We obsess over cutting 10–15% of office space. But we ignore the ~40% sitting empty every day. That’s the real problem. Not how much space you have. But how well you use it. A scenario I keep seeing (simplified): 50,000 sq ft office @ ~45% utilisation → typical hybrid baseline You “optimise” → move to 40,000 sq ft Smaller footprint. Better building. Feels like progress. But behaviour, strategy and workplace design don’t change. Assumptions (kept clean and in USD for sake of it): • OPEX: $80/sq ft/year • Fit-out: $150/sq ft • CAPEX over 10 years Scenario A: 50,000 sq ft @ 45% • Cost: $4.0M • Used: 22,500 sq ft → $177.78 per used sq ft Scenario B: 40,000 sq ft @ 52% (utilisation lifts slightly, nothing else changes) • Cost: $3.8M (incl. CAPEX) • Used: 20,800 sq ft → $182.69 per used sq ft You cut space. Utilisation improved. Costs still went up. Scenario C: 40,000 sq ft @ 60% (designed properly for hybrid) • Same cost: $3.8M • Used: 24,000 sq ft → $158.33 per used sq ft Same building. Same spend. Completely different economics. This is the trap: A 10–20% space cut with marginal utilisation gains looks efficient… …but once CAPEX is included, you lock in a smaller, underperforming asset. Because across most portfolios: • Average utilisation: 35–55% • “Good”: ~50% • Real performance: 60%+ • Desks empty: 30–50% • Meeting rooms: 20–40% So the real question isn’t: “How much space can we cut?” It’s: “What utilisation and hybrid performance are we designing for?” Because: 52% → $182.69 60% → $158.33 That’s not a tweak. That’s a different outcome. The playbook is simple: • Measure properly • Redesign space mix • Align hybrid patterns • Then make space decisions If you’re moving 50,000 → 40,000 sq ft… Don’t just ask: “How much do we save?” Ask: “What happens to performance, what happens to cost per used sq ft?” That’s where the real story is. And that’s exactly why I wrote Destination 2.0 ....to shift the conversation from space… to performance. (Numbers are Illustrative but internally consistent numbers based on averaged out OPEX and fit-out benchmarks. Confidence: high based on aggregated industry data and Work Transformers Research and Intelligence Labs research.)
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