Supply chain disruptions have secured a permanent spot on business calendars in recent years. From Covid-19 and the Russia-Ukraine war to extreme weather and labor shortages, there is uncertainty at every corner, costing businesses annually. When the pandemic hit, manufacturers were struggling to meet the demand due to shortages of inventory. While supply issues were resolved, these companies are now grappling with excess inventories. A recent McKinsey study shows sectors like consumer-packaged goods (CPGs) have 15%–20% inventory levels above pre-pandemic levels, signaling challenges for demand even today.
Caught in this imbalance at both demand and supply levels, major organizations are looking to turn their supply chain agile. With the average cost of disruptions touching 10% of annual revenues, along with reputational damage, according to Economist Impact, supply chains that were earlier designed to prioritize cost reduction and operational efficiency, now need to ensure security and risk mitigation.
To overcome disruptions effectively, organizations must first assess their ability to respond. That’s why we’ve developed a robust framework designed to measure and enhance a company’s capacity to tackle these challenges head-on.
New Mix of Challenges
Before we get to the framework to ease roadblocks, being aware of the full extent of problems on the horizon is essential. Global supply chains are facing increasing disruptions, with a 30% surge in the Geopolitical Risk with Trade Index being recorded in the past four years and the near tripling of the Global Supply Chain Pressure Index.
Among the emerging challenges, changes in tariffs and regulatory requirements stand out. The unpredictable nature of global trade policies has led to rising costs and operational hurdles, forcing companies to adapt quickly. Beyond the issues with trade routes, the constraints on critical materials, compounded by growing cyber threats, and energy transition challenges, further complicate the situation. Meanwhile, currency volatility and financial risk also impact supply chain contracts and financial stability. These challenges demand forward-thinking solutions that blend technology, strategy, and resilience to sustain operations in an increasingly uncertain world. So where should you begin when calibrating your approach to handle disruptions?
Starting Point
Gartner defines agile supply chain as “the ability to sense and respond to unanticipated changes in demand or supply, quickly and reliably, without sacrificing cost or quality.” One of the keywords in the definition is: Respond. The ability to handle disruptions without additional cost or reduced quality yet maintain high customer satisfaction. To become resilient in the face of disruptions, organizations must focus on two critical capabilities powered by AI/ML:
- Knowing Future Demand: Accuracy in demand prediction comes with incorporating external drivers, such as economic shifts, consumer behavior, and geopolitical events, which can suppress the consumption, for instance, of non-essential goods. Organizations have been forecasting their demand for long, but the traditional methods are falling short. Businesses that account for such factors can better align their production and inventory strategies, ensuring they neither overstock nor underprepared.
For example, LatentView collaborated with a leading food & beverage manufacturer to develop an AI/ML-based demand sensing and disaggregation exercise. The objective was to classify and analyze the demand forecast at the store x SKU level x daily level, enabling the client to optimize store replenishment processes and manage changes in demand patterns more effectively. This initiative resulted in a 14% improvement in forecast accuracy, enhancing overall operational efficiency. - Managing Risks in the Supply Chain: A resilient supply chain requires a clear view of potential risks, from supplier reliability to geopolitical uncertainties. Though most organizations have suppliers across the globe, they are not able to sense the risk and manage the supply can lead to shortages.
If companies are prepared for unexpected situations, they can minimize losses and maintain service levels. A leading automotive OEM was able to reduce potential losses by $80 million annually from supply chain disruptions by implementing LatentView’s multi-tier supplier risk visibility solution that maps the company’s supplier network beyond tier-1 using automated AI-based supply chain mapping. Additionally, it provided insights into risk exposure across more than 50 risk areas through a risk modeling approach using a graph ML-based digital twin of the network.
Building resilient and agile supply chains is a complex task and AI/ML can effectively change the drift. With real-time insights and predictive capabilities, companies can make smarter, faster decisions. Our framework lays the foundation to harness these technologies effectively and transform supply chain challenges into strategic advantages.
Measuring Supply Chain Agility with LVA framework
As discussed earlier, the ability to respond to both supply and demand uncertainties enable the organization to be more agile. Achieving resilience requires more than preparedness, it requires a continuous, systematic approach to measure and improve agility using a structured framework. Here’s how to calculate where you stand:
1. Demand Forecasting
To respond to uncertainties, we have come up with a list of external factors deemed necessary to sense demand earlier and having them in the forecasting models will help organizations in their planning process. This includes economic indicators, weather data, social media trends, and competitor activities.
