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Retail math : talking the talk of retail business!There is dispute among segments of the retail industry as to the retail math terminology and calculations

used in the business. There is definitely a need for a "common language" for the industry as it pertains to

calculations and terms!

But, the following list of 15 different retail math formulas and explanations is the most common. It is the

"language" used by The Hallman Company in working with our clients in formulating and guiding them in

implementing their retail business plans:

Here are the "top 15" retail math formulas:

(1) $ Cost = $ Retail x (100% - Markup %)

Example: $100 retail item with 56% markup has a cost of $44

(100% - 56% = 44%)

$100 retail X .44 = $44.

Note: This retail math formula is useful for calculating the most you can pay for an item you need to retail

at $100, but want a markup of 56%.

Use this retail math formula in cost negotiations with vendors.

(2) Cost of Goods Sold (COGS) = Beginning Inventory + Purchases - End InventoryHere is another way of stating the same formula:

inventory at beginning of year + purchases or additions during the year = goods available for sale -

inventory at end of year = cost of goods sold

Example: Inventory @ cost Beginning of year = $1,000,000.

Purchases @ cost + freight During year = $550,000.

Total available ($1,000,000. + $550,000.) = $1,550,000.

Inventory On Hand end of year @ cost = $900,000.

Cost of Goods Sold ($1,550,000 - $900,000) = $600,000.

(3) $ Retail = $ Cost / (100% - markup %)


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Note: This retail math formula is used to determine the retail price to mark an item, when the cost and the

desired markup % is known.

Example: Cost on an item is $44. Desired markup is 56%. 100% - 56% = 44% cost complement to the

retail markup. Cost $ of $44 is divided by cost complement of .44 to arrive at target retail price of $100.

($44 divided by .44 = $100)

(4) $ Markdown = Original retail price - lower retail price

Example: Original retail price $100. New lower price $80. The markdown is $20. This 20% discount

becomes an markdown expense of 25% because the $20 must be divided by the $80 sale to be expressed

as a % to sales, the way other expenses are expressed as a % to sales.

(5) GMROI (Gross Margin Return on Investment) = Gross Margin $ divided by average inventory at cost.

Example: Annual Gross Margin $ of $400,000 with an average inventory cost of $150,000 would have a

GMROI of $2.67; in other words, for each dollar invested in inventory on average, the $1 invested

returned $2.67. ($400,000 divided by $150,000.) This is a particularly important retail math formula.

Most retailers do not pay enough attention to GMROI).

(6) Gross Margin = Sales - cost of good sold (Maintained Margin, supposed referred to as Gross

Margin, is the initial margin or markup less the cost of markdowns at cost.)

(7) Margin % = ($ Retail - $ Cost) / $ Retail

Example: $100 retail - $44 Cost = difference of $56. The $56 divided by $100 = 56%

(8) Markdown % = $ Markdown / $ Net Sales

Example: $20 markdown divided by $80 net sale = 25% retail markdown expense.

(9) Markup = The difference between the cost of an item and its selling price. This is the initial

markup, or initial margin, before the impact of markdowns.

A merchant's job is to turn the inventory often, while preventing the depreciation of the initial markup.

The NUMBER 1 cause of excessive markdowns is OVER_BUYING! Proper inventory planning,

provided for you by The Hallman Company, will prevent over-buying.

(10) Percent change in sales = this period of sales - Last period of sales / Last period of sales

Example: This period sales = $1,000,000. Last period sales = $900,000. $1,000,000 - $900,000 =

$100,000 increase. Increase of $100,000 divided by last period sales of $900,000 = 11.1% increase.


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(11)Planned Stock = planned monthly sales x stock sales ratio. Example: Planned monthly sales of

$100,000 X planned stock to sales ratio of 4.0 = a planned first of (planned) month inventory of

$400,000. Averaging a 4 to 1 stock to sales ratio each month (4 months supply on hand) will result in

achieving retail inventory turns of 3 per year.

(12)Stock Sales Ratio = B.O.M. $ Stock / Sales for period.

Note: B.O.M = beginning of month inventory. This is one retail math formula which can vary - many

companies look at cost inventory- not retail, when computing turns. We recommend retail inventory

management. Example: As in example above, a B.O.M. stock of $400,000 retail divided by that month's

sales of $100,000 = a stock to sales ratio of 4.0 to 1. ($400,000 divided by $100,000).

