In order to find out how profitable or unprofitable an enterprise is, it is not enough just to count money. To understand this for sure, and most importantly, to help increase profits, you need to regularly conduct a factor analysis of the revenue and overall performance of the enterprise. And for this you need to have some skills in the accounting field and certain information. It is worth considering that the company worked both at the time of inflation and during the crisis. Prices are constantly changing. Now you understand why a trivial calculation of money does not make it possible to objectively assess the situation with profit or costs? After all, you must take into account the price factor.
So, many find it difficult to do factor analysis. An example of our analysis, we hope, will help them make their own - by analogy, this type of diagnosis is drawn up extremely quickly. It is made in the form of a table. First, we’ll make a cap for our factor analysis. We draw a table in 5 columns and 9 rows. Make the first column wider — it will contain the names of the articles in the enterprise, not the numbers. It will be called - "Indicators", which you should write in the first row of the column. In it, fill in all the lines according to the model: 1 - name, 2 - put the number 1 - column numbering, write down in the 3rd line - "Sales revenue", 4 - "Cost". In the fifth row of the first column, put the item - "Selling expenses". In 6 write - "Costs for process control." The seventh line is called “Profit from sales”, and 8 - “Index of changes in prices”, and the last, 9th line - “Sale at comparable prices”.
Next, we go to the design of 2 columns: in 1 line we write - "Previous period, thousand rubles." (you can write other monetary units - euro, dollar, etc. - it depends on what currency you will be calculating in), and in the second line we write the number - 2. Go to column 3 - in it 1 line has the name - "Reporting period", thousand rubles And the second one is filled with the number 3. Next, we draw up our factor analysis of revenue and go to column 4. In the first line, enter “Absolute change, thousand rubles, ” and the second line contains a small formula: 4 = 3-2. This means that the indicators that you will write in the next lines will be the result of subtracting the indicators of the second column from the indicators of the third. We proceed to the design of the last - 5 columns. In it, in 1 line you need to write: "Relative changes%", which means that in this column all the data will be recorded in percentage terms. In the second line, the formula: 5 = (4/2) * 100%. That's all, we designed the cap, it remains only to fill each item in the table with the relevant data. We carry out factor analysis, an example of which we give you. First of all, we calculate the price change index - this is perhaps the most important figure in our calculations. We write the numbers of different periods in the corresponding columns. In columns 4 and 5 we carry out the necessary calculations. Factor analysis, an example of which you can see, assumes accuracy in numbers. Therefore, to write in 3 lines of each column you need only reliable information. In 4 and 5, again, we carry out the calculations. As you understand, factor analysis of costs is mainly carried out in lines 5 and 6: try to add as much as possible real, not underestimated figures. In columns 4 and 5 of these lines, again carry out the calculations using the formulas. Next, we carry out a factor analysis of revenue in column 7 - profit. We write down reliable numbers in columns 2 and 3, and again in 4 and 5 we calculate everything according to the formulas. And the last column remains: we write the data, calculate it. Bottom line: factor analysis, an example of which we give you, shows what is the influence of each of the factors described in the articles on profit or production costs. Now you see the weaknesses and you can correct the situation in order to get the greatest possible profit.
You did all the calculations to conduct a factor analysis, but they will not help you if you do not analyze the data thoroughly.
