Supply Chain
Article | August 17, 2023
Efficient demand forecasting techniques transform supply chain management, help optimize inventory levels, streamline operations, improve customer satisfaction, and achieve a competitive edge.
Contents
1. How Accurate Demand Forecasting Impacts Business Operations and Profitability?
2. Navigating the Pitfalls of Traditional Demand Forecasting
2.1 Limitations of Manual Forecasting Methods
2.2 Inaccuracy and Inconsistency in Demand Prediction
2.3 Multiple Products and Markets Challenges
2.4 Influence of External Factors on Demand Forecasting
3. Advanced Demand Forecasting Techniques for Supply Chain Management
3.1 Statistical Forecasting
3.2 Collaborative Demand Planning
3.3 Demand Sensing and Real-time Data Analytics
3.4 Agile Supply Chain Management Practices
4 Summing up
1. How Accurate Demand Forecasting Impacts Business Operations and Profitability?
Accurate demand forecasting plays a vital role in determining the operations and profitability of a business. By anticipating future demand, companies can more effectively plan their production, inventory management, and supply chain activities to meet customer needs while minimizing costs.
Additionally, accurate demand forecasting can aid businesses in enhancing customer satisfaction by proactively meeting customer needs and expectations, improving customer experiences and increasing customer loyalty. To generate actionable insights that drive informed decision-making, businesses must leverage advanced analytics and predictive modeling techniques that combine data from various sources with industry-specific knowledge and expertise.
“Businesses that leverage advanced analytics and predictive modeling techniques for demand forecasting report an average of 5% improvement in their supply chain efficiency.”
(Source: A survey by Deloitte)
Supply chain businesses frequently rely on sales data from the past, which may not be sufficient in the complex and rapidly changing business environment. Businesses might not observe an improvement in operations and profitability if they rely solely on conventional methods.
2. Navigating the Pitfalls of Traditional Demand Forecasting
As businesses strive to optimize their supply chain operations and meet customer demand, traditional demand forecasting methods can often hinder their efforts. In this context, it is essential to navigate the pitfalls of such techniques to achieve success in supply chain management.
2.1 Limitations of Manual Forecasting Methods
Manual forecasting methods have limitations that can affect demand forecasting accuracy in supply chain management. Frequently based on historical data, these methods can overlook emerging trends in supply chain management and alterations in customer behavior. In addition, manual processes are time-consuming, prone to error, and incapable of incorporating real-time supply chain data. As a result, businesses struggle to optimize supply chain operations and meet customer demand.
In addition, traditional forecasting methods can influence the ability to accurately predict demand, resulting in overstocked inventory, delivery delays, and, ultimately, poor customer satisfaction. Inaccurate demand forecasts can also result in poor purchasing decisions and increased carrying costs, negatively impacting profitability.
2.2 Inaccuracy and Inconsistency in Demand Prediction
Inaccuracy and inconsistency in demand forecasting pose significant obstacles in managing the supply chain. This is the case in the dynamic business environment, where market conditions can change rapidly, making it challenging for companies to keep up with shifting demand patterns. As traditional demand forecasting methods depend heavily on historical data, they produce inaccurate forecasts that do not reflect real-time market changes.
In addition, inconsistency in demand forecasting can also result in a mismatch between supply and demand, leading to missed opportunities or excess inventory. As a result, creating an effect on company’s bottom line in addition to customer satisfaction.
2.3 Multiple Products and Markets Challenges
Accurate demand forecasting is crucial to the success of supply chain management. When there are multiple products and markets to manage, it becomes a challenge for traditional demand forecasting. Different products and markets may have varying demand patterns and drivers, making it difficult for businesses to accurately forecast demand.
Manual processes and siloed data can hinder visibility and the ability to identify cross-product or cross-market trends, making supply chain optimization operations and meeting customer demand more complex. Managing multiple products and markets is one of the challenges of traditional demand forecasting when businesses operate in various markets with varying customer preferences and demand patterns for products.
2.4 Influence of External Factors on Demand Forecasting
External factors can significantly impact the demand forecasting accuracy for supply chain optimization. These factors are often unpredictable, and conventional methods may not account for them. The external factors affecting the supply chain include natural disasters, economic recessions, and sudden changes in consumer behavior.
