of public-private initiatives. Finally, these partnerships can help maintain a specified level of pandemic preparedness and formalize pandemic preparedness as a condition for participation in federal programs.

Organizations need to recognize that supply chain disruptions are becoming more frequent and severe.

Source: McKinsey Global Institute, 2020

Supply chain pressure is only increasing in recent times as reflected below:

Source: Michigan State University's Supply Chain Pressure Index 

Source: New York Fed's Global Supply Chain Pressure Index

Supply-chain leaders believe that the issues by the pandemic will transform supply chains. 73% of respondents in a McKinsey survey indicated that they encountered problems in supplier footprint, 75% faced issues in production and distribution footprints, 85% struggled with insufficient digital technologies, and 48% experienced delays in planning decisions.

Organizations need to understand the bottlenecks along the PPE value chain due to increasing manufacturing capacity. For respirators, supply pressure arises mainly from shortages of melt-blown non woven, a critical ingredient. Supply pressure in for medical masks also arises mainly from shortages of melt-blown non-woven. And for gloves, supply pressure is driven both by nitrile shortages and limited specialist manufacturing capacity

 

Source: COVID-19 PPE demand and supply perspectives, Industry experts interviews (November 2020)

Consumers and non-healthcare workers will drive surgical mask demand in 2021 before dropping by ~ 40 % p.a. in 2021-25. A significant shift in the weight of global PPE demand will move towards Asia.

Source: Source: Mordor Intelligence (updated in November 2020 ), EPI model, WHO assumptions

According to a McKinsey surveys of global Supply Chain leaders, 93% expect to increase resilience across the supply chain, 90% plan to increase digital supply chain talent across supply chains, and 54% expect changes in supply chain planning after COVID-19. As for measures for resilience, 53% plan to consider dual sourcing, 47% plan to increase inventory of critical supplies, 40% are considering near-shoring and increasing their supply base, and 38% plan to regionalize their supply chains. To improve digital supply chain talent, 70% are planning to resell their supply chain labor force and 55% are considering acquiring new talent from the labor market. For supply chain planning 60% are considering implementing advanced analytics, 58% will consider centralizing supply chain planning, and 50% are going to retail faster sales and operations planning cycle. 11% of the respondents indicated facing budget challenges associated with transforming their supply chains.

Given the importance of resilience among supply chain leaders it is important to consider both resistance and recovery capabilities. Resistance capabilities help avoid and contain disruptions. Recovery capabilities enable stabilization and return to normalcy. Companies need to consider not only risk factors (impact and probability of disruptions), but also uncertainties (known, unknowns and unknown, unknowns) associated with disruptions.

Investment strategies need to be considered to manage disruptions effectively. These investments strategies can be categorized as those related to discovery, information, supply chain design, buffers, operating flexibility, security, and preparedness. Discovery related investment strategies would require investing in the ability to identify potential problems in the supply chain as close to the event occurrence as possible. The types of investments include information technology/information sharing, early warning by supply chain partners, forecasting, demand sensing, monitoring of performance in the supply chain. Investment strategies in information call for improving the quantity, speed, and quality of information flow within the supply chain. These could be facilitated by improved information technology, effective communication, and visibility. Supply chain design investment strategies involve designing and implementing supply chains that can be configured and reconfigured quickly in response to changes within the supply chain. Supply base management and supply base reconfiguration can help in this regard. For buffer related investment strategies organizations need to create excess cushions in the form of inventory, capacity and lead times by considering human resource capacity, human resource capabilities/experience, inventory, operating flexibility, and redundancy. With investments in operating flexibility organizations can create a system that can change either the flow or product specifications in response to supply chain problems. Alternatives for transportation and variable bills of material are examples of such investments. Investment in security can help protect the system from supply chain shocks by creating firewalls, quarantine protocols, and development of strengthened supply chains. Finally, preparedness related investment strategies require designing contingency plans for dealing with potential supply chain shocks and carrying out drills using these plans so that various groups would know what they must do and what their specific responsibilities are. This can be facilitated by investing in planning for contingencies, training/rehearsing, risk assessment and insurance.

Different investment strategies contribute towards different stages of resilience. Avoidance stage is best handled by investment strategies in discovery, information, security and preparedness. Containment can be managed by investments in supply chain design, buffers, operating flexibility, security, and preparedness. Investments in supply chain design, buffers, operating flexibility, and preparedness can also help with stabilization. Finally, the return stage is best managed by investments in operating flexibility and preparedness.

Organizations need to realize that there are several modes of reshoring as shown below. Firms can relocate manufacturing activities performed by wholly-owned offshore facilities to wholly-owned onshore facilities (in-house restoring); can relocate manufacturing activities performed by wholly-owned offshore facilities back to onshore suppliers (restoring for outsourcing); can relocate manufacturing activities performed by offshore suppliers to wholly-owned onshore facilities (reshoring for in-sourcing); and can relocate manufacturing activities performed by offshore suppliers back to onshore suppliers (outsourced reshoring). 

