Excel GROWTH Function
last modified April 4, 2025
The GROWTH function calculates predicted exponential growth based
on existing data. It returns values along an exponential trend line. This
tutorial provides a comprehensive guide to using the GROWTH
function with detailed examples. You'll learn basic syntax, practical
applications, and advanced techniques to master this statistical function.
GROWTH Function Basics
The GROWTH function predicts exponential growth by fitting an
exponential curve to existing data points. It uses the least squares method to
find the best fit. The function returns y-values for specified x-values.
| Component | Description |
|---|---|
| Function Name | GROWTH |
| Syntax | =GROWTH(known_y's, [known_x's], [new_x's], [const]) |
| Arguments | known_y's (required), known_x's (optional), new_x's (optional), const (optional) |
| Return Value | Array of predicted y-values |
This table breaks down the essential components of the GROWTH
function. It shows the function name, syntax format, arguments, and return
value characteristics.
Basic GROWTH Example
This example demonstrates the simplest use of the GROWTH function with basic data points.
| A | B |
|---|---|
| 1 | 2 |
| 2 | 4 |
| 3 | 8 |
| 4 | =GROWTH(B1:B3, A1:A3, A4) |
The table shows x-values in column A and corresponding y-values in column B. The GROWTH formula in B4 predicts the next y-value for x=4 based on the existing data.
=GROWTH(B1:B3, A1:A3, A4)
This formula predicts the y-value for x=4 based on the exponential trend of the existing data points. The result will be approximately 16, following the pattern of doubling (2,4,8,16...).
GROWTH with Multiple Predictions
GROWTH can return multiple predictions at once when given multiple new x-values. This example shows this capability.
| A | B | C |
|---|---|---|
| 1 | 100 | |
| 2 | 150 | |
| 3 | 225 | |
| 4 | ||
| 5 | ||
| =GROWTH(B1:B3, A1:A3, A4:A5) |
This table demonstrates predicting multiple future values at once. The formula in C6 returns predictions for both x=4 and x=5 based on the growth trend.
=GROWTH(B1:B3, A1:A3, A4:A5)
This array formula predicts y-values for x=4 and x=5. Based on the 50% growth rate in the data (100,150,225), the results will be approximately 337.5 and 506.25. Remember to enter as an array formula (Ctrl+Shift+Enter in older Excel).
GROWTH with Const Argument
The const argument controls whether to force the curve through the origin (0,0). This example shows the difference when const is FALSE.
| A | B | C |
|---|---|---|
| 1 | 10 | |
| 2 | 30 | |
| 3 | 90 | |
| 4 | =GROWTH(B1:B3, A1:A3, A4, FALSE) |
The table shows how setting const=FALSE affects the prediction. The formula forces the exponential curve to pass through the origin (0,0), changing the growth rate calculation.
=GROWTH(B1:B3, A1:A3, A4, FALSE)
This formula predicts the y-value for x=4 while forcing the curve through (0,0). The result will be different from the default const=TRUE case. This is useful when you know the relationship must pass through the origin.
GROWTH for Revenue Projections
This practical example uses GROWTH to project future revenue based on quarterly growth data.
| A | B | C |
|---|---|---|
| Q1 | 50000 | |
| Q2 | 65000 | |
| Q3 | 84500 | |
| Q4 | =GROWTH(B1:B3, , C1:C3) |
The table shows quarterly revenue data with GROWTH used to predict Q4 revenue. Note we're omitting known_x's to use default sequence (1,2,3).
=GROWTH(B1:B3, , C1:C3)
This formula predicts Q4 revenue based on the exponential growth trend from previous quarters. With 30% quarterly growth (approximately), the result will be around 109,850. This demonstrates GROWTH's business forecasting application.
GROWTH with Non-Numeric X Values
GROWTH can work with non-numeric x-values by converting them to numeric equivalents. This example uses months as x-values.
| A | B | C |
|---|---|---|
| Jan | 200 | |
| Feb | 240 | |
| Mar | 288 | |
| Apr | =GROWTH(B1:B3, ROW(A1:A3), ROW(A4)) |
The table shows how to handle text x-values by converting them to row numbers. The ROW function provides numeric equivalents for the month names.
=GROWTH(B1:B3, ROW(A1:A3), ROW(A4))
This formula predicts April's value by treating months as positions 1,2,3. The result will be approximately 346, continuing the 20% monthly growth trend. This technique works for any ordered categorical data.
The GROWTH function is powerful for analyzing and predicting
exponential trends in data. From business forecasting to population modeling,
it provides valuable insights. Remember to use it when growth is multiplicative
rather than additive. Combine with data validation for robust spreadsheets.
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