In addition, political and regulatory modifications, such as tariffs or trade agreements, can affect the supply and demand of particular products. Therefore, businesses must incorporate these external factors into their demand forecasting models and advance the process, as traditional demand forecasting methods cannot predict accurate future demand patterns and ensure optimal supply chain operations.
3. Advanced Demand Forecasting Techniques for Supply Chain Management
To avoid the above-mentioned pitfalls, companies need to adopt advanced demand forecasting techniques that enable capturing and analyzing huge data from various sources to generate accurate and real-time demand forecasts.
3.1 Statistical Forecasting
Statistical forecasting is an advanced method for demand forecasting in supply chain management that utilizes complex algorithms and statistical models to analyze historical data, identify trends, and generate forecasts. This method employs numerous statistical techniques, including regression analysis, time-series analysis, and exponential smoothing, among others.
Statistical forecasting can help businesses overcome some of the limitations of traditional manual forecasting methods because it is more objective, data-driven, and capable of identifying trends and patterns which are not apparent with manual forecasting methods. As a result, by utilizing statistical forecasting, businesses can increase demand forecasting accuracy, optimize inventory management, and better align supply and demand, resulting in enhanced customer satisfaction, greater efficiency, and lower costs.
3.2 Collaborative Demand Planning
Collaborative Demand Planning combines intensive forecasting algorithms to predict future demand and a set of ML techniques to achieve better demand forecasting. It involves collaboration between suppliers, customers, and other stakeholders. The advanced data and insights sharing technique improve the comprehensive understanding of demand drivers and trends, leading to more accurate demand forecasting. The collaborative approach enables real-time adjustments to demand forecasts, which can help businesses respond promptly to market conditions and customer demand changes.
In addition, using advanced analytics and machine learning algorithms can help identify patterns and trends that would otherwise go unnoticed. That enables businesses to optimize inventory levels, reduce under and overstocking, and enhance customer service levels. In the dynamic business environment, it helps transform the supply chain that is better equipped to meet the ever-changing demands of customers.
3.3 Demand Sensing and Real-time Data Analytics
Demand Sensing and Real-time Data Analytics are advanced demand forecasting techniques that can assist businesses in overcoming the challenges that multiple products and markets pose to the supply chain. By utilizing real-time data from various sources, such as social media, point-of-sale systems, and weather reports, businesses can better understand customer demand patterns, adjust inventory and production planning, reduce delay, and increase responsiveness.
In addition to implementing demand sensing, businesses can begin with sell-in data obtained from supply chain planning or an ERP system in supply chain management and then incorporate all relevant data sources and external factors to broaden the forecasting horizon.
3.4 Agile Supply Chain Management Practices
Agile supply chain management practices are a collection of methodologies and strategies emphasizing supply chain operations' adaptability, responsiveness, and flexibility. These practices involve utilizing real-time data analytics, collaborative planning, and other advanced technologies to enable businesses to respond swiftly to changes in customer demand, market conditions, and other external factors.
Adopting an agile model allows the organization to act swiftly and decisively and achieve successful business outcomes despite adverse conditions. Agile supply chain management practices can give companies greater visibility and control over their supply chains, enabling them to adapt more effectively and efficiently to fluctuating market conditions in the context of external factors influencing demand forecasting. By cultivating a culture of continuous improvement, innovation, and customer value, agile supply chain management practices have the potential to transform into modern supply chain.
4. Summing up
Demand forecasting accuracy is crucial for supply chain management and profitability. Manual forecasting methods hinder operational optimization and customer demand fulfillment. Customer satisfaction, purchasing decisions, and carrying costs suffer from inaccurate forecasting. In order to avoid these pitfalls, businesses can leverage statistical forecasting and collaborative demand. These methods recognize trends and patterns, optimize inventory levels, reduce over- and under-stocking, and improve customer service using advanced analytics and machine learning algorithms.
As the supply chain evolves and becomes more complex, businesses must adopt advanced demand forecasting techniques. Implementing these techniques will enable businesses to optimize their supply chain management by better-aligning supply and demand, resulting in increased productivity, decreased costs, and ultimately increased profits.
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Management
Article | June 21, 2023
A sector which has been heavily disrupted in the last years is the mobility sector. Following decades of "car being king", we have reached a saturation and mentality shift. People want to be more healthy and more ecological (sustainable) and also avoid losing precious time in traffic jams. As a result a whole eco-system of companies has been created to find solutions for this.
This article tries to provide an overview of the trends in this market, with a focus on the Belgian market.
