Factors Affecting Feasibility Study Pricing

Large consulting firms prefer to work with Fortune 1000 companies with tens of thousands of employees, multi-billion dollar revenues, and multi-million dollar consulting budgets. Their clients — large multi-national corporations and governmental organizations — are used to hiring consulting firms, and generally have a pretty good idea of what to expect from consultants. They are experienced at negotiating contract terms, and have deep pockets and top attorneys to protect them in the event things go wrong.

Our firm, Ground Floor Partners, works at the other end of the spectrum — small and mid-size businesses and non-profit organizations with perhaps dozens of employees, revenues generally below $10 million, and much smaller project budgets. Our clients generally have little or no experience with consultants and often have unrealistic expectations for consulting project pricing and outcomes. It is not that unusual for us to with business owners who want $30,000 of work completed for $3,000. They want customized solutions that are tailored precisely to their needs, but they want to pay commodity pricing. It just doesn’t work.

Pricing misconceptions are particularly common when it comes to feasibility studies. The purpose of this note is to outline some of the most important factors involved in feasibility study pricing, and help business owners set more realistic expectations.

Volume vs Quality — Many of our competitors drown their clients in data. They want to impress their clients by the huge volume of numbers, charts and figures, while ignoring problems with quality. The reality is that nobody can accurately predict whether or not a particular technology, business concept, revenue model, or marketing approach will gain traction in the marketplace. They can identify and assess strengths, weaknesses, opportunities and threats (SWOT analysis). They can look at political, economic, social, technological, legal and environmental factors (PESTLE analysis). They can look at the spectrum and nature of competitors in the current marketplace, and they can compare projected financials with historical financials from similar or previous projects. But all of these things require some analysis and thought. Data is clearly necessary, but it is not sufficient.

Scope — Recently a friend of mine asked me to take a look at a report analyzing a proposed single payer healthcare plan for the state of California. The report was very professional and seemed quite thorough, at first glance. But after a little more reading, I realized it had completely ignored some of the most important and critical areas involved in healthcare. The report focused on direct costs attributable to healthcare coverage, such as emergency room visits, hospital stays, physician visits, and medical testing and evaluations. But it completely ignored “indirect” costs from factors such as productivity losses due to missed workdays by sick parents or increased crime rates from people who have treatable mental illnesses but are not receiving counseling or medication because they do not have adequate healthcare insurance. The analysis also ignored a range of alternative possible payment models, and instead focused on only two: sales taxes and “growth receipt taxes”. The point is not to pick on this particular study, but rather to point out that a better approach would have been to expand the scope of the study by analyzing a wider range of factors and considering more payment options.

Industry and Type — While all feasibility studies have elements in common, there is no such thing as a generic feasibility study: every project is different. A feasibility study for an innovative new business model is very different from a feasibility study for a new instance of a standard business such as a hotel, restaurant, bar or salon.

Complexity and Scale — A healthcare facility is highly regulated (possibly at the federal, state and local level), whereas a hair salon is loosely regulated. Generally, the more regulated the industry, the more complex the analysis and the more expensive the study. Size is another factor: a 2,000 square foot hair salon is usually much less complicated than a 20,000 square foot, mid-priced motel. Similarly a 100,000 square foot assisted living facility with memory care and other services and facilities is even more complicated. Complexity usually increases with size, degree of regulation, price, level of competition, and novelty (new and innovative businesses are often more challenging to analyze than businesses in older, more established industries).

Constraints — Every business has constraints — funding for example. Well-funded start-ups tend to survive, underfunded start-ups tend to fail. Most highly scalable, innovative businesses are funded with equity, whereas more traditional business such as restaurants often have a greater proportion of debt financing. Generally the more predictable the business, the more likely it is that banks will get involved, so the higher the proportion of debt financing. But debt financing is usually less flexible than equity funding.  Bankers want to make sure they get their money back plus a small return. Equity investors, on the other hand, hope to make large returns on their capital, and tend to be more forgiving, at least in the short term. A 20% revenue shortfall is a rounding error for a tech business, but it can mean the difference between success and failure for a restaurant. A restaurant feasibility study requires extremely accurate data, whereas a tech business feasibility study doesn’t.

Market Factors — Every business operates within one or more external markets. For example, a hotel competes with other hotels, but it can also compete with nearby B&B’s, clubs and resorts, home and cottage rental agencies, and even Airbnb. A thorough market feasibility study will include data and analysis on all of these potential competitors, as well as broad market trends (Is the US economy growing, shrinking or stable? Is the regional economy adding jobs or losing jobs? Are other complementary businesses (such as restaurants) doing well in this area, or are they shedding jobs and closing up shop?)

Transparency and Availability of Data — While some industries are flooded with data, others are starved for data. Most healthcare and education businesses fall in the former camp, whereas financial and professional services tend to fall in the latter. Of course there are exceptions, but the underlying explanation is that healthcare and education are highly regulated and receive large amounts of public funding. Healthcare and education businesses must disclose massive amounts of information if they want to stay in business. They also have large numbers of workers in trade unions which monitor them. Financial and professional services firms are also regulated, but receive far less funding from taxpayers. They have far fewer, better compensated workers, who are essentially incentivized to keep quiet. Some businesses and industries are more open and transparent than others. Transparency, or lack thereof, can make a big difference in how easy it is to get accurate, reliable information.

Options — How many and which options are being considered? For example, location is a critical factor for businesses such as hotels, restaurants, resorts, salons, museums, and many others. The right location can make such a business, but the wrong location can break it. A thorough feasibility study will identify criteria for determining whether or not a particular location is acceptable or not, and will also include rankings to determine whether acceptable locations are “good”, “better” or “best”. Common criteria include demographic information (age, wealth, income, etc.), road and traffic information (How many people drive by this particular location each day? Are there convenient entrances and exits nearby? Etc.)

The bottom line is that any feasibility study worth the paper it is printed on requires careful market research and analysis. A wide range of factors should be considered, and “simple” projects often have unexpected levels of complexity. Pricing involves many factors, such as regulations (highly regulated or unregulated), competition (high or low), market trends (positive or negative), and project scope (narrow or broad). As a percentage of the underlying project budget, a good rule of thumb is the larger the project, the lower the price of the feasibility study. For example, a feasibility study for a $250,000 nail salon might cost $6,000 (2.2%), whereas a feasibility study for a $50 million real estate development might cost $100,000 (0.2%).  Note that these are “typical” numbers; actual prices could be above or below these estimates. Every project has unique features, and a cookie cutter approach rarely works.