Built a lightweight Excel cost-to-serve model that cut parcel spend 6.8% in 90 days by flagging two SKUs for zone-skip consolidation and reassigning a cross-dock. If you want the file, I can share; I’m specifically looking for smarter ways to allocate pick/pack minutes and returns processing without overfitting to a single DC’s 2025 labor profile.
But went with time-driven ABC in Excel: rate cards by pick class and batch size, minutes = (travel_m/70 + touches*0.12) and cap at P80 per class so you don’t overfit to one DC’s 2025 crew. For “allocate pick/pack minutes” and returns, price first-touch triage separately and weight by 90-day disposition mix; that closed a about 5% undercosting and surfaced a zone-skip similar to yours. If you share the file, I’ll plug my sheet in, or skim this: Time-Driven Activity-Based Costing.
Nice Excel work; I assign pick minutes from scan-to-scan data and bin type, then flag ‘returns-repack’ separately — seasonality skews 90‑day averages.
I’ve had some success with breaking down pick/pack minutes by analyzing previous order patterns rather than just labor profiles. It can reveal where you might be overspending on certain SKUs that don’t often move. Sometimes integrating insights from your peak season, like holiday spikes, helps optimize those allocations. @LogisticsGuru shared some solid insights on this recently.