Introduction
Grocery retailing is an essential service in Australia, yet the networks that keep supermarket shelves stocked are long, concentrated and increasingly exposed to climate and health shocks. Two national chains account for roughly two-thirds of grocery sales, and the bulk of volume moves through a small number of distribution centres and linehaul corridors (ACCC 2024). Between 2020 and 2022, Australian shoppers repeatedly encountered empty shelves that were caused not by production shortfalls but by disrupted logistics, demonstrating that product availability depends as much on network design as on farm output (Productivity Commission 2021).
This paper assesses the supply chain resilience of Meridian Grocers, a hypothetical national full-line grocery retailer operating 430 supermarkets across all Australian states and territories. The retailer is supplied by one national ambient distribution centre (DC) in Melbourne, six state fresh DCs and approximately 1,900 direct suppliers. Resilience is understood here as the capacity of a network to prepare for, respond to and recover from disruption while restoring service at acceptable cost and within acceptable time (Christopher & Peck 2004; Ponomarov & Holcomb 2009). The analysis proceeds in three stages: it maps vulnerabilities across the farm-to-store network and calculates risk priority scores, it analyses four candidate resilience strategies, and it evaluates those strategies to recommend a sequenced investment portfolio.
The Australian Disruption Context
Recent Australian experience supplies the evidence base for the vulnerability assessment. In January 2022, floodwaters washed out sections of the Trans-Australian Railway west of Adelaide, severing the principal freight link to Perth for more than three weeks and prompting visible rationing of staples in Western Australian supermarkets. Weeks later, the February-March 2022 floods across south-east Queensland and northern New South Wales inundated concentrated growing regions such as the Lockyer Valley and the Northern Rivers, closed sections of the Bruce and Pacific highways and forced fresh produce onto longer inland routes at significant cost. These events revealed that transport corridors, rather than farms alone, are frequently the binding constraint on grocery availability.
The COVID-19 pandemic stressed the same network from the demand and labour sides. Panic buying in March 2020 lifted food retail turnover by more than 20 per cent in a single month, far beyond what replenishment systems were designed to absorb (ABS 2020). In January 2022, the Omicron wave then removed a substantial share of the distribution and transport workforce through isolation requirements, with reported absenteeism above 20 per cent in some facilities, producing gaps in meat, produce and pantry categories even though farm production was largely unaffected. Consumer behaviour and workforce availability therefore constitute disruption channels in their own right.
Policy settings reinforce the case for deliberate resilience planning. The Productivity Commission (2021) concluded that Australian supply chains are generally robust but that a small set of critical dependencies warrants active management by firms rather than governments. The National Freight and Supply Chain Strategy similarly prioritises resilient freight corridors as a national objective (Commonwealth of Australia 2019). Because the intensity of heavy rainfall events is projected to increase, flood disruption should be treated as a recurring operating condition for Australian retail logistics rather than an exceptional event (CSIRO & Bureau of Meteorology 2022).
Vulnerability Mapping of the Farm-to-Store Network
Six nodes in the Meridian Grocers network were assessed using structured scenario analysis. Likelihood was scored from 1 to 5, where 5 indicates a disruption expected at least once a year over a five-year horizon, and impact was scored from 1 to 5, where 5 indicates a severe network-wide availability failure lasting longer than a week. A risk priority score (RPS) was then calculated for each node as: RPS = likelihood × impact. For the interstate linehaul corridors, for example, the calculation is RPS = 4 × 5 = 20 out of a maximum of 25. The full vulnerability map is presented in Table 1.
Table 1: Vulnerability map of the Meridian Grocers farm-to-store network (scores 1-5; RPS = likelihood × impact)
| Supply chain node | Disruption scenario | Likelihood | Impact | RPS | Priority rank |
|---|---|---|---|---|---|
| Interstate linehaul corridors | Flood closure of east-west rail and coastal highways | 4 | 5 | 20 | 1 |
| Grower regions (fresh produce) | Flood inundation of concentrated growing regions (Lockyer Valley, Northern Rivers) | 4 | 4 | 16 | 2 |
| DC and transport workforce | Pandemic isolation rules removing 20-30 per cent of rostered shifts | 4 | 3 | 12 | 3 |
| National ambient DC (Melbourne) | Single-site failure through fire, flood or industrial action | 2 | 5 | 10 | 4 |
| Import container flow (Port of Melbourne, Port Botany) | Port congestion and international freight rate escalation | 3 | 3 | 9 | 5 |
| Store delivery and cold chain | Extreme heat compromising temperature-controlled last-mile delivery | 3 | 2 | 6 | 6 |
Two features of the map deserve emphasis. First, the two highest-ranked risks both arise from geographic concentration: reliance on a handful of east-coast growing regions and on a small number of linehaul corridors that cross flood-prone country. The likelihood ratings for these scenarios are grounded directly in the 2022 experience rather than in speculative modelling. Second, the national ambient DC receives a low likelihood score but the maximum impact score, making it a classic low-probability, high-consequence single point of failure of the kind Sheffi and Rice (2005) identify as the most commonly neglected vulnerability in efficiency-optimised networks. Pettit, Croxton and Fiksel (2019) caution that resilience investment should be matched to mapped vulnerabilities, since capability that exceeds exposure erodes profitability, and the strategy analysis below follows that principle.
