Measuring efficiency has never been more critical as hybrid work models raise questions about remote productivity and AI's impact on workers’ potential, Bloomberg reports. But productivity data is notoriously volatile and misleading. The official government gauge has "error-prone" inputs, says Harvard's Jason Furman. The pandemic saw huge swings not reflective of actual efficiencies. There are still debates about 1940s figures.
With slowing population growth in developed nations, productivity must increase to provide for more retirees. But the shift from goods to services complicates metrics. It's easier to gauge auto plant productivity than elderly home care worker productivity, a major growth area. Business-level measures also vary, from billable hours to bugs fixed. The mismatch fosters distrust, with most workers feeling productive while few bosses agree, per a Microsoft survey.
Experts urge looking beyond quarterly fluctuations toward long-term trends. Pinpointing productivity could determine whether AI generates major gains or fizzles out. It may also settle whether remote work boosts or hinders corporate performance, fueling heated debates. With so much riding on these elusive metrics, companies are urgently trying to quantify productivity more accurately.
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