First of all when looking at mobility and the offers on the market it is important to make a distinction between private and professional displacements. This last category can additionally be split up between the daily commute and professional displacements during working hours.
When looking at private mobility (the so-called B2C market), the car remains an important pilar. Especially for families with (young) children it remains difficult to do everything without a car. Obviously, there is a trend to be more sustainable, which is reflected in more sales of hybrid and electric vehicles, more usage of (e)bikes and (e)steps and an increasing usage of shared mobility options (like shared bikes, steps or cars).
Statistics from China, which is already the furthest in the post-Covid era, show that most mobility options have lost terrain (compared to pre-Covid), with the exception of the car and bike. The car, although still not very sustainable, is still the most flexible and has the least chance for contamination. Especially the flexibility will become more important as office hours also become more flexible. Additionally due to the increased home working, in some cities traffic jams have considerably reduced, making room again for more people to switch back from public transport to their car.
Additionally there is the bike. This is a very flexible, individual, healthy and sustainable mode of transportation that many have discovered during the crisis. Furthermore with ebikes becoming more and more common, bigger distances can be covered without needing to be in excellent physical shape.
The professional mobility (i.e. B2B(2C) market) is however even more in evolution, as governments provide all kinds of fiscal incentives to change the mobility habits of employees and employers. Furthermore employers want to offer more flexibility (in working hours, in working location and in mobility options) and less administrative burden to their employees, allow them to profit from those fiscal incentives (resulting in an increased buying power) and become more sustainable.
As a result a variety of new offers to be more flexible and optimally profit of those extra-legal advantages has come to the market. This makes it very complex for an employer to find his way in this tangle.
Obviously, every company is unique, with multiple axes determining which mobility options are possible and best suited for the company:
The location of the company, i.e. Is the company situated in a city with a lot of mobility difficulties (traffic jams)? Is the company situated near public transport options? Is the company situated in a city where a lot of shared mobility options are available? Are the employees typically living close or far away from the company? Which kind of parking facilities does the company have? Does the company have multiple offices geographically spread over the country?
The type of work done at the company, i.e. Does the work require physical presence at a specific location (i.e. time- and location-dependent work)? Is remote work possible? Does the work require a lot of displacements to customers (and/or partners, suppliers…) during working hours?
The type of employees working at the firm, i.e. Are the employees typically living close or far away from the company? What is the age distribution of the employees within the company (e.g. lot of young people, lot of employees with children…)? How strong is the war for talent for the desired employees, forcing the employer to offer a lot of extra advantages to attract people?
The size of the company, i.e. a bigger company has the means to setup more complex mobility plans/options, as they often have dedicated people within HR specialized in these setups.
This makes it difficult to define a "one-solution-that-fits-all" approach, but rather a more tailored approach is required, with some degree of customization per customer.
Some examples:
Promoting commuting by bike via bike leasing and a bike allowance is mainly interesting for companies with employees not living too far away from the company and not requiring doing customer or other professional displacements during working hours. Additionally it depends on the profile of the employees and the safety of the trajectory between the home of the employees and the office. Note that 54% of Belgian employees does not want to use a bike to come to work, with the main reason people finding it too dangerous. At the other hand a similar percentage of employees indicates they would be very interested in options like bike leasing and bike allowances.
Shared mobility options are of course only interesting in the bigger cities, where those options are also strongly available. As a result incorporating those options in a mobility plan does not make much sense when the employer is situated in a location where those options are (almost) not available.
The same applies for "multi-modal transportation" (and the associated multi-modal route planners), which are also only interesting in the larger cities where multiple mobility options are readily available. Furthermore a company introducing this multi-modal mobility concept should be able to put a whole change management trajectory in place, as it requires discovering new mobility options and changing existing commute habits (for most employees the commute is a routine activity, which they do in "auto-pilot")
Setting up a Cafeteria plan or Mobility budget can be quite complex, making the costs and effort, especially for smaller firms, not always outweigh the benefits. New digital solutions can provide a (partial) solution to this, but they typically do not take away the uncertainties for employers to deal with something they do not fully understand.
Electric cars are still difficult for people doing large distances on a regular basis, due to their limited action radius and the too low number of charging stations (especially in the South of Belgium). On the other hand for companies where employees come to the office the whole day and that have the required space to setup charging stations, this can be a very interesting option both fiscally and ecologically.
