By Manish Srivastava (Vice President Supply Chain Analytics & Digital Practice | Genpact), Nikhar Sharma (Asst. Vice President Supply Chain Analytics & Digital Practice | Genpact) and Prasad Havre (Asst. Vice President Supply Chain Analytics Delivery | Genpact)

The expansion of the supply chain has increased global connectivity. But organizations still find it challenging to detect and minimize risk proactively. As a result, unexpected supply-chain disruptions and weaknesses have caused material shortages worldwide. In the manufacturing world, it has been estimated that raw material shortages account for 8% to 10% of overall service losses considering product availability and throughput.

In 2022, significant supply disruptions have impacted global supply chains. The average price of materials has increased due to rising commodity costs led by geopolitical tensions, pandemic and inflationary pressures. It has proved detrimental to producing consumer goods, automotive components etc. The supply chain involves a vast network of resources, technologies, individuals, companies, and interdependent activities where isolated functions and processes influence one another. Organizations are increasingly struggling with cybersecurity challenges especially with suppliers’ global connectivity and compliance. Additionally, due to the growing need for a unified supply chain approach, organizations need more visibility and control over the upstream supply chain which are often external, making it challenging to manage (Exhibit 1).

Exhibit 1: upstream vs downstream supply chain

In real life supply chain interruptions are unavoidable, but business leaders must preempt the risk to stay ahead of the competitive curve. For instance, Tata Motors recently replaced Hyundai as the second-largest automaker in the Indian market. The key driver for Tata Motors was their anticipation and ability to handle the scarcity of semiconductors effectively, thereby reducing the time to delivery for their clients.

A structured solution for supply chain risk management

Businesses must focus on enhancing use of analytical methods and techniques to create a trustworthy data-based supply chain risk framework to tackle upstream supply chain deviations and uncertainties. This method makes it possible to observe when supplies are arriving and helps to prevent production losses driven by material shortages while substantially lowering expedition expenses. However, it would be best if you established connections between Tier 2 suppliers and the manufacturing unit to assist in cataloguing essential performance indicators and significant variables. Furthermore, creating a resilient monitoring system through automation enhances decision-making with speed, transparency, and cooperation can help address the challenges (Exhibit 2).

Exhibit 2: upstream supply chain resilience monitoring

1. Define and classify the risk

Risk management aims to identify and comprehend possible hazards before they manifest in the supply network. It helps you examine the insights, estimate the chance of occurrence, and prioritize prompt actions. Few risks can be classified and documented more quickly if they have occurred in the past. However, strategic risk factors, including geopolitical difficulties, natural catastrophes, the financial health of suppliers, and other worldwide shortages, have a low likelihood of occurring. To de-risk these factors, it is necessary to take a different approach of mitigation and ensure consistency of on-time delivery of materials. The threats are clubbed into several categories once classified, as shown below (Exhibit 3).

Exhibit 3: risk classification

2. Risk computation and prioritization

Combining comprehensive domain and industry knowledge with advanced analytics equips you to assess and prioritize risk based on mathematically calculated risk scores. Further, in conjunction with the risk matrix, you can define priorities for risk resolution and action on all three levels (Exhibit 4). Also, it is crucial to keep an eye on how specific risk variables and their behaviors interact to produce enhanced risk situations.

Exhibit 4: risk scoring thresholds

Organizations leverage the power of predictive modelling to ensure products have the highest possibility of arriving on schedule and in sufficient quantities at their intended places thus helping mitigate risk.

Exhibit 5 demonstrates the risk matrix thresholds regarding the comprehensive risk modeling© algorithm developed by the authors.

Exhibit 5: Benchmarking (Illustrative)

3. Risk Mitigation

Utilizing the below enablers can help risk managers, leaders, and planners with intelligent decision-making:

1.Feedback capability

De-risking can be time-consuming, but by including an interactive feedback loop, organizations can work with internal and external stakeholders to find a solution.

2. Recommend action

The feedback loop is handy for understanding planner deviations, identifying practical and productive solutions, and exchanging best practices.

3. Alternate plan

The risk mitigation strategy also facilitates the establishment of a scenario planning workbench that enables planners to simulate (what-if), identify, and evaluate various choices for minimizing downtime and comprehending alternative production schedules.

Conclusion

Organizations must have robust programs to anticipate and mitigate supply chain risks as they are irreversible and expand faster than local supply chains. Business leaders should strive to create a data-driven and structured risk management strategy. It is essential to be nimble to develop effective procedures and reliable governance frameworks in the new-normal, dictating a shift from the conventional way of thinking.

(The authors are Mr. Manish Srivastava (Vice President Supply Chain Analytics & Digital Practice | Genpact), Nikhar Sharma (Asst. Vice President Supply Chain Analytics & Digital Practice | Genpact) and Prasad Havre (Asst. Vice President Supply Chain Analytics Delivery | Genpact) and the views expressed in this article are their own)