Minding Your Own Business; How’s Your Shop Doing?

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Last month in this space I suggested a simple system for tracking your financial results with the goals of having better control and being able to react to surprises. If you use it for, say, six months, you are going to have some good information that will have helped you manage your shop. The next step, which this article addresses, is to use the information collected over a period of time to help you answer the fundamental question “How am I doing and what can I do better?”

The National Ski and Snowboard Retailers Association (NSSRA) can help you answer that question with their biannual cost of doing business financial survey. 64 shops responded to the survey for the 1995-96 season. NSSRA segmented the shops according to their revenues levels and calculated key performance measures so that shops can compare their performance to the others producing similar revenue.
 
 Some of the gross data was presented in last month’s Transworld Snowboarding Business. Below, selected information from the survey is presented in a different format and how you can interpret it discussed.   The table below highlights some data across the complete revenue range that I think is particularly interesting. It’s instructive to look at how you’re doing compared to shops your size, but it can be equally interesting to see how things may change (or not change) with revenue growth.
 
 
 
 
 
 
Total Company Revenue:
 
 
 
 
 
 
Under
$500,000 to
$1 to $2
Over
 
 
 
 
 
$500,000
$1 Million
Million
$2 Million
Income Statement (%of Total Revenues)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Net Sales of Merchandise
 
 
92.9%
94.5%
92.6%
95.4%
Operating Margin
 
 
 
46.9%
41.0%
43.7%
40.0%
Total Payroll (including tax & benefits)
 
22.0%
18.0%
19.2%
18.7%
Occupancy Expenses
 
 
7.4%
5.8%
5.8%
7.8%
Other Operating Expenses
 
 
14.4%
11.3%
12.4%
12.0%
Net Income Before Tax
 
 
3.2%
5.7%
6.4%
1.1%
 
 
 
 
 
 
 
 
 
Key Performance Measures
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Owner’s Compensation & Profits to Revenue
 
12.6%
10.3%
9.9%
5.4%
Total Square Feet Per Store
 
 
3,300
4,800
5,700
5,571
Selling Square Feet Per Store
 
 
1,800
3,200
3,500
4,333
Total Revenue Per Selling Square Foot
 
$243
$258
$368
$230
Total Revenues Per Total Equivalent Employee
$95,219
$80,297
$123,811
$115,900
 
 
 
 
 
 
 
 
 
Median Revenue Per Company
 
 
$460,816
$650,000
$1,400,000
$4,500,000
 
Before you start interpreting this data and applying it to your situation, remember that every statistical analysis has flaws. Unless you understand how it was collected, and compiled, you can reach bad conclusions using it.
  
Tom Doyle, President of NSSRA, reminded me that it tends to be the more sophisticated and better organized shops that return the survey, so the results may not be representative of “typical” shops. The survey also includes balance sheet data, but I’ve purposely excluded it from this discussion. In seasonal industries, a good company can have a strong balance sheet in January and a lousy one in July. Unless all the balance sheets are as of the same date, the survey results can be meaningless. Since we don’t know what those dates are, I’d take the balance sheet data with a grain of salt if you get the survey for your shop.
 
Don’t get too focused on comparing percentages. The absolute numbers do matter. An 85% gross margin won’t save the day if your total sales are $75,000.
 
According to Tom, the sample size is large enough to be statistically valid even when the responding shops are divided among the four revenue categories. But if you were to select different revenue ranges, you might see dramatically different results. I also get nervous about the sample size when, for example, they divide the respondents in one revenue category into the lower 25%, the middle 50% and the upper 25%. At that point, each of those segments may have so few data points that one unusual value dramatically changes the result. About all that can be done to remedy this problem is to get more of you to participate in the survey. 
 
Even though the word snowboard has been added to the association’s name, only about six percent of revenue of the responding companies is from snowboarding. Don’t stop reading. As far as I know, we don’t have any better information to work with, and if half the revenue were from snowboarding, I don’t think the calculations would turn out to be much different. 
 
So now, keeping these possible shortcomings in mind, you can go into this analysis with your eyes open. First, look at what happens to the various indicators as revenue grows. As median revenue grows from $460,816 to $650,00 (41%), owner’s compensation and profits (OCP) grow only from $58,063 to $66,950 (15.3%). From a strict financial point of view, the additional effort and risk may not be worth the additional income to the owner. But going one growth step further, median revenue growth from $650,000 to $1,400,000 (115%) yields a comparable increase in OCP of 107% to $138,600.
 
 
If we take the last step up, sales increase by 221%, but OCP is up only 75%. This isn’t surprising. You can see that most of the expense reductions take place between $500,000 and $2,000,000 in revenue. Payroll, occupancy and other operating expenses each drops a couple of points.   Operating margins are lowest for the companies over $2 million in sales.
 
A strict financial analysis then, suggests that an appropriate revenue goal for a shop is somewhere between $1 and $2 million, because that’s where you seem to get the most operating efficiencies and to maximize your pretax income as a percent of revenue. Too small an operation has to spend too high a percentage of its revenues on fixed costs. Too large and your profitability drop because you do not hold your margins and your revenue per selling square foot declines. Larger companies typically are less riskier than smaller ones and can attract capital with less trouble and at a lower cost. Perhaps a lower return on incremental sales is justified by reduced risk to the owner/investor.
 
If one use of this data is to plan your financial future, another is to manage your present business. Tom Doyle relayed a couple of instances in which his members used it to save some money.
 
In one case, a shop used it to negotiate a better deal on its lease. They showed the survey data to the landlord and successfully argued that they couldn’t afford to pay a higher percent of revenue for rent than their competitors. In another case, an owner noted that his insurance expense appeared very high as a percentage of his revenue. A few phone calls confirmed that there were better deals available.
 
