important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and

One of the most difficult tasks a new prospective entrepreneur faces is the construction of a Sales Model. Many books devoted to instruction for writing a business plan devote little or no attention to this vital exercise. The knowledge needed to assemble a quantified, qualified and clearly narrated Sales Model is essential to convey the scope and validity of an opportunity.

The most elemental data point required to commence assembling a strong sales proposition is the Cost of Goods (COG). Knowing with absolute certainty the all-inclusive COG is the foundation number necessary to build the Sales Model and ultimately a strong business plan. Guessing, estimating or hoping that the number you slot into your plan is accurate will lead to a solid dead end, and very quickly.

The Sales Model, just like the completed business plan, is written based on a series of assumptions. These assumptions are then qualified (given historical and current market perspective), quantified (COG and sales goals are utilized to extrapolate a believable sales universe is available for the product) and narrated (explanation is provided to support the basis on which the assumptions were based). The Sales Model is but one section of a business plan: however, it is the heart and soul of the following financial section so crucial to investors.

I see so many business plans that scream “this is guesswork”! First year sales are projected at a nice, clean round number (so often $1,000,000). Growth ramps up too quickly, and to unbelievable numbers. The justifications for these assumptions are based on mirrors and hope.

Let us make a few assumptions here to show a basic example of a method to build a believable Sales Model. We will assume that research has proven that our COG (remember, including packaging, shipper, master shipper and freight, customs and duties, if any) is $1.00 per unit for our widget.

Our next assumption to decide is the wholesale selling price: if the item is to be sold through traditional retail sales distribution channels. The nearest competition we can find on the market is selling in mass-market distribution stores (Wal Mart, K-Mart, etc.) for an average of $6.49. Assuming a 37.5% markup, the competitive item is being sold at wholesale for $4.06 (round to $4.00). Assuming that our item has features and benefits that would be perceived as similar to the competition $4.00 is an acceptable wholesale. A 25% COG is well within industry parameters (based on historical norms).

We now have our COG, a wholesale sales price and a pretty good picture of the retail price that will enable the item to be competitive and still offer excellent profit potential. The easy part is over. Here is where things get tricky.

Our item will be sold in the hardware section of stores. After studying industry specific data and researching the hardware product category we determine that we will have over 135,000 potential store placements if 100% of the American market could be penetrated. This is hard data. Now we must leave science and become artful.

How many of these 135,000 hardware outlets can we believably project to carry our widget in year one of operations, year two, year three, etc? Making every effort to build our plan on solid assumptions, we are going to be conservative. During the first year after operations commence, we will open 2% of our potential universe. Year two will see the widget’s distribution add another 2.5% of the hardware outlets and year three we will gain another 3.5%. After three years we will conservatively projected 8% of the potential distribution points for a hardware widget.

Another point to consider when building out a distribution model, not all of the stores will be shipped at one point in any yearly cycle. It is important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and

nt market perspective), quantified (COG and sales goals are utilized to extrapolate a believable sales universe is available for the product) and narrated (explanation is provided to support the basis on which the assumptions were based). The Sales Model is but one section of a business plan: however, it is the heart and soul of the following financial section so crucial to investors.

I see so many business plans that scream “this is guesswork”! First year sales are projected at a nice, clean round number (so often $1,000,000). Growth ramps up too quickly, and to unbelievable numbers. The justifications for these assumptions are based on mirrors and hope.

Let us make a few assumptions here to show a basic example of a method to build a believable Sales Model. We will assume that research has proven that our COG (remember, including packaging, shipper, master shipper and freight, customs and duties, if any) is $1.00 per unit for our widget.

Our next assumption to decide is the wholesale selling price: if the item is to be sold through traditional retail sales distribution channels. The nearest competition we can find on the market is selling in mass-market distribution stores (Wal Mart, K-Mart, etc.) for an average of $6.49. Assuming a 37.5% markup, the competitive item is being sold at wholesale for $4.06 (round to $4.00). Assuming that our item has features and benefits that would be perceived as similar to the competition $4.00 is an acceptable wholesale. A 25% COG is well within industry parameters (based on historical norms).

We now have our COG, a wholesale sales price and a pretty good picture of the retail price that will enable the item to be competitive and still offer excellent profit potential. The easy part is over. Here is where things get tricky.

Our item will be sold in the hardware section of stores. After studying industry specific data and researching the hardware product category we determine that we will have over 135,000 potential store placements if 100% of the American market could be penetrated. This is hard data. Now we must leave science and become artful.