Collective organized transport is typically only economically viable for large companies, for which a large number of employees are coming from the same region. Platforms exist to manage this cross-employers, but this raises a number of other concerns and reduces the added-value.
Options like "no-mobility" (i.e. home working) and "less-mobility" (flex-offices / co-working places) depend on the work culture and the type of work to be done. For some companies the shift to homeworking during the Covid-confinements was already a serious stretch, which will take years to get fully absorbed. Introducing new concepts like "flex-offices" (co-working places) is probably a bridge too far, especially as there is still a lot of unclarity of who will be paying (and what the fiscal implications are) for the office space (employee paying out of his mobility budget or employer paying) and even more for the added-services like drinks, snacks, catering…
…
In general employers have a big interest to do something around mobility, but when having to deal with all complexity (fiscal and operational concerns like policies, load administration…), many employers drop out. Employers fear especially all exceptions, as they often represent hidden costs and lot of extra effort. E.g. what happens if an employee leaves the company? What if someone is fired? What about the liability in case of accidents/theft/vandalism? What will be the exact total cost for me as an employer? How do I need to manage VAT? What is the exact value of benefit of all kind for the employee? Which proofs do I need to collect for the tax authorities? Does it fit with the agreements made in the collective labor agreement of the joint committee?…
These questions mainly originate from the existing unclarities in the fiscal regime, which is due to the fact that many HR managers are not yet acquainted with these new offers, the fact that new mobility offers are created continuously (making it impossible for the government to stay up-to-date) and the continuous change in regulation (e.g. "Mobility Budget", "Company Car Legislation"…).
This lack of maturity in the industry puts a break on the adoption and this maturation might take years to unfold. E.g. meal vouchers took 40 years to arrive to a market penetration of 50%, while this is a much simpler HR product than most mobility options. Until this maturity level is reached, resulting in more well-known, better integrated, more frictionless and cheaper offers, the traditional company mobility options of reimbursing public transport subscriptions and salary cars will remain mostly used. Those are still most widely known by HR managers, are fiscally still very interesting and fit well the needs and desires of most employees.
This last argument is important, as no mobility option will become mainstream unless employees are happy with it. This means the mobility option should not only give a solution for "Professional displacements" but also for the "Private displacements" (in evenings, weekend, holidays…), often with the whole family.
Nonetheless we see the market is maturing and transforming, as millions of euros of VC money are invested in promising new start-ups. Almost all of those start-ups are not profitable yet but given the market potential a few of them could grow out to become unicorns. Today’s students are more acquainted and open for these new mobility services, so likely some of them will become mainstream in the next decade.
Today a whole eco-system of young start-ups and existing incumbent players are offering mobility services, like
Car leasing companies: Alphabet, ALD Automotive, ING Lease, KBC Autolease, LeasePlan, ARVAL…
Car rental companies: Sixt, Avis, Dockx, Hertz, Rent a car…
Car sharing companies (in the form of cars that can be easily used for individual trips up to platforms facilitating sharing your private car or co-driving): Cambio, Poppy, Partago, Zipcar, Cozywheels, Getaround, Dégage, Share Now, Stapp.in, Tapazz, BlaBlaCar, Klaxit, TooGethr, Carpool (Mpact)…
Taxi services: Uber, Wave-a-Cab, Taxi.eu, Heetch, Bolt, Free Now, Allocab…
Bike leasing companies: Ctec, O2O, Joulebikes, KBC-Fietsleasing, B2Bike, Cyclis, Lease-a-bike, Cyclobility, Cycle Valley…
(e)bike, (e)step and scooter sharing & renting: Lime, Dott, Bird, Felyx, Scooty, Villo!, Billy Bike, Mobit, Blue Bike, Swapfiets, Spinlister…
Fuel card and Electric charging card issuing companies: Network Fuel Card, Modalizy, Fleetpass, Belgian Fuel Card (BFC), XXImo, EDI (Electric by D’Ieteren), New Motion, Plugsurfing, Blue Corner, Luminus, EVBOX, Cenergy, Eneco, Dats24, EV-Point,…
Parking companies (either companies providing public parkings or platforms to share individual and company parkings): Yellowbrick, Indigo, QPark, BeMobile, BePark, Pasha, ParkOffice…
Companies helping to define mobility plan and manage setup of policies and mobility plans/budgets: Social Secretariats (SD Worx, Partena, Securex, Acerta, Liantis…), Payflip, Mbrella, MaestroMobile (Espaces-Mobilités)…