(13) Shrinkage = Difference between book and physical inventory. This is an "unknown" loss. A

markdown is a loss, but if it is recorded, it is a known loss, not shrinkage. If an item is broken or otherwise

damaged in stock and disposed of, and no markdown is recorded, it becomes an "unknown" loss, and is

reflected as a mysterious "shrinkage" in the inventory. Theft, of course, is unknown or unrecorded loss, or

shrinkage.

(14) "inventory turnover." Turnover is the number of times you sell your average investment in inventory

each year.

Turnover = net sales for period / average retailinventory for period. The "period" should be for at least 12

months.

Here is another way of stating the same formula:

Inventory turns:

The retail sales for a period divided by the average inventory value at retailfor that period. Most retailers

are in the range of two to four turns a year.Properly prepared Inventory Plans will significantly

increase your turns and decrease your average $ tied up in inventory, while increasing

your profits and boosting your cash flow. At The Hallman Company, we urge our clients to

express inventory turnover at retail, not cost. It is relatively easy to speed up inventory turns at cost- just

mark everything down to cost, sell it at cost, and you can "sell through" many more times during the

period. But we must not only increase turnover, we must at the same time protect the markup.

For more information on having your Inventory Plans with Open to buy custom-prepared for your retail

business, submit the contact us form from this site.

(15) Breakeven = Fixed Costs $ / (Net Sales - Contribution Margin %) Note: The Contribution Margin %

(CM) is the sum of the Variable Expense % + Cost of Goods Sold % after the impact of markdowns.

Breakeven Analysis: Simply stated, this formula indicates how much sales volume must be accomplished


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in order to cover all costs (fixed and variable), and begin generating a profit. In other words, it is the point

in sales volume at which you have no profit and no loss.

Support Here

Forecasting methods and formulas with ExcelBy Guillaume Saint-Jacques, 2008-06-18 (last revised, 2010-02-22)

This guide explains elementary forecasting methods that can be readily applied into

Microsoft Excel spreadsheets. This guide applies to managers and executive who need

to anticipate customer demand. The theory is illustrated with Microsoft Excel.

Advanced notes are available for software developer who would like to reproduce the

theory into a custom application.

Table of Contents[Hide/Show]

Forecasting methods and formulas with ExcelBenefits of forecastingHow to make things easy: labels, comments, filenamesGetting Started: a simple forecasting example using trendlinesForecasting using the Analysis Tool PackGoing further: the example of exponential fittingInstalling the Analysis Tool Pack (ATP)

Using the Analysis Tool Pack (ATP)... in a linear setting... using exponential fitting

How do I know what model to choose?Get advanced sales forecasts with Salescast

What people say

Benefits of forecasting

Forecasting can help you make the right decisions, and earn/save money. Here are a

few examples.

Define better sale strategies

If a product is declining, maybe it is a good idea to consider stop producing it. But

maybe not: maybe it is just your sales that are declining, but not your competitor's?

In this case, is there a chance that you can get your market share back?
http://www.lokad.com/support.ashxhttp://www.lokad.com/support.ashxhttp://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashxhttp://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashxhttp://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashxhttp://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_methods_and_formulas_with_Excel_11http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_methods_and_formulas_with_Excel_11http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Benefits_of_forecasting_3http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Benefits_of_forecasting_3http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_to_make_things_easy:_labels_comments_filenames_4http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_to_make_things_easy:_labels_comments_filenames_4http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Getting_Started:_a_simple_forecasting_example_using_trendlines_5http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Getting_Started:_a_simple_forecasting_example_using_trendlines_5http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_using_the_Analysis_Tool_Pack_6http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_using_the_Analysis_Tool_Pack_6http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Going_further:_the_example_of_exponential_fitting_7http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Going_further:_the_example_of_exponential_fitting_7http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Installing_the_Analysis_Tool_Pack_ATP_8http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Installing_the_Analysis_Tool_Pack_ATP_8http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Using_the_Analysis_Tool_Pack_ATP_9http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Using_the_Analysis_Tool_Pack_ATP_9http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_in_a_linear_setting_0http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_in_a_linear_setting_0http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_using_exponential_fitting_1http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_using_exponential_fitting_1http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_do_I_know_what_model_to_choose_10http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_do_I_know_what_model_to_choose_10http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Get_advanced_sales_forecasts_with_Salescast_12http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Get_advanced_sales_forecasts_with_Salescast_12http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#What_people_say_2http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#What_people_say_2http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#What_people_say_2http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Get_advanced_sales_forecasts_with_Salescast_12http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_do_I_know_what_model_to_choose_10http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_using_exponential_fitting_1http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#_in_a_linear_setting_0http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Using_the_Analysis_Tool_Pack_ATP_9http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Installing_the_Analysis_Tool_Pack_ATP_8http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Going_further:_the_example_of_exponential_fitting_7http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_using_the_Analysis_Tool_Pack_6http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Getting_Started:_a_simple_forecasting_example_using_trendlines_5http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#How_to_make_things_easy:_labels_comments_filenames_4http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Benefits_of_forecasting_3http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashx#Forecasting_methods_and_formulas_with_Excel_11http://www.lokad.com/forecasting-methods-and-formulas-with-excel.ashxhttp://www.lokad.com/support.ashx