How many of these 135,000 hardware outlets can we believably project to carry our widget in year one of operations, year two, year three, etc? Making every effort to build our plan on solid assumptions, we are going to be conservative. During the first year after operations commence, we will open 2% of our potential universe. Year two will see the widget’s distribution add another 2.5% of the hardware outlets and year three we will gain another 3.5%. After three years we will conservatively projected 8% of the potential distribution points for a hardware widget.

Another point to consider when building out a distribution model, not all of the stores will be shipped at one point in any yearly cycle. It is important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and

widget.

Our next assumption to decide is the wholesale selling price: if the item is to be sold through traditional retail sales distribution channels. The nearest competition we can find on the market is selling in mass-market distribution stores (Wal Mart, K-Mart, etc.) for an average of $6.49. Assuming a 37.5% markup, the competitive item is being sold at wholesale for $4.06 (round to $4.00). Assuming that our item has features and benefits that would be perceived as similar to the competition $4.00 is an acceptable wholesale. A 25% COG is well within industry parameters (based on historical norms).

We now have our COG, a wholesale sales price and a pretty good picture of the retail price that will enable the item to be competitive and still offer excellent profit potential. The easy part is over. Here is where things get tricky.

Our item will be sold in the hardware section of stores. After studying industry specific data and researching the hardware product category we determine that we will have over 135,000 potential store placements if 100% of the American market could be penetrated. This is hard data. Now we must leave science and become artful.

How many of these 135,000 hardware outlets can we believably project to carry our widget in year one of operations, year two, year three, etc? Making every effort to build our plan on solid assumptions, we are going to be conservative. During the first year after operations commence, we will open 2% of our potential universe. Year two will see the widget’s distribution add another 2.5% of the hardware outlets and year three we will gain another 3.5%. After three years we will conservatively projected 8% of the potential distribution points for a hardware widget.

Another point to consider when building out a distribution model, not all of the stores will be shipped at one point in any yearly cycle. It is important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and

and researching the hardware product category we determine that we will have over 135,000 potential store placements if 100% of the American market could be penetrated. This is hard data. Now we must leave science and become artful.

How many of these 135,000 hardware outlets can we believably project to carry our widget in year one of operations, year two, year three, etc? Making every effort to build our plan on solid assumptions, we are going to be conservative. During the first year after operations commence, we will open 2% of our potential universe. Year two will see the widget’s distribution add another 2.5% of the hardware outlets and year three we will gain another 3.5%. After three years we will conservatively projected 8% of the potential distribution points for a hardware widget.

Another point to consider when building out a distribution model, not all of the stores will be shipped at one point in any yearly cycle. It is important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and

important to have a line at the very top of the cash flow section in the Financials that details how many stores you project to open each month. Allow for seasonal variations. Is the widget a summer item, a Holiday item? This will determine peak shipping months.

The next assumption is sell-in levels. How many units of the widget will a store typically carry in inventory? Competition averages 18 units per store. Is the widget going to be promoted, placed on end cap display, given a floor stand or presented in a featured way? These are questions that must be qualified, quantified and narrated to justify the sell-in assumption.

If the sell-in assumption is 18 units per store, then our next task is creating a retail sales turnover. Again, if it is verifiable that the competitive leader turns goods an average of eight times per year, we will be conservative. An inventory turn of six times during year one, seven times during year two and eight times in year three is easily defensible. This will, of course, be average out as stores come on line during monthly new door openings.

As we are not completing a proper spreadsheet here, reflecting 12 month flows in our example, let us assume that year one sales are for stores that have been carrying the product for a full 12 months. Here is where our Sales Model construction for year one has brought us.

Doors Opened 2700 (2% of 135,000)

Sell-in per Door 18 units

Wholesale Price 4.00

Inventory Turnover 6 Turns

Sales Year 1 = $1,166,400

Perform the same calculations on the assumptions we have created for years two and three and the results are $3,061,800 and $6,220,800 respectively.

The Sales Model we have created for our mythological widget is built on assumptions that we have vetted, checked against historical norms and properly support our theorem with logic and a conservative, believable rationale. The numbers work together and tell a story of strong sales traction with a lot of distribution to be gained (after year three we have 92% of the market still not serviced).

We now have the top line sales number under which we can project a financial picture that will excite potential investors, licensees and partners. They will know that we are serious, professional and knowledgeable. This presentation of a comprehensive plan supported by reality based assumptions is lacking in so many business plans I read.

By definition, a business plan is based on assumptions, and lots of things happen to distort assumptions. Murphy named a law after himself for a reason. Stuff happens! Nevertheless, business plans that achieve successful results are built on assumptions that mitigate the potential for ugly surprises. A business plan without a well-constructed Sales Model has no chance of overcoming the natural cynicism inherent in investors and decision-makers.