Project future storage capacity needs based on current usage and growth rate.
Capacity planning at its simplest divides the remaining free space by the rate at which it's being consumed — this gives a linear projection of when storage will run out if current growth trends continue unchanged. It's a first-pass planning tool rather than a precise forecast, since real growth is rarely perfectly linear; seasonal spikes, data purges, and new application onboarding can all shift the actual runway significantly from this estimate.
Months to full
months_to_full = (total_capacity − used_capacity) / monthly_growth
Real storage growth is often non-linear — new projects or data sources can cause step-changes in growth rate, retention policy changes or archival/purge jobs can cause sudden drops, and growth itself frequently accelerates over time as an organization's data footprint expands. Use this as an early-warning estimate and revisit it monthly with updated actuals.
Most storage teams start capacity expansion planning at 70-80% utilization, since procurement, provisioning, and migration lead times (especially for SAN/NAS hardware) can take weeks to months — waiting until near 100% risks an outage before new capacity arrives.
Use an average monthly growth rate calculated over several recent months (not just the last month) to smooth out one-off spikes, and re-run this calculation regularly rather than treating a single projection as fixed — trending the projected full date over time reveals whether growth is accelerating or stabilizing.