Tracking Signal Chart Calculator

Measure forecast bias with tracking signal chart. Review period errors, MAD, and cumulative deviations quickly. Make clearer forecasting decisions across teams and reporting cycles.

Calculator Inputs

Enter actual and forecast values using commas, spaces, or new lines. Optional labels help name each period on the chart.

Use warning ±3 and control ±4 for a common planning rule.
120, 125, 129
or
120
125
129

Example Data Table

Period Actual Forecast Error Absolute Error RSFE MAD Tracking Signal
Jan1201182222.001.00
Feb128130-2202.000.00
Mar1331312222.001.00
Apr1411374462.502.40
May145148-3332.601.15
Jun1501491142.331.71

Formula Used

Forecast Error: Error = Actual - Forecast

Absolute Error: |Error| = absolute value of Error

RSFE: RSFE = Σ(Actual - Forecast)

MAD: MAD = Σ|Error| / Number of Periods

Tracking Signal: Tracking Signal = RSFE / MAD

A large positive signal suggests under-forecasting. A large negative signal suggests over-forecasting. Many teams review values against limits such as ±3 and ±4.

How to Use This Calculator

  1. Enter actual demand, sales, or production values.
  2. Enter forecast values in the same order and count.
  3. Add optional labels for months, weeks, or batches.
  4. Set warning and control limits for your review rules.
  5. Click the calculate button to generate the full table.
  6. Review final tracking signal, breaches, and chart movement.
  7. Download the output as CSV or PDF if needed.

Frequently Asked Questions

1. What does a tracking signal measure?

It measures forecast bias over time. The value combines cumulative forecast error with mean absolute deviation to show whether forecasts are consistently too high or too low.

2. Why are limits like ±4 commonly used?

They provide a practical control band for monitoring bias. When the tracking signal crosses those limits, many analysts treat the forecast process as out of control and investigate causes.

3. What does a positive tracking signal mean?

A positive value usually means actual values are exceeding forecasts. In simple terms, the forecasting process may be underestimating demand or output.

4. What does a negative tracking signal mean?

A negative value usually means forecasts are higher than actual outcomes. That points to over-forecasting and possible excess inventory, staffing, or production planning.

5. Why can the tracking signal become undefined?

It becomes undefined when MAD equals zero. That happens if every forecast error is zero, leaving no average deviation to divide into cumulative error.

6. How many periods should I include?

Use enough periods to observe a pattern, not just one unusual point. Monthly teams often review six to twelve periods, while fast operations may use weekly data.

7. Can I use weekly or daily forecasts?

Yes. The calculator works for any consistent time interval, including daily, weekly, monthly, or quarterly data, as long as actual and forecast series align properly.

8. Is tracking signal the same as forecast accuracy?

No. Accuracy metrics show error size, while tracking signal focuses on direction and accumulation of bias. They work best together in a complete forecast monitoring process.

Related Calculators

cumulative forecast errortracking signal limits

Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.