For two decades, supply chain professionals have been caught in what feels like an impossible choice. On one side: lean operations, minimal inventory, just-in-time delivery, and razor-thin costs. On the other: resilience, safety stock, backup suppliers, and the flexibility to absorb shocks.

The pandemic seemed to settle the debate decisively. Lean was reckless. Resilience was essential. Companies that had optimized for efficiency found themselves paralyzed when a single supplier went dark or a shipping lane closed.

But this framing misses something important. The real problem was never lean itself—it was naive lean, implemented without understanding the difference between waste and strategic protection. The most sophisticated supply chains don't choose between efficiency and robustness. They've figured out how to get both.

Taiichi Ohno, who pioneered the Toyota Production System, identified seven types of waste: overproduction, waiting, transport, overprocessing, inventory, motion, and defects. His insight transformed manufacturing. But somewhere along the way, the nuance got lost.

Here's what many lean implementations miss: not all inventory is waste, and not all redundancy is inefficiency. Ohno himself maintained strategic buffers at key points in Toyota's system. The goal was never zero inventory—it was zero unnecessary inventory.

The distinction matters enormously. Waste is pure cost with no corresponding benefit: products sitting in warehouses that nobody wants, transportation routes that add time without adding value, quality defects that require rework. These should be eliminated ruthlessly.

Strategic buffers are different. They're insurance premiums—costs you pay to protect against specific, identifiable risks. A two-week safety stock of a critical component costs money, but if that component has a sole supplier in a geographically concentrated region, the buffer might be the cheapest form of protection available. The key is being intentional: knowing what risks you're buffering against, what those buffers cost, and whether cheaper alternatives exist.

Takeaway

Before labeling something as waste to eliminate, ask whether it's pure inefficiency or insurance against a specific risk. The answer determines whether cutting it makes you lean or just fragile.

The false dichotomy between lean and resilient dissolves once you discover strategies that reduce waste while preserving—or even enhancing—your ability to respond to disruption.

Postponement is perhaps the clearest example. Instead of manufacturing finished products to forecast, you produce standardized components and delay final configuration until customer orders arrive. Dell pioneered this in computers; Zara applies it to fashion. You get the efficiency of scale in component production plus the flexibility of late-stage customization. Inventory doesn't pile up because you're not betting on specific SKUs months in advance.

Modular design works similarly at the product level. When products share common platforms and components, you can maintain fewer distinct parts while serving diverse market needs. Volkswagen builds multiple car brands on shared architectures. If demand shifts between models, the component supply chain barely notices.

Multi-sourcing with concentration offers another path. Rather than single-sourcing for cost or spreading orders across many suppliers for safety, you develop deep relationships with two or three qualified suppliers. Primary volumes go to the most efficient source, but the relationships and systems are in place to shift quickly if needed. You're not paying for redundancy you never use—you're maintaining options at modest cost.

Takeaway

The best supply chain strategies don't trade efficiency for resilience or vice versa. They're architectural choices that make the trade-off less severe—or eliminate it entirely.

Traditional supply chain optimization starts with a forecast—expected demand, expected costs, expected lead times—and designs the network that performs best under those assumptions. This works beautifully when the future cooperates with your expectations.

When it doesn't, optimized-for-one-scenario networks can fail catastrophically. The distribution network perfectly tuned for normal demand becomes a bottleneck during a surge. The supplier chosen purely for cost becomes a liability when their region experiences disruption.

Scenario-based optimization takes a different approach. Instead of designing for one expected future, you identify multiple plausible scenarios—a demand surge, a supplier failure, a logistics disruption, a gradual shift in geographic demand—and design a network that performs acceptably across all of them.

The math gets more complex, but the logic is straightforward. You're not maximizing performance in the base case; you're maximizing expected performance weighted across scenarios, or minimizing your worst-case outcome, or finding the design that avoids catastrophic failure regardless of which future materializes. This often leads to solutions that look slightly suboptimal on a spreadsheet assuming normal conditions, but dramatically outperform naive designs when conditions shift. The modest cost of this apparent inefficiency is the premium you pay for a supply chain that actually works in the real world.

Takeaway

Optimizing for a single expected future creates fragility. Designing for multiple plausible scenarios builds a supply chain that performs in the world as it is, not just as you hope it will be.

The lean-versus-resilient debate was always a false choice, born from oversimplified implementations of both concepts. Real lean thinking eliminates waste—and waste only. Real resilience thinking invests in protection proportional to risk.

The sophisticated path forward combines both: ruthlessly eliminate pure inefficiency while strategically buffering against specific, identifiable risks. Adopt flexible strategies that reduce trade-offs. Design for multiple futures, not just the one you expect.

This isn't a compromise between efficiency and robustness. It's a recognition that the two concepts, properly understood, were never actually opposed.