What frameworks explain a local retailer's bankruptcy and pre-collapse signals?

[FrankBP]

I'm an MBA student working on a case study about a local retail chain that recently filed for bankruptcy. For my business failure analysis, I'm trying to move beyond obvious factors like poor location or online competition. I want to examine deeper systemic issues, perhaps in their supply chain management, capital structure, or organizational culture. What frameworks or methodologies are most effective for conducting a thorough post-mortem on a business failure? Are there specific financial ratios or operational metrics that are particularly telling in the years leading up to a collapse?

[JosephTM]

Good starting point: frame the analysis with defensible frameworks. Use Altman Z-score and O-score to gauge bankruptcy risk; DuPont decomposition to trace where earnings, asset efficiency, and leverage failed; a simple 5 Whys for root-cause; plus a narrative timeline linking key decisions to financial signals. A quick crosswalk of strategy, structure, and capabilities (McKinsey 7S) can reveal misalignments that no one talks about until cash runs dry.

[ChloeL]

Key ratios to pull from the 3–5 years before collapse: liquidity (current ratio, quick ratio, cash on hand), solvency and leverage (debt-to-equity, interest coverage, debt maturity profile), profitability (gross, operating, net margins; ROA/ROE), and cash conversion (operating cash flow, free cash flow). Efficiency: inventory turnover, DSO, DIO, DPO. Watch for deteriorations, especially if revenue grows but cash flow tanks or debt escalates.

[StellaT]

Operational metrics: inventory obsolescence, supplier concentration, days payable, fill rate, backorders, capacity utilization, and capex-to-revenue. A creeping increase in average discounting or promo pressure that hurts margins can foretell trouble. Also monitor working capital cycle length and need for working capital to finance growth.

[Sofia66]

Governance and culture: look for incentives misaligned with profitability (growth-at-all-costs), debt covenants tightening liquidity, rapid leadership changes, or complex off-balance-sheet commitments. Map governance via frameworks like 7S or VRIO to spot capability gaps that hinder execution under stress.

[NoraG]

Common pitfalls: data quality issues, survivorship bias, focusing only on one-year signals, ignoring seasonality, and not triangulating with qualitative signals (customer, supplier, employee sentiment). Also beware of restatements and accounting quirks that can disguise true performance.

[ScottA]

Practical 6-step post-mortem: 1) collect 5–years of data and build a timeline of major decisions; 2) compute and plot key ratios; 3) perform root-cause analysis with 5 Whys; 4) run scenario tests on debt, working capital, and revenue; 5) check governance and culture signals; 6) produce a concise findings report with a risk map, proposed fixes, and a watchlist for early warning signals.