Recognize that just because your shop is above or below a particular indicator doesn’t means that you have a problem or are doing exceptionally well. Evaluation of financial indicators is a dynamic process; each indicators affects others. Your goal is to understand why the variance exists and either be comfortable with it or make some changes.
 
Get a copy of this study from NSSRA. Check out the methodology so you understand what they are doing. On a piece of paper, write down as few or as many of the statistics for shops your size as you want. In the next column, calculate the numbers for your shop. In the next column record the positive or negative variance.
 
Where the absolute numbers or the percentage variance is very small (less than 5% either way?), ignore it. Where the variance is significant, write down what you think is the explanation in the next column. Note both positive and negative variances. Spending too little on something can be as bad as spending too much.
 
Where you don’t have an explanation, take the time to find one. The survey indicates that the cost of insurance for a company doing between $500,000 and $1,000,000 is 1.2% of revenue. It also says the middle range (the 25% on each side of the median) is from 0.4% to 1.7%. So maybe if your percentage is 3.2 you want to call your agent and cancel the rider that covers you against the invasion of the body snatchers. On the other hand, maybe you’re strategically situated on the hills outside of Sarajevo, and no matter what the percentage is, you think a little more business interruption insurance might be just the ticket.
 
This isn’t about comparing percentages. The term “insurance” covers a lot of things (never buy it when you’re playing blackjack) and just because your expense as a percent of revenues is different from what some study finds doesn’t mean you should change. Maintaining a higher gross margin, for example, may require that you spend more on advertising.
 
This survey is a screening mechanism that can highlight, without much effort, areas where improvement in your shop’s financial performance might be possible. It doesn’t provide black and white answers, but can be a valuable guide. Use it as a tool to help you think about your business, but temper any conclusions you reach using it with knowledge of your special circumstances.

 

 

Who Are Your Customers? And Why Are They Buying From You?

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As a snowboard retailer, you have a position in your market. You own it, and it’s yours to loose. The best way to loose it is to forget who your customers are and what they want.

The other day I was in one of these warehouse stores. There was a snowboard with bindings for, I think, $299.00. The board had a full metal edge, the inserts and finish looked fine and the bindings, while nothing to write home about, seemed perfectly functional. The description said it had a full wood core, and most of the other statements about it could have been out of an ad for a leading brand. The brand? At about the point where the number of brands passed 150 the part of my brain that could remember them all atrophied.
 
It’s enough to strike terror into the heart of a shop owner. If you end up competing on price…. Well, you can’t. 
 
But there’s hope. Recently, a competing publication (I don’t think they’ll let me say Transworld Snowboard Business here) did a survey of 100 snowboard shops. It indicated that brand name and the sales person were the two most important factors determining a purchase. On a local level, how can you get that kind of information; the kind you can act on?
 
Rush to your local library or town hall, or log onto the Internet. Dig up the census data for your county or SMSA (standard metropolitan statistical area). What are the incomes levels? Average age? Population density? Where are most of the people you believe are your likely customers?
 
Are they your customers? Ask questions of every customer that comes in your store whether they buy or not. Get their address, school they attend if appropriate, where they work, what mountains they ride, whatever will help you figure out what they want. This doesn’t mean locking them in a room until they fill in a three page questionnaire. It can be part of an informal conversation between the sales person and customer. The trick is getting it consistently written down immediately after the conversation.
 
One side benefit is that showing that kind of personal interest in a potential customer may actually increase your chance to make a sale. Listen to your customer. Easier said than done.
 
Get a map of the area and tape it to the wall. Put a pin in to show the home and/or job and/or school of each person. Is there a pattern to where your customers are coming from? Is it what you thought it was? Does this tell you anything about how to reach them and where you should be advertising?
 
Pay for gas, food and list tickets for a couple of shop employees on the condition that they come back with information on 50 snowboarders. What kind of riding do they do, how often, where did they buy their gear, and why? Offer to share your data with the mountain if they’ll do the same with you.
 
It isn’t enough to collect this information on slips of paper or three by five cards, read through it, think to yourself, “Isn’t that interesting” and then forget it. Organize it to see the patterns. On a computer, or on some big pieces of paper taped to a wall. The more data you collect and the more ways you look at it, the more you learn. The magic of being this rigorous is that some of your cherished and unquestioned assumptions about who your customers are and why they buy will turn out to be a bunch of fatuous blather (i.e., wrong).
 
Assuming that you go through the procedure I’ve described (or a similar one you believe is more appropriate to your market) what’s in it for you? Now you have some harder data on what kind of people are buying from you, what they are buying and why. Tape some more big pieces of paper on the wall with information about your inventory at different times of the year. Given the kind of people buying from you and their reason for buying at your store, should your product mix be different? Are you carrying too much of some items and not enough of another?
 
How many dollars is it worth to you to have the right inventory at the right time and have as little as possible left over at the end of the year?
 
If you are a little better able to anticipate your customers’ needs, what kind of return and add on sales does that generate? The process is cumulative and never ending. The better you do, the better you do.
 
Scurry to the book store and buy a paperback called Customers For Life, by Carl Sewell. Mr. Sewell is the most successful luxury car dealer in the country. The book is about how he gets and keeps his customers. Before you laugh about using the ideas of a car dealer in a shop that sells snowboards, you might take a look at the consolidation going on in that industry. Price competition is intense, the number of dealers has declined rapidly, the survivors are tending to be much larger, and the customers aren’t as willing to be convinced that there’s a significant difference between brands . Recognize any trends you’re worried about?
 
Your shop is unique. My questions and sources of information may not be the right ones for you, but the concept is right; whether you’re selling cars or snowboards. There’s no more important information than who are your customers and why are they buying from you. In the snowboard industry’s competitive environment, you have to take the time to find out.