Supply chain resilience refers to the capacity of networks to anticipate, adapt to and recover from unexpected shocks. Inventory strategies play a central role in this capacity. This essay evaluates two widely taught models, Economic Order Quantity (EOQ) and Just-In-Time (JIT), assessing their ability to sustain operations during pandemics, natural disasters and geopolitical tensions. While both approaches offer distinct advantages, evidence indicates that neither is fully sufficient on its own when global disruptions occur.
Theoretical Foundations of EOQ and JIT
The EOQ model, first formulated by Harris (1913) and later popularised by Wilson (1934), calculates an optimal order quantity that minimises the combined costs of ordering and holding stock. It assumes relatively stable demand, constant lead times and predictable costs. In contrast, JIT, developed by Toyota in the 1950s and 1960s, aims to eliminate waste by receiving materials only when they are required for production or sale (Ohno, 1988). JIT therefore relies on short lead times, reliable suppliers and minimal buffer stock. Both models rest on assumptions of continuity that can be challenged by sudden, large-scale events.
EOQ and Resilience During Disruptions
Because EOQ typically prescribes larger order quantities and safety stock, it can provide a buffer when supply is interrupted. During the early months of the COVID-19 pandemic, firms holding modest EOQ-derived inventories were sometimes able to continue production while competitors faced immediate shortages (Christopher, 2016). However, the strategy carries limitations. Holding extra stock increases warehousing, insurance and obsolescence costs, which can erode competitiveness under normal trading conditions. Moreover, EOQ calculations rely on historical demand data; when consumption patterns shift abruptly, as occurred with sudden surges in demand for personal protective equipment, the model’s recommendations quickly become outdated (Tang, 2006). Consequently, EOQ offers partial resilience only when demand remains relatively predictable.
JIT and Vulnerability to Supply Shocks
JIT’s emphasis on minimal inventory makes it inherently more exposed to disruption. The 2011 Tōhoku earthquake and tsunami severely affected Japanese automotive and electronics firms that practised JIT; many plants halted within days because component deliveries ceased (Matsuo, 2015). Similar patterns emerged during the 2021 Suez Canal blockage and subsequent semiconductor shortages, where JIT-dependent manufacturers could not draw on internal stocks. Although JIT reduces holding costs and improves quality through frequent small deliveries, these strengths become liabilities when transport links break or suppliers are closed by lockdowns. Firms have therefore attempted to add limited safety stock or dual sourcing, yet such modifications move the system away from pure JIT principles and increase complexity (Liker and Choi, 2004).
Comparative Evaluation and Hybrid Considerations
A direct comparison reveals a trade-off between efficiency and robustness. EOQ can absorb short-term shocks through inventory buffers but at higher steady-state cost, while JIT minimises waste yet amplifies the impact of any supply failure. Empirical studies of supply-chain glitches show that companies with leaner inventories experience larger and longer-lasting performance declines after disruptions (Hendricks and Singhal, 2005). Therefore, neither model in isolation maximises resilience across all disruption types. Some organisations now combine elements of both, employing EOQ-style calculations for critical components while retaining JIT for stable, locally sourced items. Such hybrid approaches require careful segmentation of products and suppliers, increasing managerial demands.
Implications for Practice and Further Research
For UK undergraduate supply-chain students, the evidence suggests that inventory strategy selection must be contingent on the likelihood and duration of potential shocks. Where geopolitical risk is high, modest buffers calculated through adapted EOQ models may be justified. Where cost pressure dominates and suppliers are diversified, JIT may still be viable provided contingency contracts exist. Future research could usefully examine how digital tools, such as real-time visibility platforms, alter the risk profiles of both strategies.
In conclusion, EOQ provides limited resilience through inventory buffers but incurs ongoing costs and relies on stable assumptions, whereas JIT maximises efficiency yet leaves supply chains highly vulnerable to global shocks. Effective resilience appears to rest on context-specific hybrids rather than adherence to either pure model. Managers must therefore balance cost efficiency against the probability and severity of disruption when designing inventory policies.
References
- Christopher, M. (2016) Logistics and Supply Chain Management. 5th edn. Harlow: Pearson.
- Harris, F.W. (1913) ‘How many parts to make at once’, Factory, The Magazine of Management, 10(2), pp. 135-136.
- Hendricks, K.B. and Singhal, V.R. (2005) ‘Association between supply chain glitches and operating performance’, Management Science, 51(5), pp. 695-711.
- Liker, J.K. and Choi, T.Y. (2004) ‘Building deep supplier relationships’, Harvard Business Review, 82(12), pp. 104-113.
- Matsuo, H. (2015) ‘Implications of the Tohoku earthquake for Toyota’s coordination mechanism: supply chain disruption of automotive semiconductors’, International Journal of Production Economics, 161, pp. 217-227.
- Ohno, T. (1988) Toyota Production System: Beyond Large-Scale Production. Cambridge, MA: Productivity Press.
- Tang, C.S. (2006) ‘Perspectives in supply chain risk management’, International Journal of Production Economics, 103(2), pp. 451-488.
- Wilson, R.H. (1934) ‘A scientific routine for stock control’, Harvard Business Review, 13(1), pp. 116-128.