Source: Gray et al. (2013)

To be successful, new entrants will need to achieve scale and secure raw materials and specialist machinery. The will also need to acquire technical expertise and quickly build brand strength.

Source: COVID-19 PPE demand and supply perspectives, Industry experts interviews (Nov. 2020)

Organizations need to consider a range of supply (shift away from sole-source contracts), data aggregation and predictive modeling capabilities, understand the price-points for competitiveness, manage quality of products, have built-in redundancies, invest in innovation & reusables, create transparency in their supply chains, and foster talent. 

Russia-Ukraine Crisis and the Automotive Wiring Harness Supply Chain

Modern vehicle is much more of a digital device than a mechanical one. Whether it is engine control systems, driver assistance systems or media centers, electronic technology is omnipresent. The advancement towards the "connected car" and autonomous driving is only accelerating this trend. In this increasing presence of electronic systems in a car, the wire harness is one of the key backbone that integrates various digital components, links digital components with  mechanical and structural components, and ensures that the onboard electronic systems get the required power supply. It is also critical for enhancing efficiency and ensuring vehicle safety.

In a typical car, the cables forming the wiring harness stretch more than 3 miles in length and Ukraine is a key supplier in the supply chain for this essential backbone. Leoni AG, a global supplier of wiring harness, has sites covering more than 65,000 miles in the Lviv region in Ukraine. The company employs more than 7,000 people in Ukraine and the cable assemblies made in Ukraine are supplied to LEONI plants in Poland, Slovakia, Hungary, Czech Republic, Germany, Spain, Portugal, Italy, Belgium, the UK, the USA and Austria. These plants in turn supply the wiring harnesses to car manufacturers such as Opel, Porsche, Volkswagen, Audi and Lamborghini. 

Fujikuru, a Japanese company that make wiring harness, also has sites in Ukraine and supplies cables to car manufacturers such as Volkswagen, Porsche, Audi, and the Czech Republic’s Skoda. Sumitomo Electric Bordnetze with 60:40 split in terms of shareholding between Sumitomo Electric Industries and Sumitomo Wiring Systems has facility in Ternopil, Ukraine. Nexans, headquartered in France, is another such company with sites in Ukraine. Along with these companies other suppliers such as Germany's Forschner, Kromberg & Schubert, Prettl, SEBN and Japan's Yazaki have built up wire harness production sector in Ukraine. In fact, Ukraine supplies nearly 7% of all imports of wire harnesses in the European Union. These wire harness manufacturing sites are among about 22 automotive companies that have invested more than $600 million in 38 plants and employing over 60,000 Ukrainians.

The western part of Ukraine bordering Poland was a relatively safe haven in the conflict until now. However, today's missile strike in the Lviv region has upended the situation. This morning (18th March) several missiles had struck an aircraft repair plant at the airport complex in Lviv, destroying the buildings. 

While several manufacturers preempted the situation due to rising hostilities and had moved high volume production of parts for vehicles out of the Ukrainian plants to other locations, it wasn't an easy transition. The factory space, machinery, tooling, workers and financing requirements are going to add a fair amount of lead time to be up and running. Automakers will have to find short and medium term solutions. As of this writing, the Volkswagen Group was trying to boost production of wire harnesses in neighboring locations in Europe and North Africa such as Romania, Hungary, Tunisia and Morocco, but also in farther locations such as Mexico and China.

Data: CRU

S&P Global Mobility downgraded its 2022 and 2023 global light vehicle production forecast to to 81.6 million for 2022 and 88.5 million units for 2023. These figures are 2.6 million units lower for both years than previous year. The European forecasts are expected to be 1.7 million units lower with almost 50% of the figure resulting due to part shortages of chips and wire harnesses. The remaining 50% would be due to reduced demand from Russia and Ukraine. European automakers such as Volkswagen, Porsche, BMW, Audi, Mercedes-Benz have suspended production at some of their plants. Since Ukrainian wire harnesses constitute almost 45% of imports in German and Poland, German automakers are particularly going to be affected due to this crisis and the profit margins are going to witness a squeeze. 

This is a reversal of the trend that we were seeing in January and February. According to LMC Automotive, the selling rate in Germany had improved slightly in February to 2.7 mn units/year from 2.6 mn units/year previously. Similar trends were visible in other European markets. However, although LMC anticipates the 2022 annualized selling rate to improve over the course of 2022, it will grow at a slower rate than forecasted last month due to the current conflict. This is due to supply disruption, inflationary pressure and lowering of consumer confidence. 