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Forecasting techniques provide answers to these questions vital questions to your

business.

Size your inventories optimally

Time is money. Room is money. So what you want to do is use all means at your

disposal in order to reduce your stocks without experiencing any shortages, of

course.

How? By forecasting!

How to make things easy: labels, comments, filenames

Over time, as you data accumulate, you will be more and more likely to get confused;

to make mistakes. The solution? Don't be messy: making good use of labels, commentsand naming your files correctly can save you a lot of trouble.

Always label your columns. Use the first row of each column to describe the data it

contains.

Different data, different columns. Do not put different numbers (for example, you

costs and your sales), on the same column. It is incredibly likely for you to get

confused, and it makes computations and data handling more difficult.

Give each file a clearly understandable name. It takes little effort and speed things

up. It makes them easy to identify visually, and easier to find using the windows

search function.

Use Comments.

Even if you don't usually work with a large amount of data, it is still very easy to get

confused. This applies especially if you come back to the data you have created a

long time before. Excel has a great solution to offer: comments.

The usefulness of comments

Just do a right click on the cell you want to comment, and then select insert

comment .


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You can use them:

to explain the content of a cell (i.e. unit cost according to Mr Doe's estimates)

to leave warnings to future users of the sheet (i.e. I have a doubt about this

calculation... )

Get advanced sales forecasts with our webappSalescast. Lokad specializes in

inventory optimization through demand forecasting. The content of this tutorial - and

much more - are native features of Salescast.

Getting Started: a simple forecasting example using trendlines

Viewing your data

Let us now do our first forecast. In this part, we will be using this file:Example1.xls.

To repeat the steps by yourself, you can download the file. This data serves just as

example.

Our Data:- in the first column, data about the unit costs of similar products. The unit

cost reflects the quality of the product.- in the second one, data about how much has

been sold.

What we want to know: If we sell another product, with a quality corresponding to a

cost of $150/unit, how many units can we expect to sell?

How we get there: Here, it is pretty simple. We want to find a simple mathematical

relationship between unit cost and sales, and then use this relationship to do our

forecast.
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First, it is always useful to create a graph in Excel, in order to take a look at the data.

Your eyes are excellent tools that can help you identifying trends in a few seconds.

To do this, we select our data, then use Insert > Chart, and chose the XY(Scatter)

option. We want to estimate sales as a function of quality, therefore we put the unit

cost on the horizontal and the sales on the vertical axes.

Now, we stop a few seconds and take a good look at what we see: the relationship

seems to be increasing, and linear.

In order to get an idea of the exact form of the relationship, we right click on the

chart, and select the "Trendline" option.

Creating a trendline

Now, we have to select the relationship that seems to "fit" (i.e. best describe) our

data. Here again, we use our eyes: In this case, the dots are almost in a straight line,

so we use the "linear" setting. Later on, we will use other - more complex, but often

more realistic - settings, like "exponential".

Our trendline is now displayed on the chart. Another right click allows us to display


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the exact form of the relationship: y = 102.4x - 191.64.

Understand: Number of unit sold = 102.4 times the unit cost - 191.64.

So, if we decide to produce at a $150 unit cost, we can expect to sell 102.4*150 -

191.64 = 15168 units.

A linear trendline

We have just completed our first forecast successfully.

