Validating Business Case Assumptions

Objective

This article describes methodologies for validating business case assumptions for entrepreneurs seeking venture capital financing and for product managers requesting internal funding. To avoid confirmation bias, it is helpful to think of “validating” as “de-risking.”

 

Validating and/or de-risking business case assumptions, or at least having a plan for doing so, enhances credibility and enables informed decision-making. Assumptions are risky and uncertain.

 

The article starts with best practices for business case assumptions and for prioritizing which assumptions to validate and finishes with validation methodologies.
 

 

Business Case Assumption Best Practices

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• To help organize your thoughts and develop a plan, create a visual dashboard.

  • List each assumption and its data source and rationale.

  • Assess each assumption’s probability of being true (high/medium/low is a good start), and why it is risky.

  • Describe any efforts that have gone into de-risking each assumption.

  • Identify the smallest test you can run to de-risk each assumption and specify upfront each test’s success metrics.
     

• Be conservative. When market size, revenue and other metrics look good despite conservative assumptions, it adds credibility. You need a large market and revenue opportunity to justify a project, but aggressive assumptions create skepticism and can lead to unrealistic expectations.
   

• Simpler is better, complex assumptions do not scale. Too many layers of assumptions lead to over-analyzing unknowns.
   

• Leverage industry benchmarks and market trends. If the project is an upgrade or extension, compile historical data for the last 3-5 years. Business case deviations from context need a justifiable, credible rationale.
   

• Collaborate with stakeholders. Get buy-in. Stakeholder input adds credibility.
   

• Estimate price by global region. Price is often higher in relatively wealthy countries like the U.S.
   

 

Prioritizing Assumptions to Validate

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Prioritize validating an assumption if:
 

• The target metric is highly sensitive to the assumption. Change each assumption by the same percentage and note assumptions that cause the largest percentage change in the target metric.
   

• Its worst-case scenario causes the largest percentage change in the target metric. Estimate a realistic worst-case scenario for each assumption. Unlike sensitivity analysis, the percentage change in the assumption is not important.
   

• It has a low probability of being true. Gather data to support the “null hypothesis” that the assumption is not true.
   

• It has a relatively low cost to validate.

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Applying the above prioritization concepts to business case assumptions:
 

• Market size and revenue are highly sensitive to (i) launch price, and (ii) the number of times per year customers buy your product (“algorithm”) which is typically low cost to validate. Prioritize validating your algorithm for market segments and/or geographies that comprise most of your market size and revenue.
   

• Market size is also sensitive to addressable volume, which is typically low cost to validate. As discussed in our Market Sizing article, you might have “direct” customers that purchase your product and then offer your product to their own customers – your “indirect” customers.
   

• Revenue is also sensitive to market share. Attainable market share depends on product differentiation, willingness to buy at the price point, and sales + marketing execution. Prioritize validating product differentiation and willingness to buy at the price point.
   

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Validation Methodologies

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Start by validating addressable volume assumptions. If your addressable market is too small you can avoid the effort of validating assumptions about the revenue and profit opportunity.
 

• Consult with industry experts (internal and external) to (i) determine which indirect customer market segments your solution could address (ii) determine whether you could efficiently sell to indirect customers via direct customers, and if so, which direct customer segments you could address (iii) develop hypotheses about expected and worst-case scenarios for your algorithm and for how much customers pay for alternative solutions.
   

• Find a trustworthy data source for your indirect customer volume. An ideal data source segments volume in a way that enables you to eliminate segments you cannot address.
   

• Triangulate on your indirect volume data source by using different revenue drivers and/or data sources to estimate addressable volume. Validation occurs when the secondary approaches and/or data sources are within 20% of the original method.

  • Meta-literature that analyzes various other literature sources is particularly helpful. Be careful about data definitions – literature might focus on a narrower demographic or region than you.

  • If relevant, interview direct customers about how many indirect customers they serve, how they segment the indirect customers and purchase drivers for each indirect customer segment.

    • Find a data source for the number of direct customers. Like with indirect customer data sources, an ideal data source segments direct customers in a way that enables you to eliminate segments you cannot address.

    • Calculate addressable indirect customer volume served by addressable direct customers.

  • Back test your financial model for a few years when evaluating a product upgrade or extension where you have significant market experience. Given your understanding of competitor market share, adjust your addressable market volume if necessary to make more sense.
     