Source: LMC Automotive 

US auto industry will also not be immune to this supply disruption. According to S&P Global Mobility North America light-duty vehicle production will be reduced by 480,000 units in 2022 and by 549,000 units in 2023. According to the company there will be a shortage of nearly 25 million units of global light-duty vehicle production from its forecast between now and 2030.

Russia-Ukraine crisis and the resulting supply chain disruption - a reflection

Russia's invasion of Ukraine that began a week ago (on 24th February 2022) is setting in motion a set of dire conditions that supply chains are going to face in coming weeks and months. In this post, I reflect on the effect of the crisis on oil prices, energy prices, supplies for product manufacturing, service supplies, food supplies, and metals. 

The Brent Crude Oil Continuous Contract Price opened today at $107.34 and is ranging between $106.83-$113.94 at the time of this writing.

This crisis has taken the oil price above $104 for the first time since 2014. As the third-largest oil producer and second-largest oil exporter, Russia exerts power in the oil supply equation. Low levels of inventories, spare capacities, and stockpiling activities are putting upward pressure on the oil price. Addressing this would require sale from alternative sources such as the U.S. Shale, OPEC or Iran.

In addition to transportation costs due to increasing oil prices, transportation is also being affected due to the effect of the crisis on the estimated times of arrivals and pricing. Trade lines from China to North America are exploring various options to manage this crisis. The quantities transported from China to the EU increased in the first half of last year (at 336,500 TEUs, it was more than 44% higher as compared to 2020 and 99% higher than 2019) and this trend was continuing this year. However, these shipments that were transported by rail will now need to use alternative modes (ocean or even more expensive air). 

This can cause ocean freight rates to go up by two to three times (from $10,000 per container to more $30,000 per container) and the air freight spot rates and lead times to go up three to four times.

With Russia providing about 35% of the supplies of Europe, energy prices have started to witness an upward tick. Russia has already reduced the supply of natural gas and is potentially going to further reduce the exports as a retaliation to sanctions. Compounding this situation is the fact the almost 10% of the liquefied natural gas flows through pipelines from Ukraine to the European Union; these assets are at risk of being damaged due to the invasion. These rising energy prices will increase the operating costs of various entities in the supply chain, including manufacturing firms, distributors and retailers. Without alternative sources of supplies from places such as U.S. and Qatar, the costs of operations can become very high. The situation is also going to test Russia's ability to withstand the financial impact of reduced supplies to Europe.

There is also an expected impact on supply shortage since a large set of organizations (more than 2000 US firms and more than 1000 European firms) receive their supplies from first-tier suppliers that are located in Russia. Additionally, several companies (more than 450 US firms and more than 200 European firms) also have their first-tier suppliers operating out of Ukraine. Companies located in Russia and Ukraine are also prominently suppliers of services, including software and IT services (13%), consumer services (7%), and trading and distribution services (6%). On the product side, 4% of industrial machinery as well supplies such as oil, gas, steel and metal products are supplied from these two countries. Overall, as compared to other countries such as China, the overall trade impact due to tier-1 supplier disruptions may not be very high, but when tier-2 and tier-3 suppliers are added to the mix, the impact can be substantial since close to 200,000 firms in the US and more than 100,000 firms in Europe have upstream suppliers (tier-3) from these two countries.

Russia is the top wheat exporter, Ukraine is the top exported of rye, barley and is the third largest exported of corn. Given these trade situations, food supplies are expected to get disrupted in coming days.

On the metal commodity front, markets for copper, nickel, platinum and aluminum are expected to be squeezed due to the conflict.

Overall, the supply chain disruption caused by this crisis is just unraveling and will manifest fully in coming weeks and months. Organizations should take necessary steps to reduce the potential impact that the conflict might have on their businesses by proactively taking steps for continuity planning.

 

Quality penalties and continuity of health care

In a study my co-authors and I examine whether quality penalties aimed at reducing readmissions improve continuity of health care. We investigate if the quality penalty policy impacts continuity of care for services that were targeted by the policy through what we refer to as primary spillover effects. We also investigate the secondary spillover effects of the quality penalty policy on continuity of care for related ailments that were not targeted by the policy. The findings of this study show that externalities from quality penalties for readmission not only benefit continuity of care for the regulated ailments, but also allow health care organizations to adapt their existing routines and unlock continuity of care improvements for related, but non-targeted ailments. The finding that continuity of care does not diminish for unrelated services assuages concerns that hospitals respond strategically by neglecting or redirecting resources away from unrelated services. We provide novel insights as to how organizations respond to regulation by actively re-configuring their care patterns and coordinating service provision with attendant spillover effects on a variety of patients. Processual mechanisms such as the source of patient admissions and length of stay, and structural mechanisms such as system size and investments in continuity of care facilitate the spillover effects. 

Source: Ananthakrishnan, R., Deore, A., Nair, A. Virtuous Spillover Effects of Quality Penalties on the Continuity of Health Care. Working paper.