However, be careful: The software is always able to find a relationship between the

two columns, even if this relationship is in reality very weak! Therefore a check for

robustness is required. Here is how you quickly do this:

First, always take a look at the chart. If you find the dots closely located to the

trendline, as is the case in our example above, there is a good chance that therelationship is robust. However, if the dots seem to be located almost randomly and

are in general quite far from the trendline, then you should be careful: the

correlation is weak, and the estimated relationship should not be blindly trusted.


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The dots are everywhere: no evident relationship, unreliable forecasts

The dots "make sense", and allow more reliable forcasting

After taking a look at the chart, you can use the CORREL function. In our example,

the function would read: CORREL(A2:A83,B2:B83). If the result is close to 0, then the

correlation is low, and the conclusion is: there is simply no real trend. If it is close to


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1, then the correlation is strong. The latter is a helpful, since it increases the

explanatory power of the relationship you found.

There are more subtle ways of making sure the correlation is high; we will come back

to this later on.

Of course, these last steps can be automated: you don't have to note the relationship,

and use your pocket calculator to do the computation. You need the Analysis Tool

Pack!

Forecasting using the Analysis Tool Pack

Before proceeding, you should check if theExcel ATP(Analysis Tool Pack) is installed.

Refer to the section Installing the Analysis Tool Pack, for further information.

Unfortuntaley such perfect sales data with such a nice, simple linear relationship is

quite uncommon in real life. Let us have a look at what Excel has to offer for more

complicated situations, with more complicated data.

Going further: the example of exponential fitting

As you might imagine, such a linear model of your data is not always likely. In fact,

there are many reasons to believe that it should follow an exponential model. Many

behaviors in the economy are driven by exponential equations (i.e. interest

compounding computations are a classical example).

Here is how to perform an exponential fitting:

1) Take look at your data. Draw a simple graph, and just look at it. If they follow an

exponential evolution, they should look like this:
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erfect exponential shape

This is the perfect case. Of course, the data will never exactly look like this. But if

the dots seem to approximately follow this repartition, it should encourage you to

consider exponential fitting.

Using trendlines


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As in the previous example, you can always draw a chart of your data, ask for a

trendline, and choose exponential instead of linear.

Then, gather the displayed equation, as usual.

2) Luckily, you can also do all this directly, using the Analysis Tool Pack: Put all your

data into a blank excel sheet, and go to Tools => Data Analysis

Installing the Analysis Tool Pack (ATP)

The ATP is an add-in that comes with Microsoft Excel, but that is not always installed

by default. In order to install it, one can proceed as follows:

1. Make sure you have your Office CD with you. Excel might require you to insert the CD

in order to install the ATP files

2. Open an excel sheet, and go to Tools Menu, and then select Add-Ins. Check the firstbox of the window, labeled Analysis ToolPack .

3. Insert your Office CD if asked to do so by the software.

4. That's it! Notice that your Tools menu now includes many more features, including

a Data Analysis option. This is the one that we will use the most.

Using the Analysis Tool Pack (ATP)

... in a linear setting

Now, let us come back to our linear example. If your data looks good (see aboveillustration), you can use the ATP to get a direct estimation of the functional form,

without going through the trendline process.

Open your data sheet, then open the tools menu and select Data Analysis . A

window pops up, asking you what kind of analysis you want to perform. Select

regression for linear settings.

Now you need to give Excel two arguments: an Y range and an X range . The Y

range indicates what you want to estimate (i.e. your sales), and the X range contains

the data that you think can explain your sales (here, your unit cost). In our example(see example1.xls), our sales data are in column B, from row 3 to row 90, so you need

to put $B$3:$B$90 as the Y range, and $A$3:$A$90 as the X range. When you

are done, click ok .

A new sheet appears, containing the regression results .


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The Analysis ToolPack Output, in the case of an Ordinary Least Squares regression

The most important result is contained in the Coefficients column at the bottom

of the sheet. The intercept is the constant, and the X variable coefficient is the

coefficient of X (here, your unit cost). Hence, we find the same equation we found

using the trendline function. Sales = Intercept + Xcoefficient * unit costSales = -

126 + 100 * unit cost

This sheet also contains a useful number that gives you information about how good

your estimation is: the R Square . If it is close to 1, then your estimate is good,

which means that the equation you found is a fairly good representation of your data.If it is close to 0, then the estimation is not good, and you should probably try another

kind of fitting (see exponential fitting below).