• Interview customers about problems and solutions. Ask potential customers open-ended questions that elicit a story about (unmet) needs, challenges with existing solutions, what they are looking for in a new solution and their recent search efforts, ideal solution, purchase volume drivers i.e. why they need a solution and switching costs and more (see below). Validation occurs when you encounter “interview boredom” after hearing consistent responses to open-ended questions. 4-8 interviews are often enough.

  • Algorithm. Confirm your hypothesis and learn how to avoid the worst-case scenario.

  • What customers pay for alternative solutions. Try to confirm your hypothesis.

  • Value alternative solutions have provided to customers. Learn what you can to help inform your price point. Your product can likely capture 10-30% of customer value realized.

  • Challenges using alternative solutions. Informs your product differentiation and price.

  • Generate interview leads. Ask about colleagues who might be willing to speak with you.

  • Be mindful of your customers’ time. You might want to follow up with them.

 

Finish validating core market size assumptions by analyzing price. To do so, you’ll need either a clear description of your solution and its differentiation or a prototype or mockup of the solution.
 

• Interview customers about price and willingness to buy at the planned launch price. Again, ask open-ended questions and conclude the effort when you hit “interview boredom.”

  • The Van Westendorp pricing method helps define a range of acceptable prices by asking customers at what price is a product (i) a bargain (ii) a bit expensive but still worth considering (iii) too expensive (iv) too cheap to consider because you question the quality.

  • In a different interview, ask about willingness to buy at your planned launch price on a scale of 1-10 where 10 means “definitely.” Walk potential customers through a mockup or prototype of your solution. If the willingness to buy is less than 10, ask what would need to happen to change the answer to a 10.
     

• Research your competition’s pricing. As discussed in our Market Sizing article, using existing products as a reference point is most important for products that are not revolutionary. To address the customer risk of using new products, many companies underprice new products which reduces their market size. Addressing customer risk directly is generally a better strategy.

  • You can potentially price higher than your competition if your product is faster or less labor-intensive. A “total cost to use” analysis would then indicate your product has an equivalent price given its advantages in speed and/or ease of use.
     

Then validate assumptions related to attainable market share for five years. Again, you’ll need either a clear description of your solution and its differentiation or a prototype / mockup of the solution.
 

• Triangulate on your attainable indirect volume. Segment your direct customers by small/medium/large volume and prioritize segments most likely to adopt your solution at launch. Estimate (i) how many direct customers you can capture in a year given your price point and their switching costs, and (ii) your potential indirect customer volume given direct customer switching costs and indirect customers served. Again, validation occurs when the secondary approaches and/or data sources are within 20% of the original method.

  • For product managers seeking internal funding, ask sales how many existing customers are likely to buy the product in the first year, and ask finance about historical product launch volume and customer uptake.

  • Achieving 30% market share in five years is generally aggressive; in many industries, 3-4 competitors take 70% of the market.
     

• Consider conducting landing page tests about product differentiation. Publish a web page showcasing your new solution’s features, workflow and differentiation, and invite visitors to sign up to receive more information or request early access. Ask qualified respondents which aspect of the solution is most important to them and why, and if they have any suggestions for additional features or capabilities.

 

Finally, validate assumptions about profitability.
 

• Cost of Goods Sold (COGS, or all costs to make a product) typically declines over time as a percentage of revenue as you achieve economies of scale.

  • To estimate short term COGS, analyze the cost of labor, materials and overhead for each step in the production process and/or seek quotes from contract providers.

  • To validate long term COGS as a percentage of revenue, analyze comparable publicly traded companies.
     

• Operating expenses e.g., sales, marketing, general and administrative. Your operating expenses as a percentage of revenue in the medium term should be like those of comparable publicly traded companies that are rapidly growing. In the short term, they may be even higher. Growth companies prioritize investing in growing their business over profitability. As companies mature, they reduce operating expenses as a percentage of revenue.

  • Consider fixed costs in your first year after launch. Calculate the all-in annual cost of the sales, marketing and administrative people you plan to hire at launch and set your operating expenses as the higher of the fixed cost or the comparable expense ratio.

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About the Author

Daryl Michalik is a Principal at Michalik Enterprise Services.

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Michalik Enterprise Services Can Help

As experts in product management and financial analysis, we have significant experience in crafting business cases and validating their assumptions. We distill business cases into simple assumptions and credible financial models by collaborating with stakeholders and efficiently sourcing relevant information about assumptions. We can undertake an entire project or a portion of one or provide feedback on an existing analysis.

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