Figure 1 illustrates the farm-to-store product flow and highlights the interstate linehaul corridor as the priority failure point identified in Table 1. Fresh produce moves from growers through regional consolidation directly to state DCs, but ambient volume crosses the highlighted corridor on almost every path to a store outside Victoria, which explains the corridor’s maximum impact score.
Resilience Strategy Analysis
Four strategies are analysed against the mapped vulnerabilities. Following Tang (2006), preference is given to robust strategies that improve everyday performance as well as disruption performance, so that resilience spending is not purely an insurance cost.
Dual Sourcing of Fresh Produce
Splitting volume for the highest-turnover fresh lines between two climatically separate growing regions, such as south-east Queensland and northern Victoria or Tasmania, directly targets the second-ranked vulnerability in Table 1. If either region floods, the alternate region can be scaled up within days rather than weeks, reducing the impact score from 4 to 2 and the RPS from 16 to 8. The costs are real but bounded: buying prices rise by an estimated 2-4 per cent on covered lines because volume discounts are diluted, and dual accreditation adds audit and quality assurance overhead. Dual sourcing also delivers everyday benefits in seasonal coverage and supply continuity, consistent with the readiness phase of resilience that Hohenstein et al. (2015) identify as the cheapest point of intervention. Contractual arrangements with the second grower base must still meet the fair dealing obligations that apply to grocery buying relationships in Australia (ACCC 2024).
Buffer Stock and Safety Stock
Buffer stock operates at two levels: operational safety stock that absorbs routine variability, and a strategic reserve that covers corridor-scale disruption. Operational safety stock is sized using the standard formula SS = z × σd × √L, where z is the service-level factor, σd is the standard deviation of daily demand and L is replenishment lead time in days (Silver, Pyke & Thomas 2017). Table 2 summarises the inputs for a representative line, UHT milk, at the Perth state DC.
Table 2: Safety stock parameters, UHT milk, Perth state DC
| Parameter | Symbol | Value |
|---|---|---|
| Mean daily demand (units) | d | 3,200 |
| Standard deviation of daily demand (units) | σd | 640 |
| Replenishment lead time (days) | L | 9 |
| Service-level factor (98 per cent cycle service) | z | 2.05 |
Substituting these values: SS = 2.05 × 640 × √9 = 2.05 × 640 × 3 = 3,936, or approximately 3,900 units. The corresponding reorder point is ROP = (3,200 × 9) + 3,936 = 32,736 units. This protects against ordinary variability, but the January 2022 rail washout stretched the effective lead time to Perth towards 30 days, which no economically sensible cycle safety stock can cover. The appropriate instrument is a strategic reserve of shelf-stable staples for Western Australia and the Northern Territory sized at 14 days of demand, or 14 × 3,200 = 44,800 units for this line. At a landed cost of $1.20 per unit and an annual holding rate of 22 per cent, the holding cost is 44,800 × $1.20 × 0.22, approximately $11,800 a year for this line, and an estimated $3.5 million annually when applied across the 300 highest-priority staple lines. Positioning the reserve west of the corridor before the northern wet season converts a three-week outage into a manageable service degradation, reducing the linehaul RPS from 20 to 12.
Nearshoring of Private Label Supply
Meridian Grocers currently sources a large share of private label pantry lines from offshore contract manufacturers, exposing them to the port congestion node in Table 1. Shifting high-velocity lines to Australian manufacturers addresses that exposure and shortens lead times from roughly 36 days by sea to 9 days domestically. Because safety stock scales with the square root of lead time, the reduction from √36 = 6 to √9 = 3 halves the safety stock required for those lines, partially offsetting an estimated 5-8 per cent unit cost premium driven by higher Australian labour and energy costs. Domestic manufacturing capacity is the binding constraint, so nearshoring is best staged over three years and confined to lines where velocity justifies the premium. This tempered approach is consistent with the Productivity Commission (2021) finding that wholesale onshoring is rarely cost-effective, whereas targeted domestic capability for genuinely critical lines can be.
Supply Chain Visibility Technology
A visibility layer, comprising a control tower that integrates supplier portals, GPS and cold chain telemetry, DC throughput data and Bureau of Meteorology flood warnings, shortens the interval between disruption and decision. Digital twin capability extends this by allowing the network to be stress tested against corridor closures before they occur (Ivanov & Dolgui 2021). During the 2022 floods, the retailers that performed best were those that pushed stock into exposed regions ahead of forecast rainfall, a response that is only possible with integrated early warning. Visibility investment is comparatively cheap, an estimated $4 million in capital plus ongoing licences, and it raises the effectiveness of every other strategy, but it adds no physical capacity of its own and therefore complements rather than substitutes for redundancy (Sheffi & Rice 2005).