This method is probably faster than the trendline techniques. However, it is a bit

more technical and much less visual. So if you do not want to go through the trouble

of plotting and eyeballing your data, make sure you at least check the R square

value.

... using exponential fitting

If the linear estimation does not go well (for instance if you obtain a low R-Squared,

i.e. 0.1), you may want to use Exponential Fitting.

Launch the Analysis Tool Pack, as usual: Open your data sheet, then open the

tools menu and select Data Analysis . A window pops up, asking what kind of

analysis you want to perform.


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In our exponential setting, what we want to select is exponential .

Notice that excel only asks you for one input range. Select the column that contains

the data you want to forecast (i.e. unit cost), and pick a smoothing factor.

How do I know what model to choose?

Note that you do not need to try every estimation method and then select the one

that works best. You do not need to try each estimation method in order to find the

one that works best for you. This can only be achieved through automation, since

there is such a large number of methods available. If you want all models to be

benchmarked against your data, you can consider sending them to Lokad. We have a

powerful computer system that tests all models and selects only the ones that work

best with the data of your business (find out more aboutwhat Lokad has to offer).

A powerful tool, however, that enables you to select the proper model is your own

eyesight: plot your data (see section 1), compare them to the following illustrations,

and pick the model that looks like your data.
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The Women's Department had a cumulative markuppercent of 55% and a markdown rate of 24% for themonth of October. What was the gross margin percent forOctober?(A) 44.2% (B) 43% (C) 41.8% (D) 31%

The Jewelry Department buys necklaces for $60 pernecklace. If each necklace has an initial markup percentof 75% of retail, what is the retail price of each necklace?(A) $105 (B) $180 (C) $210 (D)

$240

The manager of the Footwear Department hopes toachieve an annual turnover rate of 4.0 for next year. Inorder to achieve this rate, approximately what averageweekly sell through must be attained?(A) 13.0% (B) 8.3% (C) 7.7% (D)1.9%Questions 4 - 5 refer to the table below.

For the three month period shown in the table, what is the average value of inventoryat retail?(A) $612,000 (B) $636,500 (C) $643,667 (D) $675,333

What is the turnover rate for the three month period shown in the table?


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(A) 0.91 (B) 0.88 (C) 0.87 (D) 0.83

Last year, the accessories department had a gross margin percentof 40%, a turnover rate of 5.5, and a percent markup on average inventory of 55%.What was their gross margin return on investment (GMROI) last year?

(A) 0.99 (B) 4.00 (C) 4.89 (D) 6.19Answers: 1. (A) 2. (D) 3. (C) 4. (B) 5. (B) 6. (C


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Sales forecasts are an essential element in a business plan. A sales forecast sets thestandards for expenses, profit and growth. Forecasting is basically making an educatedguess as to how a company will do in the near future.

Difficulty:

Moderately Challenging

InstructionsThings You'll Need

Past reports on expenses, profits and growth Industry trend reports

1.How to Forecast Retail Sales

o 1Analyze past reports. If this is a new business, you will be making educated guessesbased on the trends in the retail industry. However, if you have been in business for atleast a quarter, you can prepare a more accurate forecast.

o 2Look for trends. Examine your past reports and look for trends in losses and profits. In

retail businesses, it is accurate to assume that trends will continue. Usually there areonly specific times of the year in which sales will dramatically increase or decrease inretail.

o 3Estimate. If you are preparing a forecast for an entire year, remember to account forholiday sales and your decline in sales after the holidays. Outside of those specifictimes, your forecast should be pretty much the same year round. So just make aneducated guess based on your previous information.

o 4Make your charts. Now that all the information has been computed, input it into a chartor an Excel document. In Excel you can put all of the reports into one document. Therewill be a page in the document for each of the months for the first year and then yearlyreports for the next three years.

o 5


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Add the charts to your business plan. Once the reports have all been finished and theyhave been printed out, add them into your business plan in the appropriate area.

Read more:How to Forecast Retail Sales | eHow.comhttp://www.ehow.com/how_2307554_forecast-

retail-sales.html#ixzz1ZKpjQmvK

How to Forecast Seasonal Sales WithMoving AveragesBy Josh Victor, eHow Contributorupdated June 07, 2011

Print this article

Related Searches: Sales Forecasts Predict Sales

Sales forecasts must take into account seasonaldiscrepancies.Sales forecasts do not exist in a vacuum. They must incorporate seasonal fluctuationsin the data that occur every year. For example, the Christmas shopping season is the

most active time for retail sales, while the summertime is the most active for homesales. Analysts can use moving averages to flatten out the fluctuations to provide amore accurate analysis.

