## Scattergraph Method

The scattergraph method is a visual technique used primarily in cost accounting and managerial decision-making to help determine the behavior of costs, especially with respect to the relationship between total costs and activity levels. It helps in estimating the variable and fixed components of a mixed cost by plotting past historical data points and then fitting a straight line (often done manually) through the scattered points.

Here’s a step-by-step explanation of the scattergraph method:

**Data Collection:**Gather historical data that includes the activity level (e.g., machine hours, production volume) and the associated total cost.**Plot Data Points:**Using a scatter plot, plot the activity levels on the x-axis and the associated total costs on the y-axis. Each data point represents a period (e.g., a month or a quarter).**Draw a Line:**Manually draw a straight line that best fits the data points. This line should capture the general trend of the data points.**Interpret the Line:**The point where the line intersects the y-axis represents the estimated fixed cost (because at 0 activity level, the cost remains fixed). The slope of the line represents the variable cost per unit of activity.**Estimate Costs:**Using the interpreted line, one can estimate costs for a given activity level. The formula based on the line is y=mx+cy=mx+c, where mm is the slope (variable cost per unit of activity) and cc is the y-intercept (fixed cost).

**Advantages:**

- It’s a simple and straightforward method.
- It provides a visual representation of cost behavior.
- It can help in spotting outliers or irregularities in the data.

**Disadvantages:**

- It’s subjective since drawing the “best fit” line depends on the individual’s judgment.
- It may not be as accurate as other methods (like the high-low method or regression analysis) because it doesn’t necessarily use a mathematical approach to fit the line.
- It’s more suitable for smaller datasets; with a lot of data points, the scatter can become too difficult to interpret.

Despite its limitations, the scattergraph method can be a useful preliminary tool for understanding cost behavior, especially when combined with other methods for more rigorous analysis.

## Example of the Scattergraph Method

Let’s look at a practical example involving the scattergraph method.

Suppose a small manufacturing company wants to understand the relationship between the number of units produced and the total production cost, which includes both variable and fixed costs.

**Data for the Past 6 Months:**

Month | Units Produced | Total Production Cost ($) |
---|---|---|

Jan | 100 | 1,200 |

Feb | 150 | 1,650 |

Mar | 200 | 2,100 |

Apr | 250 | 2,550 |

May | 300 | 3,000 |

Jun | 350 | 3,450 |

**Steps:**

**Plot Data Points:**Plot each month’s data on a scatter plot with Units Produced (x-axis) and Total Production Cost (y-axis).**Draw a Line:**By visually examining the data points, you can see they form an upward trend. Draw a straight line that seems to fit these points best. For simplicity, let’s assume the line goes through the points (100, 1,200) and (350, 3,450).**Interpret the Line:****Fixed Cost:**Observe where the line intersects the y-axis. Let’s say it touches the y-axis at $500. This suggests that when no units are produced, the production cost is $500, which would be the fixed cost.**Variable Cost:**To find the slope (or variable cost per unit), pick any two points on the line. Using the two points we mentioned:- Change in cost = 3,450 – 1,200 = 2,250
- Change in units = 350 – 100 = 250

**Conclusion:**

From the scattergraph method, the company can estimate that for each unit produced, the production cost increases by $9 (variable cost). No matter the production level, there’s a consistent cost of $500 (fixed cost).

So, if the company plans to produce 400 units next month, the estimated production cost would be:

= (Variable cost per unit x Units) + Fixed cost

= ($9 x 400) + $500

= $3,600 + $500

= $4,100

Remember, while this method gives a reasonable estimate, it’s based on visual interpretation and past data. The actual costs can vary due to various factors not captured by this analysis.