Lean supply chains minimize waste — inventory, capacity buffers, redundant sourcing — and are highly efficient under normal operations, but the COVID-19 pandemic and shocks such as the global semiconductor shortage exposed their fragility under disruptions. The recommended remedies (extra inventory, backup sourcing, capacity reservations) protect against disruptions but degrade efficiency, and it is currently unknown whether this trade-off is fundamental: can a supply chain be simultaneously lean-efficient and resilient, is the relationship between efficiency and resilience a trade-off (substitution) or a synergy (complementation), and does a well-defined 'tipping point' — a boundary separating configurations where lean measures dominate from those where resilience measures dominate — exist, and where does it lie as a function of the supply chain's parameters? Recent work by Ivanova (2025, 2026) formalizes this question as the lean-resilience tipping point (LRTP) problem, extending the AURA and low-certainty-need (LCN) frameworks, while the literature review of Lücker, Timonina-Farkas, and Seifert (2024) shows that the coupling of efficiency and resilience research is very recent and identifies the value of dual-purpose versus dedicated resilience levers as an open gap. The general question of the existence, location, and trade-off-versus-synergy nature of the lean-resilience boundary remains open.

Background

Supply chain management distinguishes two kinds of risk. Recurrent risk arises from ordinary mismatches between supply and demand (demand fluctuations, quality problems, lead-time variability) in the absence of disruptions; a supply chain's ability to mitigate recurrent risk is its efficiency. Disruption risk arises from rare, severe events — natural disasters, pandemics, geopolitical conflicts, factory fires — that interrupt supply, production, or logistics; the ability to prepare for, absorb, and recover from such disruptions is supply chain resilience. Lean management — just-in-time (JIT) production with minimal inventory, single sourcing, and tight capacity buffers — is the classical toolkit for efficiency, but it leaves little slack, and multiple recent crises showed that maximally lean chains fail under disruption. The standard resilience remedies are redundancies: safety stock, backup suppliers, capacity reservations, and dual sourcing. These hold cost and no benefit when no disruption occurs, so they degrade efficiency in expectation. Whether this tension is a law or an artifact of particular designs is the question at issue.

Several strands frame it. First, an older paradigm debate: Naylor, Naim, and Berry (1999) analyzed 'leagility' — combining lean and agile (responsiveness-oriented) paradigms in one chain — and showed the combination is possible by splitting the chain at a decoupling point, the location where product-specific information meets generic material flow; the lean-resilience tipping point question is the modern, risk-oriented analogue of asking where such a boundary lies, but now between efficiency and disruption-robustness rather than efficiency and responsiveness.

Second, Dmitry Ivanov's frameworks: the low-certainty-need (LCN) supply chain (Ivanov and Dolgui, 2018) proposes designing chains whose performance depends little on accurate knowledge of future disruptions, rather than betting on predetermined control strategies; and the AURA framework (Active Usage of Resilience Assets; Ivanov, 2021) coined 'lean resilience' — the idea that resilience assets should be actively used for value creation in normal times rather than held as passive, cost-driving shields, which would make resilience and efficiency partially complementary.

Third, the literature review of Lücker, Timonina-Farkas, and Seifert (2024, Production and Operations Management) formally separates efficiency (mitigating recurrent risk) from resilience (mitigating disruption risk), observes that only recently have the two been studied jointly, distinguishes dual-purpose levers (resources that improve efficiency and expected resilience simultaneously) from dedicated resilience levers (resources that protect against particular disruptions without any benefit in their absence), and calls for research on their value to overall supply chain performance, noting particular gaps in multi-echelon (multi-stage) and multi-product settings. Building on this, Marina Ivanova poses the question directly — 'do lean and resilience contradict each other? can they complement each other? can a supply chain be both efficient and resilient?' — and introduces a formal model for locating the lean-resilience tipping point (LRTP), the boundary or optimal blend separating lean-dominant from resilience-dominant configurations, illustrated through a simulation-based example (IFAC-PapersOnLine 2025; International Journal of Integrated Supply Management 2026). Her papers treat the general question as open: how the tipping points should be allocated between lean and resilience, and how the two concepts can complement each other, are explicitly posed as the papers' two critical questions, and the model is demonstrated on an illustrative example rather than as a general characterization.

