Great Deal! Get Instant \$10 FREE in Account on First Order + 10% Cashback on Every Order Order Now

Purpose of Assignment The purpose of this assignment is for students to learn how to apply operations forecasting. Resources Microsoft® Excel® Assignment Steps Select a business operations data set...

Purpose of Assignment

The purpose of this assignment is for students to learn how to apply operations forecasting.

Resources

Microsoft® Excel®

Assignment Steps

Selecta business operations data set from the internet or other sources which can be used for forecasting.

Developa minimum of three quantitative forecasts using Microsoft®Excel®.

• Compare and contrast each quantitative forecast you develop.
• Choose the one forecast you determine would be the best for the firm and be prepared to explain why you chose this.
• Evaluate the impact this forecast would have on the firm from a financial metrics standpoint.

Developa 700-word report in which you describe your forecasting project including details on all the assignment steps.

Formatyour assignment according to APA guidelines.

Answered Same Day Jul 01, 2021

Solution

Saloni answered on Jul 03 2021
Forecasting Data
Forecast is an anticipation, projection and estimation of future event, activity or occu
ence. In business ,forecasting refers to what is going to happen in future by analyzing past and present data. Overall, it is a instrument that helps management in to cope with the uncertainty of the future. The main use of data forecasting method is to evaluate capital cost of a business, future business revenues and expenses.
Quantitative Methods : These type of methods are established on mathematical (quantitative) models, and are unbiased in feature. They are dependent purely on the mathematical calculations. These methods are used to predict future data as a outcome of past data and are appropriate when past data are available. Quantitative methods use two models-
· Associate Models : It figures out that the variable being evaluated is related to other variables in the environment. It uses Linear Regression Method.
· Time Series Models- It examines past pattern of data and strive to evaluate the future based upon the underlying patterns contained within those data. It opeartes moving average method, exponential smoothing method and trend projection method.
There are a wide range of quantitative budget forecasting tools, the top three methods discussed here are-
· Straight Line Method
· Moving average
· Exponential Smoothing
Technique
Data needed
Use
Maths involved
1. Straight line
Historical Data
Continuous growth rate
Lowest level
2. Moving average
Historical Data
Frequent evaluation
Lowest level
3. Exponential Smoothing
Historical Data
Finance and economics
Lowest level
1. Straight Line Method - One of the easiest and simplest method to forecast data is Straight Line Method. A financial analyst uses documented figures of previous years and trends to evaluate future growth in revenue.
We use this method to find out the sales growth from the previous year. So we use the formula (Yearly sales revenue for 2nd year - Yearly sales revenue of 1st year) /Yearly sales revenue of 2nd year. A graphical representation of the sales growth is attached below-
2. Moving Average Method- Moving average is one of the best option if no medium of information is available other than sales history. The main idea to average out the sales results on monthly, quarterly and yearly basis is to get better forecast on a longer term trend which influences the results of the sales.
We , in the attached sheet have calculated average on 5 year and 10 year basis. To find out the average forecast,we put the formula =Average(Range of cells showing last five year revenue). Then press Ctrl key with ‘D’ to copy the formula down through 20 years.We can also drag down the cell to copy the formula for the next 15 years. Similarly, moving average of 10-year is calculated = Average(B2:B10).
A graphical representation to show the Actual and Moving Average has been attached below. We figure out that the 5-Year MA changes to a greater level with a clear increase in the 10Year MA.
3. Exponential Smoothing- It is analogous to moving average, it similarly use documented data of previous years to forecast the future. You take the e
ors in the last year forecast and use that result to improve the next year forecast. The basic idea is to precise the next result in a way that would have made the earlier results better.
We calculate the results by clicking on Data->Data Analysis -> Exponential Smoothing. In the input range select the cu
ent yearly sales revenue, damping factor is the weight placed for the most recent sales results. Here 0.4 has been selected as there is a regular increase in sales revenue ....
SOLUTION.PDF