EB5 Investors Magazine Volume 2 Issue 1 | Page 19

Market research - The final , and often most expensive , route is market research . Sometimes , this can be done through verifiable 3rd party research , such as industry trade publications ( i . e . STR Global for hotel data or RS Means for construction data ) or databases , like Factiva and FirstResearch . However , these sources may lack the specificity that you require .
In this case , you might consider hiring a market research firm to do a study , especially for larger ventures into new or unpredictable markets . The most important feature of market research is getting feedback directly from potential customers . So , if you have a question about your financials , hire a market research firm to find customers in your target market and ask them that question .
USCIS is increasingly issuing requests for further evidence ( RFEs ) for 3rd party studies specifically , further evidencing the need for quality , well-researched , and written support for business plan assumptions .
Three common sense guidelines Check for reasonableness - Do a gut check of the final outputs of your model ( analyzing sales , margins , EBITDA , etc .) to see if they are out of place . You may want to alter your assumptions compared to your competition if your business has a more extreme market position , such as a loss leader or a premium brand . For example , if you want to be a premium brand , do not just assume a higher selling price , but also consider lower selling volumes or higher expense levels .
Stay conservative - One important practice of financial modeling is conservatism ; when in doubt , you should be conservative with your assumptions in order to avoid bias and prevent extremely negative results . This can include choosing a lower selling price , a lower selling volume , or higher research and development expenses .
Change them ! - Our final recommendation is that you update and change your assumptions as you obtain more information . Do not be afraid to admit that your initial projections were wrong and to adopt a more realistic view when you have new insights .
Two practical examples Revenue example — pricing Revenue is , in its most basic form , price multiplied by quantity . This means that your pricing is one of the most important assumptions on the revenue side of your model . For example , if your regional center is building a hotel , and your model calls for $ 175 per night as your base rate , but the customers are only willing to pay $ 135 per night :
• When you go to market , you will have to lower the price to $ 135 per night . This represents a 23 percent price reduction and will negatively impact your margins , and could even mean the difference between profitability and failure .
• OR You might still book stays at your hotel , but at a lower occupancy than you initially projected . If your model assumes that you maintain 75 percent occupancy , and you end up at 50 percent , your financials could become unsustainable .
You should conduct intensive primary and secondary research , perhaps using a third party , to validate the nightly rate and projected occupancy that you use in your model .
Cost example — staffing
For most companies , payroll is the largest single expense . Accurate data on salaries is readily available through many public sources . However , understanding and projecting an effective staffing model is not a straightforward task . Again , using the example of a regional center building a hotel , if you assume one position will handle both marketing and sales , but you end up needing two separate positions :
• You will have more payroll expenses than you projected , which directly cuts into your margins . This is problematic , especially when considering expensive benefit packages and continually rising healthcare costs .
• OR Your team will be under-staffed and you will not be able to drive the projected revenue . If you do not hire the second person , the additional expense will not show up in the SG & A line on the income statement , but this mistaken assumption will negatively affect top-line sales and compromise your model in the long run .
For the most part , good information on staffing models comes from industry insiders . You should consult the relevant trade organization or make sure that you have an industry expert on your team . The bottom line here is : do not make guesses or wing it . Use benchmarks or historical data from an existing , profitable operation .
No model or business plan is perfect , but you can dramatically increase your overall accuracy by doing the detailed work of putting accurate data into your model . This is good for your business , and for your regional center and investor EB-5 applications . When developing assumptions , you should try to incorporate historical data , the opinions of industry experts , and market research . Then , you should supplement these sources by being conservative , checking final outputs for reasonableness , and updating your assumptions when appropriate . Assumptions are the fuel for your financial model and business plan , so if you want to go the distance , don ’ t skimp — use the highest octane you can .

Soyini Coke is managing principal at Annona Enterprises , a strategic advisory firm that provides business planning and investment support for companies with up to $ 100 million in annual revenues . Most recently , Soyini has finished The Perfect Business Plan : A Step-by-Step guide , which captures the methodology she has successfully used with her clients . She began her career at McKinsey after graduating cum laude from Harvard University in 1998 with a Bachelor of Arts in Applied Mathematics and Economics .
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