Problem Statement

Determine whether a supply chain can be simultaneously lean-efficient and resilient, and characterize the lean-resilience tipping point between them. Concretely, for a supply chain in which decision-makers can deploy both lean efficiency measures (just-in-time flow, minimal inventory, single sourcing, tight buffers) and resilience capabilities (safety stock, backup sourcing, capacity reservations, and related redundancies), the problem asks: (1) Existence and location — does a well-defined tipping point or boundary exist whose location identifies the optimal blend (combination) of lean and resilience capabilities in the model, separating configurations in which lean measures dominate from those in which resilience measures dominate, and where does this boundary lie within the pinned supply chain model? (2) Nature — are lean efficiency and resilience substitutes, so that any resilience gain must be paid for in efficiency (a fundamental trade-off), or complements, for example through dual-purpose levers that serve both objectives at once (a synergy), and under which conditions does each regime hold? The question concerns a stated supply chain model class with formal definitions of efficiency and resilience performance, and asks for a characterization of the tipping point's existence and location and of whether efficiency and resilience are substitutes or complements for that class, rather than an illustration of a single simulation instance.

References

  1. Ivanova, M. (2026). 'Lean-resilience tipping point location in the supply chain.' International Journal of Integrated Supply Management 18(2): 113–131. DOI 10.1504/IJISM.2026.152995. https://doi.org/10.1504/ijism.2026.152995
  2. Ivanova, M. (2025). 'Lean vs resilient supply chain: in search of the tipping point and synergies.' IFAC-PapersOnLine 59(10): 77–81. DOI 10.1016/j.ifacol.2025.09.015. https://doi.org/10.1016/j.ifacol.2025.09.015
  3. Lücker, F., Timonina-Farkas, A., and Seifert, R. W. (2024/2025). 'Balancing Resilience and Efficiency: A Literature Review on Overcoming Supply Chain Disruptions.' Production and Operations Management 34(6): 1495–1511 (online first 18 December 2024). DOI 10.1177/10591478241302735. https://doi.org/10.1177/10591478241302735
  4. Ivanov, D. (2021/2022). 'Lean resilience: AURA (Active Usage of Resilience Assets) framework for post-COVID-19 supply chain management.' The International Journal of Logistics Management 33(4): 1196–1217 (online first 2 February 2021). DOI 10.1108/IJLM-11-2020-0448. https://doi.org/10.1108/IJLM-11-2020-0448
  5. Ivanov, D. and Dolgui, A. (2018/2019). 'Low-Certainty-Need (LCN) supply chains: a new perspective in managing disruption risks and resilience.' International Journal of Production Research 57(15–16): 5119–5136 (online first 14 September 2018). DOI 10.1080/00207543.2018.1521025. https://doi.org/10.1080/00207543.2018.1521025
  6. Naylor, J. B., Naim, M. M., and Berry, D. (1999). 'Leagility: Integrating the lean and agile manufacturing paradigms in the total supply chain.' International Journal of Production Economics 62(1–2): 107–118. DOI 10.1016/S0925-5273(98)00223-0. https://doi.org/10.1016/S0925-5273(98)00223-0
  7. Alemsan, N., Tortorella, G., Taboada Rodriguez, C. M., Balouei Jamkhaneh, H., and Lima, R. M. (2022). 'Lean and resilience in the healthcare supply chain – a scoping review.' International Journal of Lean Six Sigma 13(5): 1058–1078. DOI 10.1108/IJLSS-07-2021-0129. https://doi.org/10.1108/IJLSS-07-2021-0129
  8. Tortorella, G., Kumar, M., Thürer, M., Browning, T. R., Hines, P., Romero, D., and Furlan, A. (2026). 'Lean and organizational resilience: A discussion.' International Journal of Production Economics 293: 109897. DOI 10.1016/j.ijpe.2025.109897. https://doi.org/10.1016/j.ijpe.2025.109897
  9. Ning, Y., Yuan, Y., and Ren, Y. (2026). 'The Productivity–Operational Resilience Trade-Off in Agri-Input Supply Chains: Evidence From China's Nitrogen Fertilizer Industry.' Agribusiness (online first 25 June 2026). DOI 10.1002/agr.70128. https://doi.org/10.1002/agr.70128