Difficulty:
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Challenging

Instructions1.

o 1Examine all the data from the previous period, either the year, season, month, week orday. For this example, we will use retail sales and consider the change over differentseasons.

o 2Look at the data from the seasons from the previous year -- for example, the October,November, and December months from a year ago. Use the sales data as the baselinefor your moving average. Perhaps the sales per day were $1,000 for a store.

o 3Note the data from the other seasons of the year compared with their previous year.How much did the first quarter of year two grow over the first quarter of year one?Conduct the same analysis for the second and third quarters. This will give you a baseprojection for the final quarter of the year.

o 4Note the change in the average sales per day of the first three quarters of year two overyear one. If the average was 10 percent growth, project a 10 percent growth for thewinter quarter as well in terms of sales per day.

o 5Substitute each day of the fourth quarter of year one with the new figures. For example,if sales for the first day of October were $900 in year one and $990 in year two, replacethe value of the data from last year's number. This will create an updated blendedaverage for the fourth quarter. As you progress throughout the quarter, the movingaverage will change, with each new day replacing the previous year's data. By the endof the quarter you will have an average sale per day for the previous quarter. This canthen be used to forecast next year's sales.

Read more:How to Forecast Seasonal Sales With Moving Averages |

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How to Create a Retail Merchandising PlanBy Jonra Springs, eHow Contributorupdated April 22, 2011

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Effective retail merchandising attracts shoppers andgenerates sales.

Retail merchandising is the practice of acquiring stock that will generate sales andattractively displaying it to let customers find it easily and ecourage purchases.Managers and sales associates review past trends and consider current fads andmarket conditions in order to make sales forecasts for specific items. Clothing storemanagers near beaches, for example, order men's swimming trunks in varying leglengths and stock shorts for women to wear over bikini bottoms based on suchforecasts.

Difficulty:


Instructions1.

o 1Make sales forecasts for specific items instead of overall categories of items. Look atthe sales trends for walking shorts, casual shorts, running shorts, skater shorts and all
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classes of men's and women's shorts individually to decide what types to stock for agiven season. Simply looking at the sales for men's or women's shorts as a whole failsto address the specific items that will sell this season.

o 2Use the storefront and windows to attract your target clientle. Place posters andmannequins in apparel out front that define your merchandise. Light front windows withan appealing glow from the center mall aisle or sidewalk. Allow different employees tochange the storefront often to create a fresh prospective and constantly attract newcustomers.

o 3Place the merchandise strategically throughout the store. Use the front and centerlocation for your top selling items to ensure the majority of customers find this stockimmediately. Place related accessories near the items they are made to accompany,

such as ties near dress shirts and socks near the shoes. Put add-ons and impulse itemsnear the point of sale desk for sales people to make quick selling suggestions.

o 4Illuminate the store appropriately for the target market. Place spotlights on top sellingitems in any store. Use energetic lighting with colors and flashing or moving lights in astore selling casual clothing for young buyers to create excitement over the stock. Makethe lighting bright enough for mature customers without loud colors or flashing lights in astore that sells dress clothes and shoes.

o 5Play music that caters to your market. Use up-tempo pop music for the youngergeneration, and generation-specific pop music or elegant classical music for other adultmarkets.

o 6Give the store an appealing fragrance as part of your retail merchandising scheme. Usea cleaner with citrus ingredients or spray a gentle fragrance. Light scented candles onshelves safely out of reach of customers and away from flammable products. Avoidheavy odors such as incense or perfumes, which may drive away some customers.

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Exercises for Sales Forecasting With ExcelBy Sara Huter, eHow Contributor

updated January 25, 2011

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Excel is a cost-effective software tool for small businesses.Microsoft Excel is a software tool for forecasting and budgeting. Predicting orforecasting sales is important so that a business owner can determine whether hisproducts will be profitable after subtracting expenses from sales. Forecasting sales alsohelps in cash budgeting. Sales forecasting using Excel can help estimate sales growth,dependence on other products, seasonal sales and impact of discounts. Excel makesthe process easy and reliable.

