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Playbook · Supply chain

Supply chain and supplier resilience

Resilience is a balance between vulnerability and capability, not a maximum of buffers. This path maps dependencies, tests visibility, and chooses between collaboration and inventory with the recovery time in view.

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6 steps · 6 cited sources · free during beta

The question this path answers

Where is the network exposed, and which capability or buffer actually reduces the exposure?

The path, step by step

  1. Map dependencies and single points of failure

    Map tier-one and critical tier-two suppliers, sites, ports and shared services. For each, estimate the operational impact and the time to recover if it stopped.

    Why it worksRisk frameworks pair vulnerabilities with capabilities. Mapping only the supplier list hides shared dependencies and the concentration that turns a local failure into a network one.

    EvidenceChopra & Sodhi (2004) · Pettit et al. (2010)

    CheckpointA dependency map with the ten highest-impact exposures and a recovery-time estimate for each.

    Common failureCounting suppliers as if two sources in the same region were independent.

  2. Test visibility and information flow

    Check how quickly you learn about a delay, how accurate the ETA is, and whether suppliers can see the demand signal they are planning against.

    Why it worksResilience research links information sharing and connectivity to visibility, and visibility to a more robust response. A buffer without warning still arrives late.

    EvidenceSheffi & Jr. (2005) · Pettit et al. (2010)

    CheckpointMeasured latency and accuracy of supplier and shipment signals for critical items.

    Common failureAssuming a monthly supplier report is a real-time warning system.

  3. Segment suppliers and choose develop or exit

    Classify suppliers by spend, criticality and performance. For strategic or constrained suppliers, set a joint improvement plan; for replaceable poor performers, qualify an alternative.

    Why it worksSupplier management is not one programme. Development effort has to be reserved for relationships where capability matters, while transactional suppliers are governed by service and price.

    EvidenceChopra & Sodhi (2004) · Pettit et al. (2010)

    CheckpointEvery critical supplier has a named strategy, owner and review date.

    Common failureApplying a standard scorecard to every supplier and changing nothing.

  4. Choose buffering versus bridging deliberately

    For each top exposure, compare the cost and recovery time of a buffer (stock, capacity, dual source) against a bridging action (collaboration, visibility, flexible routing).

    Why it worksDisruption research finds that no single strategy dominates: inventory, sourcing flexibility and collaboration each protect different parts of the flow, and the right mix depends on the failure mode.

    EvidenceTomlin (2006) · Sheffi & Jr. (2005) · Pettit et al. (2010)

    CheckpointA decision per exposure with cost, recovery time and the failure mode it addresses.

    Common failureBuying inventory for every risk, including the ones inventory cannot cover.

  5. Stress-test and rehearse the response

    Run a tabletop or simulation of the most plausible disruption. Walk through detection, decision rights, customer communication and recovery, and fix the gaps you find.

    Why it worksFirms that prepare for disruptions recover faster and lose less market value than firms that improvise. A plan that has never been exercised is a document, not a capability.

    EvidenceHendricks & Singhal (2005) · Pettit et al. (2010)

    CheckpointA rehearsed response with named decision rights and a measured recovery time.

    Common failureKeeping the continuity plan in a folder that nobody has opened.

  6. Track recovery and update the map

    After any disruption or near miss, record detection time, recovery time and what actually helped. Update the dependency map and the buffer decisions.

    Why it worksResilience is learned from exposure. Without a post-event review, the same vulnerability is rediscovered with the same surprise.

    EvidenceHendricks & Singhal (2003) · Tomlin (2006)

    CheckpointA post-event review with measured timings and at least one changed decision.

    Common failureTreating recovery as heroism rather than a system result to be measured.

The evidence base

Each step above cites hand-selected research. These are the studies behind the path.

More from the library

Further reading from Portolan's research library, matched by subject. These papers are not proof that any step works; check each checkpoint against your own operation.

  • Durach et al. (2020) — Supplier–supplier coopetition and supply chain disruption: first-tier supplier resilience in the tetradic context
  • Norrman & Jansson (2004) — Ericsson's proactive supply chain risk management approach after a serious sub‐supplier accident
  • Hohenstein (2022) — Supply chain risk management in the COVID-19 pandemic: strategies and empirical lessons for improving global logistics service providers’ performance
  • Barker et al. (2026) — Inertia Versus Adaptation: Relational Resilience in Buyer–Supplier Relationships Facing Extreme Disruption
  • Nikookar et al. (2024) — Building an antifragile supply chain: A capability blueprint for resilience and post‐disruption growth
  • Song et al. (2022) — How to enhance supply chain resilience: a logistics approach
  • Faruquee et al. (2021) — Strategic supplier relationships and supply chain resilience: Is digital transformation that precludes trust beneficial?
  • Liu & Lee (2018) — Integration, supply chain resilience, and service performance in third-party logistics providers
  • Juan et al. (2021) — An integrated model of supply chain resilience and its impact on supply chain performance under disruption
  • Ivanov & Dolgui (2020) — A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0

Guides for this path

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