MaaS (Mobility as a Service) players: Modalizy, Skipr, Optimile, Olympus, Be-Mobile, MyMove, Vaigo (Eurides), Moveasy…
(Inter-modal) Route planners: Google Maps, Coyote, Waze, Mappy, Jeasy, Skipr, Stoomlink…
Co-working place companies (either companies providing co-working places or platforms allowing to reserve spaces over multiple co-working places): Bar d’Office, Workero, Cowallonia, Burogest, Regus, Welkin, Meraki, Frame 21, Fosbury & Sons, Start it, Coffice, Spaces, House of Innovation, Ampla House, WeWork, Betacowork, Startbloc, SilverSquare…
Expense management solutions for local and international (mobility) expenses: Rydoo, XXImo, MobileXpense, N2F, Certify, SAP Concur, Travel Perk, Trippeo, SpenDesk, Splendid, Declaree, SRXP, Dicom, WebExpenses, Notilus, Expensify, ExpensePath, Abacus, ExpensePoint…
It will be interesting to see which of those companies will still be around in 10 years (i.e. which of the start-up have sufficient funding to bridge the long-time gap to profitability) and to which form they have evolved. Clearly regular pivoting will be required as this market is in full evolution.
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Article | July 29, 2021
Risk management has been a problem for as long as supply chains have existed. Because of the interdependence of all its connections, even a minor issue in one isolated region has the potential to jeopardize a whole global supply chain. As a result, when major global trends and events occur, the potential for widespread supply chain disruption is enormous.
Global supply chain risks and market disruptions have reached an all-time high. The most notable of them is the COVID-19 pandemic. In a 2020 survey, the Institute for Supply Management discovered that 95% of companies faced operational issues due to the pandemic. As a result, business executives all around the globe believe that if they want to be more resilient and competitive in the present market, they need to modernize and make significant changes to their supply chain strategy.
Other recent factors that have had a significant impact on traditional supply chain practices include the fast pace of change in consumer behaviors and a pretty unstable trade and political environment.
In the last ten years, e-commerce spending has tripled, and internet shopping had increased by 149% in 2020 compared to the previous year. With the growth of e-commerce, there has been a rise in customer demand for faster delivery and more personalized shopping experiences. The Amazon Effect refers to the growing expectation for same-day delivery and its effect on businesses and logistical networks. To be resilient enough to react to these rising demands, supply chain managers have had to make fast and significant modifications to their logistics and warehousing networks, as well as discover new ways to collaborate with third-party fulfillment partners.
Even before the impact of COVID-19, American businesses were attempting to reduce their dependence on foreign manufacturers and suppliers. Foreign tariffs and trade policies had become more unpredictable by 2019, and businesses were seeking technological solutions to make the supply chains more self-sufficient and resilient. As a result, integrating digital transformation and Industry 4.0 technology into supply chain operations is quickly becoming a top concern for global business leaders.
How does Supply Chain Resilience Work?
A flexible contingency plan and the ability to react swiftly to operational disruptions are important characteristics of effective supply chain management. However, to be truly resilient, a supply chain must be able to predict and anticipate disruptions and, in many cases, avoid them entirely.
Strategic supply chain planning is an important step in achieving resilience because it synchronizes all supply chain components and increases visibility and agility. Supply and demand needs are better understood, and production is synchronized due to supply chain planning. This integrated, forward-thinking approach assists businesses in better anticipating problems, reducing the impact of supply chain disruptions, and improving overall operations.
When a business has the digital systems to analyze and make sense of Big Data, it significantly improves supply chain resilience. Artificial intelligence-enabled systems can curate disparate data sets from across the business and the globe. To discover trends and opportunities, news, competitor activity, sales reports, and even customer feedback can be examined together. The system's connected devices are constantly monitored, providing real-time insights about where and how processes can be automated and improved. For instance, AI, machine learning, and modern databases acquire and handle Big Data and analyze and learn from it in an almost infinite number of ways. This enables intelligent automation across the network and provides supply chain managers with the real-time insights they require to respond quickly to disruption and unexpected events.