1.Forecasting Sales Growth

o If you know that sales for a product will increase at a certain percentage, forecastingsales is a simple process of calculating the growth rate and total sales for each month.

Try this exercise: Last month's sales figure for coffee machine repair company "CoffeeBits" was 1,000 units. Sales are expected to grow 3 percent monthly. Use Excel tocalculate next month's sales.

In Excel, enter formulas without spaces or thousand separators (commas). Rememberto start a formula with an "=" sign. For example, input the next month's sales formula as"=1000*(1+0.03)" and press "Enter." The result should be "1030" or 1,030.
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2.Forecasting a Product's Relationship to Another Product

o When one product is dependent on another product's sales, forecasting sales is amatter of quantifying the relationship between the two products, and calculating salesbased on the forecasted sales of the related product.

Try this exercise: Assume that one of the products "Coffee Bits" sells is a specific partfor a high-end Italian espresso machine. Therefore, sales and repair orders for theItalian coffee machine will drive sales for one Coffee Bits product. For examplepurposes, assume that 500 Italian coffee machine units will be sold next month and thatCoffee Bits sells 1.1 parts on average for each coffee machine sold. Forecast the salesfor this part for the next month.

In Excel, input "=500*(1.1)" and press "Enter." The result should equal 550.

3.Forecasting Sales for an Expected Price Reduction

o

Companies often attempt to increase sales by reducing the price. Sometimes they hopeto clear their inventory to prepare for new products.

Try this exercise: Assume that the Italian espresso manufacturer has a new modelcoming out this year and wants to clear inventory by selling the espresso machines atsteep discounts. This will result in increased sales for Coffee Bits. For examplepurposes, assume that the discount will result in a 50 percent increase in sales from anormal level of a million units. Calculate sales due to the discount.

In Excel, input "=1000000*(1+0.50)" and press "Enter." The result should equal"1500000" or 1.5 million.

4.Forecasting Seasonal Saleso Many product sales follow a seasonal pattern. For example, flannel sheets tend to sell

well in the winter months, but not in the spring and summer. Similarly, some products,such as boxed chocolates, sell better during the holiday season as gifts.

Try this exercise: Assume that most of the Italian espresso machine sales occur duringthe holiday season. It would be reasonable to assume that the parts sold by Coffee Bitswill have their highest sales a month prior to the holiday season sales period for theespresso machines. For example purposes, assume that Coffee Bits expects to sell 12million units over the next twelve months and that 80 percent of these sales areexpected to happen in August, September and October. Calculate the sales in these

months.

In Excel, enter the following formula to calculate holiday season sales:"=12000000*0.80/3" and press "Enter." The result should be "3200000" or 3.2 million.

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Optimization Tools for Sales ForecastingBy Maria Woehr, eHow Contributorupdated January 26, 2011

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Optimization tools for sales forcastingThere are various optimization tools to use for sales forecasting. The tools employstatistical and modeling techniques to help forecast sales of future events. Mostcommonly, these tools are known as customer relationship management (CRM) tools.There are two types of forecasting methods that these tools use: causal and noncausal.Noncausal forecasting uses historical data to develop future predictions. The casualmethod predicts sales based upon current factors such as pricing and promotions.

1.Finding the Right Sales Optimization Tool

o The goals of CRM tools are to gain new clients through leads and to retain old ones,

while also cutting down on business costs and forecasting future sales. Companiessuch as Salesforce.com and Oracle offer software that can help break down yourcompany's performance including customer transactions and pending invoices. Thesoftware will also generate predictions based upon history, market conditions and goalsthat your company have.

Information You Need for a Sales Forecast
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o To get a precise sales forecast using sales forecast optimization tools, you will need theright information on hand. Make sure you have your dollar sales volume for the pastseveral years and a list of all the external and internal factors that could impact yourbusiness. The more thorough the information, the more precise your sales forecast willbe. Some information that sales optimization tools will need is the seasonality of the

business, direct and indirect competition, consumer earnings and productivity changes.

Exponential Smoothing

o Sales forecasting optimization tools generally use a forecasting technique calledexponential smoothing to predict business. Exponential smoothing compares a previousforecast to actual results. The result will be an error figure that can be factored in as abase in current and future forecasts.

Trending

o Sales optimization software will identify trends to indicate where there are missed

opportunities. Trends are important forecasting tools for planning and preparation. Byidentifying trends, you can identify the highest selling months to make sure you haveenough inventory on hand and that sales efforts are strong enough.

