This article explains the overview of Fermi estimation and why it is highly valued in the consulting industry, for those considering a career change into consulting.
Having Fermi estimation skills — which make the most of available data to drive problem-solving — allows you to demonstrate strong logical thinking during interviews. We also introduce how to apply Fermi estimation depending on the target, along with specific example problems, so please use this as a reference.
What Is Fermi Estimation?
Fermi estimation is a method used to derive approximate values in situations where detailed data or information is lacking.
Based on available information and known facts, complex problems are broken down into smaller elements. Reasoning is then applied to each element before being integrated to arrive at an approximate value.
For example, when developing a new business plan or strategy, predicting market size and managing uncertainty are required. In such cases, Fermi estimation — which allows quick approximate calculations from basic data — is highly effective.
In addition, job interviews at consulting firms and similar companies often use Fermi estimation to evaluate logical thinking and problem-solving ability. Particularly in the consulting industry, where problem-solving relies on known information, Fermi estimation skills are highly prized.
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Example Problems of Fermi Estimation in the Consulting Industry
Fermi estimation, applicable across a wide range of fields, is frequently used in situations that require rational decision-making. Let’s look at some example problems to deepen our understanding.
Example 1: Market Size of Ramen Restaurants
When you want to get an approximate sense of market size, one approach is to use Japan’s total population as a baseline.
Specific numerical assumptions are made for the proportion of Japan’s population that eats ramen, the average consumption frequency per person, and the average amount spent per visit, and calculations are performed based on these.
When estimating market size, it is important to make assumptions explicit and proceed with calculations logically.
Example 2: Estimating Sales for a Single Café
When estimating the daily sales of a single café, factors such as the register’s hourly capacity (maximum number of customers served), register utilization rate, operating hours, number of customers, and average spend per customer are considered. It is also important to make inferences and assumptions that include the store’s location, customer demographics, and peak hours.
For example, let’s think about the number of customers based on daily operating hours.
If the inference is that the store gradually gets busier from opening until around noon, stays at peak from noon through the evening, and then gradually tapers off after the evening, dividing the day into three time periods and setting a utilization rate for each improves the accuracy of the estimate.
Example 3: Number of Utility Poles in Japan
When estimating the number of utility poles in Japan, land area and pole density are used. To get closer to the actual figure while accounting for these factors, it is important to also make assumptions about factors such as population density and terrain.
For example, in Japan, a large portion of the land area consists of mountainous terrain. Including the realistic condition that utility poles are installed on flat land leads to a more accurate estimate.
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Basic Approach and Method for Answering Fermi Estimation Questions
Using “the market size of ramen restaurants” from Example 1, we will explain the Fermi estimation approach and method step by step.
Step 1: Break Down the Problem
This step involves clarifying the problem to be solved and breaking it down into fundamental elements. Breaking a complex problem into smaller parts deepens understanding of each element, making it easier to grasp the essence of the problem.
The problem definition and broken-down elements when considering the market size of ramen restaurants are as follows.
Estimate the market size (annual revenue) of ramen restaurants in Japan
a. Total population of Japan
b. Proportion of Japan’s total population that eats ramen
c. Average frequency of visiting a ramen restaurant per person
d. Average price per visit
To improve the accuracy of estimates, it is necessary to simplify complex problems by breaking them down and calculating numerical values individually.
Step 2: Set the Strategy
Next, determine whether the nature of the problem is better suited to a population-based approach or an area-based approach.
When estimating the market size of ramen restaurants, estimating the number of visitors is key, so a population-based approach is appropriate.
The population-based approach is effective for demand forecasting of products and services, and for estimating consumer behavior.
On the other hand, the area-based approach is suited to estimating infrastructure placement such as roads and utility poles, and land use related to farmland and similar.
Step 3: Structure the Key Issues
Based on the strategy, identify the issues with the greatest impact on the problem, build the flow of reasoning, and consider the formula. By clarifying the important elements, estimates can be made based on more specific information.
For example, set the formula as: “Ramen restaurant market size (annual revenue) = Total annual visits × Average spend per customer.”
Step 4: Calculate and Derive the Result
Apply the assumed numerical values to each element based on the structured key issues and calculate.
In this step, ingenuity to simplify calculations is needed. For example, Japan’s total population is approximately 123 million (as of 2024), but using 100 million for the calculation simplifies the arithmetic.
a. Total population of Japan: approximately 100 million
b. Proportion of Japan’s total population that eats ramen: assumed to be 75%
c. Average frequency of visiting a ramen restaurant per person: assumed to be twice a month
d. Average price per visit: assumed to be ¥900
The calculations required to obtain the result are as follows.
| Number of ramen eaters | Calculated from the proportion (b) of ramen eaters relative to Japan’s total population (a) | 100 million × 0.75 = 75 million people |
| Total annual visits | Calculated from the average visit frequency (c) of ramen eaters | 75 million × 2 visits × 12 months = 1.8 billion visits |
| Ramen restaurant market size (annual revenue) | Calculated from total annual visits and average spend per customer (d) | 1.8 billion × ¥900 = ¥1.62 trillion |
The key point in Fermi estimation is to make assumptions explicit and then proceed with calculations logically. Once the final result is derived, examine its validity and make corrections as necessary.
Reference: Statistics Bureau of Japan, Population Estimates
Types of Fermi Estimation
There are several types of Fermi estimation.
Understand the characteristics of each type so you can apply Fermi estimation appropriately depending on the characteristics and purpose of the subject, and the information and data available.