Supply chain managers have traditionally sought to limit the number of partners and suppliers in their network to minimize operational and logistical complexity. This approach is based on the stability of the social, environmental, and political systems. Unexpected disruptions in one region can slow or even stop network operations across the board. Supply chain resilience technologies, such as blockchain, sensors, and advanced analytics, enable supply chain managers to monitor complex partnerships and supplier contracts even in the most remote parts of their network.
Profitability in the supply chain has always been dependent on minimizing excess and keeping inventories as lean as possible. Capacity and inventory buffers are expensive, and supply chain managers have often bet against disruptions to keep prices low. When the pandemic struck, many businesses discovered the real cost of the gamble. Supply chain operations can involve on-demand manufacturing, virtual inventories, and predictive demand forecasting using digital supply chain technologies to remain resilient, even in times of unexpected disruption.
Benefits of a Resilient Supply Chain
Finding a successful balance between supply and demand is a significant issue for any supply chain manager in an increasingly competitive market. Many businesses that have cut costs on diversification, supply chain technology, and other resilience measures have lately discovered the true cost of those choices. However, when businesses engage in diversification, supply chain technologies, and other resilience measures, they can achieve a variety of business benefits, including:
More efficient operations: Better resilience often results in less risk and a greater capacity to invest in innovation and growth. For example, according to a 2020 global business analysis conducted by Bain and Company, businesses that prioritized their investment in supply chain resilience had up to 60% quicker product development cycles and were able to increase production capacity by up to 25%.
Enhanced productivity: Resilient supply chain solutions lead to the overall system increased productivity. According to a McKinsey 2020 survey, supply chain leaders from across the world report increased productivity due to resilient supply chain systems, and 93% of those surveyed plan to prioritize resilient supply chain strategies for investment in the next year.
Risk reduction: Supply chain activities are often the most vulnerable to risk and loss in many businesses. Supply chains, by nature, are geographically distributed and functionally complex. As a result, supply chains are particularly vulnerable to risk. Resilient supply chain technologies minimize risk by providing insight into all network operations and enabling companies to improve and adjust their processes and logistics in real-time.
Technologies for an Agile Supply Chain
Digital transformation and modern supply chain technology provide businesses with the resilience and competitive advantage they need to react swiftly to disruptions and opportunities.
Artificial intelligence (AI): AI-powered supply chain systems can offer deep procedural and operational insights by gathering and analyzing data from many sources. Predictive analytics and Big Data analysis can assist in predicting risk and demand and recommending measures and reactions in the company.
Machine learning: Machine learning enables the discovery of patterns in supply chain data and the identification of these influential factors - all while constantly learning. This enables supply chain managers to react fast with the finest workflows and operational strategies available.
Industrial Internet of Things (IIoT): The IIoT network in a supply chain comprises connected devices and objects with sensors and unique IDs that allow them to transmit and receive digital data. They collect information and communicate with the central system. AI can analyze and understand this data to enable quick decisions and intelligent automation of supply chain operations and procedures.
Additive (3D) printing: Smart factories can quickly reprogram 3D printers to produce specific products on-demand without disrupting regular business operations in the long run. The accessibility of potential virtual inventories enables supply chains to defend themselves against disruption.
Robots and autonomous things: Robots and drones, which are intelligently automated for speed, efficiency, and accuracy, can adapt their operations on the go to meet quickly changing requirements. They also reduce the risk of harm by eliminating overly repetitive or dangerous tasks from human workers.
Modern databases: The resilient supply chain solutions rely on Big Data, advanced analytics, and real-time insights from modern databases. Supply chain technology can be improved to operate faster and most resilient when equipped with a modern ERP system and an in-memory database.
Resilience means more than just surviving a disruption in operations. A fully resilient supply chain and businesses survive hardship and use it to innovate and improve their business. Building a resilient supply chain is very important in this modern era because disruptions like a pandemic, wars, climate change, etc., are occurring a lot these days. A resilient supply chain helps businesses to survive and thrive even during tough times. To read more about ways to boost supply chain performance, click here.
FAQ
What is supply chain resilience?
Supply chain resilience refers to the supply chain's capacity to be prepared for unexpected risk events, react and recover swiftly to potential disruptions, and grow by shifting to a new, more desirable state in order to improve customer service, market share, and financial performance.
How is supply chain resilience measured?
A supply chain's resilience index is calculated by aggregating its company's resilience index. Given that supply chain company's performance influences overall supply chain performance, supply chain resilience should be measured using the companies' resilience index.
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