Accounting Spreadsheets

o Many sales forecasting programs use some form of Microsoft Excel or an accountingspreadsheet application that helps organize sales history data for forecasting, customerlists and products. These applications also generate charts and graphs so thisinformation is easier to understand.

Analyticso Many optimization tools for sales forecasting have exceptional analytics that can

monitor -- in real time -- almost all aspects of your business, such as customertransactions, invoices, sales and marketing actions and forecasts. Analytics areimportant in understanding your customer base and what they get out of your service.Analytics can identify customer satisfaction levels, response times and agentperformance. By targeting exactly what customers need, you will be able to providethem with the best service and increase sales.

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How to Forecast SalesBy an eHow Contributor

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Related Searches: Long Range Forecast Business Sales

Sales are the most important aspect of any business. Forecasting sales is both ascience and an art. The ability to accurately forecast sales will substantially increase theprofitability of your business, as there will be minimal waste, obsolete inventory or costs

related to over-staffing.

Difficulty:

Moderate

Instructions1.

o 1Review the last six months of sales figures on a daily, weekly, monthly and quarterlybasis. How do they vary day to day or week to week. Is there a pattern to the activity?

o 2Inspect the competition. Are their locations busy in comparison to yours, slower or aboutthe same? Read industry focused magazines, newsletters. Attend trade shows andconferences. These activities will give you a sense of what is happening in the industryand the level of activity.

o 3Calculate the percentage increase or decrease of sales from month to month. This is atwo step calculation: Take current month sales, subtract last month sales. Divide thisvalue by the last month sales. This value is the percentage increase or decrease.

o 4Calculate the percentage increase or decrease value for the last 6 months. Comparethe values and determine if there was a specific activity that related directly to the
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changes. An example would be a highly advertised sale, marketing or advertisingcampaign.

o 5Remove the months where the changes can be related to a specific activity andcalculate the average change. The average is found by adding up all the values anddividing by the number of values. This is your base sales percentage change.

o 6Take the dollar value of sales for last month and multiply by the average percentagesales change. This is a conservative sales forecast.

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How to Forecast Sales with ExcelBy an eHow Contributor

updated April 09, 2011

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Forecast Sales with Excel

Forecasting is more of a science than an art with advent of computer programs thathave the ability to accurately predict future event in case sales. One popular programthat is very useful in sale forecasting is Microsoft Excel. Excel is powerful spreadsheet

software that allows users to forecast future events based on a detailed statisticalanalysis.

Difficulty:


Instructions

Things You'll Need Microsoft Excel Computer1.

o 1Make sure the data is complete, correct and ordered. There needs to be enoughhistorical sales data to accurately perform an analysis, typically seven to ten timeperiods; the longer that forecast timeline the more accurate the forecast. The data mustbe ordered from oldest to newest. If there is any missing data for a time period, thenestimate the number as accurately as possible. the time periods need to be uniform; for

example compare months to months or year to years.

o 2Enter the data in an excel spreadsheet. Title the columns appropriately; for exampleone column entitled years the other entitled sales. Highlight the data to be included forthe purposes of the forecast. From the main menu choose "Insert". From the insert
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menu select "Chart". In the chart dialogue box click the standard types tab. Locate thechart option and click on "Line". Choose "Finish".

o 3

Determine the trendline. Click on the chart area that was just created. The chart menushould appear. From that menu select "Add trendline." The trendline dialogue should bepresent. Choose the type tab in trendline dialogue box. Under the type tab click onlinear. Now click the options tab. Choose the options tab and in the forward box type thenumber of years to forecast. Make sure the display R-square value option is checked.Click "OK".

o 4Know what the R-squared value means. The closer the R-squared value is to one, themore accurate the data set is purported to be. The types of trendlines may need to bechanged to R-squared result that is more accurate.

o 5Change a trendline to verify the most accurate type was utilized. First select the chart.From the format menu choose "selected trendline." Change the type of trendline tologarithmic. Repeat the previous steps to change the type to a moving averagetrendline. Trying all three trandlines give the users a better idea of which one is mostaccurate based a R-squared result

Read more:How to Forecast Sales with Excel |eHow.comhttp://www.ehow.com/how_2078464_forecast-sales-excel.html#ixzz1ZKt8G0OL
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