Case Study: Navigating a persistent inflation shock—how a mid-market Australian operator rebuilt resilience without a rate cut tailwind

Context: The macro squeeze is back—and this time it bites the P&L

Recent inflation readings in Australia dampened hopes of quick interest rate cuts, a sentiment reinforced by industry commentary across the property and finance sectors. With mortgage stress rising and the cost of capital remaining elevated, the operating picture for Australian firms is clear: demand volatility, tighter financing, and stubborn input costs. The competitive landscape is simultaneously becoming more digital and more concentrated—Australia’s competition regulator notes Google holds nearly 94 per cent of search market share (ACCC, December 2024), raising customer acquisition costs for many firms reliant on paid search.

On the policy front, Canberra is pushing responsible productivity adoption. The Australian Government’s AI policy (August 2024) aims to accelerate safe use of AI across public services—“to demonstrate leadership in embracing AI to benefit Australians,” as policy lead Lucy Poole noted—while Australia’s eight AI Ethics Principles set boundaries for deployment. Yet Australia’s AI ecosystem still shows a gap in commercialisation relative to adoption (June 2025 ecosystem review), suggesting many enterprises will import solutions or partner with global vendors to find near-term gains.

Decision: Three moves when rates don’t rescue you

Faced with sticky inflation and higher-for-longer rates, our focal company—an anonymised, ASX-adjacent mid-market consumer operator—took a CFO-led approach built around three choices:

• Defend margin with precision, not blunt increases. Move from uniform price rises to micro-segmented pricing and mix management to minimise elasticity blowback.
• Rebase cost-to-serve through Lean + AI. Use Lean/Six Sigma to simplify work, then apply AI/automation only where stable processes exist and governance aligns with Australia’s AI Ethics Principles.
• Reallocate capital to speed cash. Prioritise working-capital velocity over discretionary capex, and renegotiate supplier terms through a Kraljic-style risk/value lens.

Implementation: Evidence-first, with technical depth where it matters

1) Revenue and pricing

• Elasticity mapping: Built SKU-level elasticity curves using transaction history and cohort analysis; phased 1–2 per cent list price lifts only where cross-price elasticity was low, while boosting mix toward higher-margin bundles.
• Marketing ROI reset: Given platform concentration, the team reduced over-reliance on paid search auctions dominated by a single provider (ACCC: ~94 per cent share) and re-balanced into retail media, direct channels, and partnerships. Introduced media mix modelling (MMM) to quantify diminishing returns and reallocate spend weekly.

2) Cost and operations

• Lean-first simplification: Mapped order-to-cash and claims processes; removed handoffs and rework (FMEA + value-stream mapping), then targeted automation only for stable subprocesses.
• AI with guardrails: Deployed retrieval-augmented generation for policy lookups and customer-service knowledge, with human-in-the-loop approvals. Aligned model use with the Australian Government’s AI policy and the eight ethics principles (human-centred values, fairness, privacy/security, reliability/safety, transparency, contestability, accountability).

3) Balance sheet and cash

• Working-capital sprints: Instituted two-week sprints to reduce aged receivables and standardise payment terms; dynamic discounting for suppliers willing to trade price for early payment.
• Supplier segmentation (Kraljic): Shifted high-risk/high-value inputs to dual-source contracts; converted low-risk commodities to e-auctions with index-linked pricing where possible.

Results: Illustrative ROI model under inflation pressure

To quantify what “good” can look like in this environment, the team built a conservative model for a mid-market operator with $50 million annual revenue and 40 per cent gross margin. These are illustrative calculations for decision-making, not reported company results:

• Targeted price/mix lift: A 1.0 per cent price increase with a 0.3 per cent volume reduction lifts revenue by ~0.7 per cent. On $50m revenue, that is +$350,000. At 40 per cent gross margin, gross profit rises by ~$140,000.
• Marketing reallocation: Cutting 15 per cent of underperforming paid search spend (identified via MMM) and shifting to higher-ROI channels can reduce blended CAC by 8–12 per cent. On a $4m annual marketing budget, a 10 per cent efficiency improvement frees ~$400,000, part reinvested in retention.
• Lean + selective automation: Removing 10 minutes of handling from a process run 500,000 times annually saves ~83,000 labour hours. At $35 fully loaded hourly cost, that’s ~$2.9m in addressable cost. Capturing just 25 per cent through redeployment delivers ~$725,000 in P&L benefit.
• Working capital: Reducing DSO by 5 days on $50m revenue (assuming even monthly sales) releases roughly $685,000 in cash, lowering interest expense at current borrowing rates.

Combined effect: In-year P&L uplift of ~$1.3–1.5m and liquidity improvement approaching $0.7m are achievable when these levers are executed together, creating margin cover against inflation without relying on rate cuts.

Market context and competitive advantage

Where’s the edge? First, digital customer acquisition is concentrated—Australia’s search market structure (ACCC) means many firms overpay at the margin. Firms that use MMM and incrementality testing to diversify spend typically capture share while peers remain stuck in auction-driven cost inflation. Second, Australia’s AI ecosystem shows a commercialisation gap; early adopters can partner with proven global platforms but embed local guardrails to move faster than rivals. Third, suppliers are also under pressure—Kraljic-driven negotiations tied to inflation indices and service-level reliability can unlock price certainty others don’t secure.

Implementation reality: What trips teams up

• Data quality vs. AI ambition: Without clean process maps and standard data, AI only accelerates chaos. Lean first, then automate.
• Elasticity misreads: One-size pricing lifts backfire in price-sensitive segments. Start with controlled tests and measure cross-price effects.
• Change fatigue: Two-week sprints with visible wins (e.g., DSO reduction) build momentum while the macro remains uncertain.
• Governance: Align AI deployment to Australia’s eight AI Ethics Principles to manage reputational, legal and security risk.

Future outlook: Planning in scenarios, not wishes

With commentary suggesting rate relief may be slower than hoped, executives should plan for three paths: (1) Sticky inflation—double down on pricing precision and procurement indexation; (2) Gradual disinflation—shift savings from cost to growth experiments while locking in cash velocity wins; (3) Downside shock—activate zero-base cost plans and renegotiate covenants early. Across all scenarios, responsible AI adoption—guided by the government’s policy and ethics principles—remains the most scalable lever to offset wage and input costs.

Lessons: What boards should demand now

• Evidence over opinion: Mandate MMM and elasticity measurement to drive pricing and media decisions, not anecdotes.
• Margin architecture: Treat margin as a system—pricing, mix, procurement, and service design—rather than a quarterly patch.
• Cash is strategy: Working-capital velocity is a strategic weapon when capital is costly.
• Responsible productivity: Pair Lean with AI under Australia’s ethics principles; move from pilots to scaled run-books.
• Partner where it pays: Given local commercialisation gaps, blend Australian governance with global-grade technology to accelerate time-to-value.

In a world where inflation proves stubborn and rate cuts are uncertain, the businesses that win are those that operationalise resilience—quantified, governed, and fast.