The Demand Sensing Capability Index helps businesses assess their ability to sense demand changes, with a rating system from 0 (low) to 5 (high) based on the depth of their forecasting methods.
| Demand Forecasting and Sensing | Self-rating (0-5) | Weights | Weighted Rating |
| Economic Indicators | |||
| Weather Data | |||
| Social media | |||
| Google Trends | |||
| Competitor Details | |||
| Demand Sensing Capability Index |
2. Supply Chain Estimation
Similarly, to understand the risk involved in the supply chain it is important to account for external factors such as geopolitical factors, supplier credit ratings, and port congestion, to help organizations plan their supplier accordingly. The Supplier Risk Prediction Index assesses a company’s preparedness to manage risks, using the same 0-5 rating scale.
| Supplier Risk Prediction | Self-rating (0-5) | Weights | Weighted Rating |
| Geopolitics factors | |||
| Economic Indicators | |||
| Port Congestion Details | |||
| Weather Data | |||
| Supplier Credit Rating Index | |||
| News Feeds | |||
| Commodity Price Index | |||
| Supplier Risk Prediction Index |
3. Supplier Spread
It is also important to know how diversified the supplier base is to ensure that the organization can leverage its supplier base to maintain the flow of goods. This can be done for two types of products namely the critical and bottleneck categories.
For each of the factors mentioned above in both the Demand Sensing and Supplier Risk Index, weights can be assigned based on the business realities of the personas using this framework to measure their agility.
Supplier Diversification Index (max score 4)
| Product Category | Score |
| Critical | 2 (if all categories have more than 2 suppliers in more than 2 countries)1 (multiple suppliers in same country)0 (single supplier) |
| Bottle Neck | 2 (if all categories have more than 2 suppliers in more than 2 countries)1 (multiple suppliers in same country)0 (single supplier) |
| Supplier Diversification Index | Sum of (Average score for all Critical and Average score for all Bottle Neck products) |
4. Measuring Resiliency Metrics
The next step in assessing the supply chain agility is to measure the resiliency metrics of the company, mainly the Supplier Fill Rate and Customer Service level. This shows how the organization performs in managing its demand and supply.
- Supplier Fill Rate Index – Average supplier fill rate in last 3 months (90% means 9)
- Service Level Rate – Average customer service levels in the last 3 months
Convert the score in each of the buckets to a common denominator (10) and 60% weightage is given to FCI+SRPI and 40% weightage to the other 3. The overall score combining these factors (demand sensing, risk prediction, and diversification) determines the resilience of the supply chain, enabling businesses to adapt quickly and maintain service levels.
Sample scoring
| Demand Forecasting and Sensing | Self-rating | Weights | Weighted Rating |
| Economic Indicators | 5 | 50% | 2.5 |
| Weather Data | 3 | 10% | 0.3 |
| Social media | 0 | 30% | 0 |
| Google Trends | 1 | 5% | 0.05 |
| Competitor Details | 1 | 5% | 0.05 |
| Demand Sensing Capability Index | 2.9 |
| Supplier Risk Prediction | Self-rating | Weights | Weighted Rating |
| Geopolitics factors | 5 | 20% | 1 |
| Economic Indicators | 4 | 30% | 1.2 |
| Port Congestion Details | 5 | 10% | 0.5 |
| Weather Data | 1 | 10% | 0.1 |
| Supplier Credit Rating Index | 1 | 5% | 0.05 |
| News Feeds | 0 | 10% | 0 |
| Commodity Price Index | 2 | 15% | 0.3 |
| Supplier Risk Prediction Index | 3.15 |
| Product Category | Average Score |
| Critical | 1 |
| Bottle Neck | 2 |
| Supplier Diversification Index | 3 |
| Supplier Fill Rate Index | 9.5 (95%) |
| Service Level Rate | 8 (80%) |
Overall Supply Chain resilience score at a common denominator of 10
Demand Sensing Capability Index + Supplier Risk Prediction Index: 2.9+3.15 = 6.05
Supplier Diversification Index + Fill Rate + Service Level Rate: ((3+9.5+8)/24)*10 = 8.5
60% weightage to planning (6.05*0.6) + 40% weightage to execution (8.5*0.4) = 7.03
A number closer to 10 indicates high resilience and closer to 0 indicates low resilience. In the above example, the organization is very good in terms of execution, which is ability to source from multiple suppliers, receiving products on time, and capacity to ship to the customers on time.
However, they are decent in terms of planning as their Demand Sensing and Supplier Risk indices are not very high and this allows them to deep dive into the parameters that need attention based on their business priorities. For instance, social media listening is one of the keys to understanding changing consumer trends and requirements and if the organization scores 0 in that then they may not be able to gauge the market requirements.
Once companies identify the key areas where they need to improve using this framework, AI/ML can turn the insights gathered from the framework into actionable strategies, enabling organizations to make smarter, faster decisions.
Being Agile To Cut Losses
With McKinsey predicting supply chain disruptions lasting one month or more every 3.7 years, it is vital for organizations to understand where they stand and their ability to fulfill customer needs if a disruption happens today. Where is the risk? This is a question that companies need to be acutely aware of and take proactive measures to zero in on the gaps.
Measuring agility allows businesses to identify areas requiring investment — whether in technology, supplier diversification, or contingency planning — and align their strategies with the growing demand for resilient, adaptable supply chains. As industries shift toward more localized sourcing and heightened risk mitigation using AI/ML, those who proactively assess, measure and follow a structured approach to improve their agility will not only weather disruptions better, but also strengthen their competitive edge. A resilient supply chain is no longer just a defensive measure but a core element of sustained customer trust, and in turn revenue.