Strategy Evaluation and Recommendations
Each strategy is evaluated against three criteria: indicative cost, resilience gain expressed as the RPS reduction on the targeted node, and its role in the overall portfolio. Table 3 presents the evaluation and the resulting recommendations.
Table 3: Strategy evaluation for Meridian Grocers
| Strategy | Indicative cost | Resilience gain | Recommendation |
|---|---|---|---|
| Visibility technology (control tower, telemetry, digital twin) | Low-moderate: about $4m capital plus licences | Faster detection and response across all six nodes; raises returns on every other strategy | Adopt first as the enabling investment |
| Strategic buffer stock (WA and NT staples) | Moderate: about $3.5m annual holding cost | Linehaul corridor RPS 20 to 12 | Adopt now; resize the reserve before each wet season |
| Dual sourcing of fresh produce | Moderate: 2-4 per cent buying premium on covered lines | Grower region RPS 16 to 8 | Adopt for the top 20 fresh categories in the next contracting round |
| Nearshoring of private label lines | High: 5-8 per cent unit premium, partly offset by halved safety stock | Import node RPS 9 to 6 | Adopt selectively; stage over three years |
The sequencing logic follows directly from the risk map. Visibility is adopted first because it delivers the largest risk reduction per dollar and increases the value of the physical strategies. The strategic reserve follows immediately because it addresses the highest RPS in Table 1 and can be in place before the next wet season. Dual sourcing is timed to the fresh produce contracting cycle, while nearshoring, the weakest standalone business case, proceeds selectively as a hedge against freight cost volatility. One material residual risk remains: the single national ambient DC. Rather than committing immediately to a second site, the recommendation is a feasibility study, since duplicating a national DC is precisely the kind of capability overshoot against which Pettit, Croxton and Fiksel (2019) warn. Governance should embed the RPS review into quarterly sales and operations planning, with availability performance during disruptions reported to the board, aligning the retailer’s internal practice with the resilience objectives of the national freight strategy (Commonwealth of Australia 2019).
Conclusion
This paper mapped the vulnerabilities of a hypothetical national grocery retailer and found that the dominant risks arise from geographic concentration: flood-exposed linehaul corridors, clustered east-coast growing regions and a single national ambient distribution centre. The 2022 floods and the pandemic validated the likelihood scores attached to these scenarios, which is why the two highest risk priority scores, 20 and 16, both involve flooding. The recommended portfolio, sequenced from visibility technology through strategic buffer stock and dual sourcing to selective nearshoring, reduces those scores to 12 and 8 at a combined cost that is modest relative to the revenue and reputation protected. Resilience should be managed as a continuing capability with seasonal review, not a one-off project, because Australian climate projections indicate that the disruptions of 2022 represent an operating condition that national grocery retailers must now plan around as a matter of course.
References
Australian Bureau of Statistics (ABS) 2020, Retail trade, Australia, March 2020, cat. no. 8501.0, ABS, Canberra.
Australian Competition and Consumer Commission (ACCC) 2024, Supermarkets inquiry: interim report, ACCC, Canberra.
Christopher, M & Peck, H 2004, ‘Building the resilient supply chain’, The International Journal of Logistics Management, vol. 15, no. 2, pp. 1-13.
Commonwealth of Australia 2019, National Freight and Supply Chain Strategy, Department of Infrastructure, Transport, Cities and Regional Development, Canberra.
CSIRO & Bureau of Meteorology 2022, State of the Climate 2022, Commonwealth of Australia, Melbourne.
Hohenstein, N-O, Feisel, E, Hartmann, E & Giunipero, L 2015, ‘Research on the phenomenon of supply chain resilience: a systematic review and paths for further investigation’, International Journal of Physical Distribution & Logistics Management, vol. 45, no. 1/2, pp. 90-117.
Ivanov, D & Dolgui, A 2021, ‘A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0’, Production Planning & Control, vol. 32, no. 9, pp. 775-788.
Pettit, TJ, Croxton, KL & Fiksel, J 2019, ‘The evolution of resilience in supply chain management: a retrospective on ensuring supply chain resilience’, Journal of Business Logistics, vol. 40, no. 1, pp. 56-65.
Ponomarov, SY & Holcomb, MC 2009, ‘Understanding the concept of supply chain resilience’, The International Journal of Logistics Management, vol. 20, no. 1, pp. 124-143.
Productivity Commission 2021, Vulnerable supply chains, study report, Productivity Commission, Canberra.
Sheffi, Y & Rice, JB 2005, ‘A supply chain view of the resilient enterprise’, MIT Sloan Management Review, vol. 47, no. 1, pp. 41-48.
Silver, EA, Pyke, DF & Thomas, DJ 2017, Inventory and production management in supply chains, 4th edn, CRC Press, Boca Raton.
Tang, CS 2006, ‘Robust strategies for mitigating supply chain disruptions’, International Journal of Logistics: Research and Applications, vol. 9, no. 1, pp. 33-45.