Macro Sales Estimation
Macro sales estimation, suited for handling large-scale data, is a method used to estimate the sales of an entire market.
For example, when estimating the total sales of the ramen market in Japan, an approximate market size can be calculated based on elements such as Japan’s total population, the average frequency of ramen consumption, and the average spend per visit.
Using macro sales estimation, you can forecast the overall scale and demand of a target market, allowing you to explore the potential for new businesses.
Since competitors’ market share and sales can also be estimated, it is also possible to objectively evaluate your own company’s competitiveness and optimize strategy. Furthermore, classifying users into light users and heavy users allows for a more accurate estimation of market size.
Micro Sales Estimation
This is a method suited for when you want to understand the sales of a specific store or area. When estimating sales on a small scale, micro sales estimation — which calculates based on individual data — is appropriate.
For example, when estimating a café’s daily sales, factors such as number of seats, average spend per customer, table turnover rate, and operating hours are considered. It is also possible to improve the accuracy of the estimate by accounting for time-of-day characteristics.
Micro sales estimation is effective when considering the possibility of opening a new location or when trying to improve the performance of an existing store.
Quantity Estimation (Owned / Non-Owned)
Quantity estimation is a method used to estimate the number of objects. It is classified into owned and non-owned depending on the target of estimation and the difference in approach.
Quantity estimation of owned items is a method suited to consumer behavior analysis and market analysis. It is characterized by targeting specific items owned by individuals or organizations, and estimating based on the owner as a reference point.
On the other hand, quantity estimation of non-owned items is used in infrastructure development and resource management. Since it is used to estimate the quantity of objects in a specific location or situation, it is characterized by thinking from the perspective of “where it is.”
Why Fermi Estimation Is Valued in Consulting Industry Interviews
Fermi estimation is a method for breaking complex problems into smaller parts and deriving rational estimates from limited information.
Fermi estimation questions may be asked in consulting industry interviews. Let’s understand why Fermi estimation is highly valued.
It Can Confirm the Level of Logical Thinking
Fermi estimation is useful for evaluating logical thinking ability.
Logical thinking refers to the ability to thoroughly consider the “why” and “how” behind things. In consulting, clients themselves are often unaware of the background of their issues or the root causes. The ability to thoroughly think through the reasons behind a challenge and identify concrete solutions — logical thinking — is one of the indispensable abilities for a consultant in such situations.
In actual consulting work, there are many opportunities to use Fermi estimation when estimating market size or researching the chances and possibilities for new businesses.
In job interviews, there is a tendency to place greater importance on how logically the candidate can explain an estimated figure derived using general knowledge, rather than on whether the correct answer is reached.
Since the ability to make rational estimates within limited information and time is tested, Fermi estimation skills are extremely important for consultants.
It Allows Assessment of Communication Skills
Interviewers check communication ability from the perspective of how the candidate approaches solving a problem and whether they can explain the process clearly.
In actual consulting work, there are many situations where dialogue with clients and the communication of complex information are required while working toward resolving issues. Therefore, the ability to engage in constructive dialogue is necessary.
From listening to the problem through proposing and implementing measures, smooth communication must be maintained to ensure both parties remain aligned — which is why Fermi estimation is valued as a way to verify that skill.
It Allows Verification of Flexible Thinking
Fermi estimation is also used for the purpose of evaluating what perspectives and ideas a candidate has, and whether they can approach problem-solving flexibly.
Since flexible thinking and creativity are required to thrive as a consultant, whether the candidate can propose new approaches is also a point of evaluation.
By demonstrating the ability to adapt to various situations through Fermi estimation, you should be able to appeal your capacity to adapt to uncertain environments.
Is Fermi Estimation Really “Useless” or “Pointless”?
Despite being valued in interviews for a variety of reasons, Fermi estimation has reportedly drawn criticism — mainly from hiring personnel — as being “useless” or “pointless.”
Originally, Fermi estimation is said to have begun as a way to observe how candidates respond when asked something out of the blue.
However, as Fermi estimation questions became widely known, many preparation books were published and candidates became able to prepare sufficiently. As a result, it is believed that Fermi estimation came to be considered useless because it could no longer measure the original goal of “ability to respond to unexpected questions.”
In Japan, Fermi estimation has been adopted mainly by companies in consulting, investment banking, and similar industries. On the other hand, some major global companies that were at the forefront of adopting it have discontinued its use in their selection processes.
In fact, Google stopped using Fermi estimation in interviews. This was because it became clear that being good at Fermi estimation does not necessarily mean high performance after joining the company.
However, this does not mean Fermi estimation has no value. Its intrinsic value remains intact.
Fermi estimation is effective in strengthening the ability to derive approximate values from incomplete information — a skill demanded in business settings. It cannot be said wholesale that Fermi estimation is “useless” or “pointless.”
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Summary
Fermi estimation is a method for deriving approximate values based on limited data and information, and depending on the scale and purpose of the subject, it is used in different forms: macro sales estimation, micro sales estimation, and quantity estimation (owned / non-owned).
Since it can measure logical thinking, communication skills, and flexibility of thought, Fermi estimation questions may be asked in job interviews at consulting firms and similar companies.
In recent years, there are voices saying Fermi estimation is useless, but the ability to derive approximations from incomplete information is important not only in the consulting industry but in business in general. For those aiming for a career change into the consulting industry, Fermi estimation skills should be a significant asset.
