Leverage historical weight and cost data to build accurate shipping budget forecasts.
In the complex world of logistics, fluctuating freight costs can significantly impact your bottom line. For businesses relying on shipping—USFANS included—moving from reactive cost tracking to proactive forecasting is a game-changer. By harnessing the power of spreadsheet analytics, you can transform past shipping data into a reliable crystal ball for your future freight budget.
Accurate prediction starts with clean, organized historical data. In your spreadsheet (e.g., Microsoft Excel or Google Sheets), create a structured log with at least the following columns for past shipments:
Smooth out short-term volatility to see the underlying cost direction. Calculate a moving average (e.g., 3-month or 6-month) of your "Cost per Pound." This helps establish a baseline trend for future periods, filtering out one-time spikes or dips.
Use the CORREL
This is your most powerful tool. Use the SLOPEINTERCEPTPredicted Cost = (SLOPE * Planned Weight) + INTERCEPT
You can then input forecasted shipment weights to generate predicted costs.
Identify patterns that repeat annually (e.g., holiday peaks, seasonal surcharges). Compare the same month year-over-year to calculate a seasonal index, which can adjust your baseline forecasts for anticipated seasonal fluctuations.
Implementing this analytical approach delivers immediate and long-term benefits:
