Marginal Analysis: A Complete Guide with Examples

You don’t have to flip your entire business model upside-down to find more profit. Sometimes, it just takes a small change to win big. Marginal analysis lets you see the small, strategic adjustments in pricing, production, or sales strategy that could boost your bottom line. Forget about guesswork. We’ll show you how to use marginal analysis to optimise revenue, cut costs, and improve overall performance to help improve your revenue lifecycle.

Read on to learn more about margin analysis, how to perform one, and how it might look in the real world.

Marginal analysis is a way to evaluate the costs and benefits of making a change, even a small one. Unlike other financial assessments, marginal analysis hones in on the impact of one small change. That might be producing one more product, hiring an additional employee, or investing in an extra marketing campaign.

Businesses, sales workers, and finance professionals rely on marginal analysis to maximise profits, improve efficiency, and guide investment decisions. By examining how small changes impact outcomes, you can see if there are benefits of more production compared to the costs of implementing it. Marginal analysis shows the cost of production until the break-even point (where the costs and income are equal). This helps you ensure the benefit outweighs the cost.

Or it could guide your product decisions. For example, manufacturers apply marginal analysis to decide how many units to produce. If the cost of producing one additional unit (marginal cost) is lower than the sales revenue it generates (marginal revenue), it makes sense to increase production. However, once the marginal cost exceeds marginal revenue, further production becomes unprofitable.

Margin analysis examines incremental changes, focusing on the additional cost or benefit of making a small adjustment. It’s particularly useful for optimising ongoing processes, such as adjusting pricing, hiring decisions, or production levels. On the other hand, a cost-benefit analysis (CBA) looks at the total costs vs. total benefits of an entire decision. It’s typically used for larger, one-time investments, such as launching a new product line, expanding into a new market, or acquiring a company.

Marginal benefit is the additional value or revenue gained from producing or consuming one more unit while the marginal cost is the additional expense incurred from producing or consuming one more unit of a good or service.

Typically businesses will compare these two metrics to determine the most efficient point of operation. The best case scenario is when marginal benefit equals marginal cost (MB = MC). For example, if the marginal benefit of raising prices exceeds the marginal cost of lost sales, a price increase is justified. Or if hiring a new employee could generate more recurring revenue than the cost of their salary, the company should send them an offer letter.

Marginal analysis is a great tool for businesses looking to make data-driven decisions. It can help you carefully weigh the incremental gains against the incremental costs of various actions. Instead of making broad, generalised choices, your company can fine-tune its strategies by evaluating the precise impact of small changes. That way you can see if even a tiny adjustment in your production levels or pricing could help your company increase your profits. When you use a margin analysis, you can:

• Optimise resource allocation: by allocating time, labor, and capital efficiently and assessing whether additional investment in a particular area will yield a proportional return.
• Maximise profitability: by determining the most profitable production levels, pricing strategies, and investment decisions by focusing on incremental changes rather than broad financial shifts.
• Improve cost efficiency: by identifying areas where you can cut unnecessary costs while maintaining or even increasing output and gross revenue.
• Enhance decision-making: by providing a structured, data-driven approach to evaluating business changes, helping your company’s executives and managers make informed choices.
• Support pricing strategies: by assisting you in setting the optimal price point by balancing consumer demand with production costs to maximise revenue.

One of the primary uses of marginal analysis is to help your company make more money. You can use a margin analysis to determine your best production levels or control costs effectively. For example, let’s say a retail company selling electronics wants to optimise its pricing strategy to maximise profitability.

By conducting a marginal analysis, they test incremental price increases on their best-selling product. This research indicates that raising the price by 5% leads to increased total revenue, even with a slight drop in sales. This business could then use the results of the marginal analysis to determine that they should adjust the pricing model to boost their profits.

The general formula for marginal analysis is:

Below is the breakdown of what each facet of the formula means:

• Change in benefit: The increase in revenue gained from an additional unit of production, investment, or action.
• Change in cost: The extra expense incurred from producing or implementing one more unit.
• Change in quantity: The number of new additions (e.g., one more product produced, one more employee hired, or one more dollar spent).

Marginal analysis is a structured approach that helps businesses evaluate the financial impact of small changes in production, pricing, hiring, or investment decisions. Here’s an example of how to perform a margin analysis, with a pizza restaurant:

• Identify a change you’re evaluating: Pick what one adjustment you’re going to make. The pizzeria is evaluating increasing the price of a single slice of pizza from $5 to $6.
• Determine the marginal cost: This cost refers to any additional expenses incurred from implementing the change. That could include the boost in raw materials or even the cost of training for employees. In this example, the marginal costs would include the expense of remaking menus or a loss of sales.
• Determine the marginal benefit: This is the additional revenue, efficiency, or utility gained from implementing the change. Here, the main benefit would be higher revenue.
• Compare the marginal cost vs. marginal benefit: You want the benefit to exceed the cost. If it doesn’t, you’ll want to reconsider the change. If they’re equal, you’ll want to evaluate your approach and consider tweaking it. The pizza restaurant believes that the increase in sales will far outweigh the cost of remaking menus and a few customers dropping off.
• Make data-driven adjustments: Once you implement the change, monitor it and adjust if necessary. The pizza restaurant finds that the price change is successful in the market, so they keep it.

Marginal analysis is widely used across industries to guide data-driven decision-making. Below are real-world examples demonstrating how different sectors might use marginal analysis to improve efficiency and profitability.

Manufacturers use marginal analysis to determine the most profitable production levels, adjust pricing strategies, and manage labor costs. They evaluate whether producing additional units will increase profits or lead to diminishing returns due to rising costs. Below is a hypothetical example about a car manufacturer:

The car manufacturer wants to determine if increasing production from 1,000 to 1,200 vehicles per month is financially beneficial.

• Marginal cost: The additional 200 vehicles require more materials, labor, and energy, adding $15,000 per vehicle to production costs.
• Marginal revenue: Each vehicle sells for $18,000, generating an additional $3,000 per vehicle in revenue after covering marginal costs.
• Marginal benefit: Since the marginal revenue ($18,000) is greater than the marginal cost ($15,000), the manufacturer should increase production.

The reverse could also be true. If the car company found that increasing production from 1,000 to 1,200 would lead to diminishing returns, they wouldn’t move forward. Here’s how the example would look if that were the case:

• Marginal cost: This metric is the same. It will cost about $15,000 per vehicle to increase production costs.
• Marginal revenue: However, a recent change in the economy has made it more difficult to sell cars at their full price. To continue to sell, the company changes the cost per vehicle from $18,000 to $14,000.
• Marginal benefit: Since the revenue is now lower than the cost, the manufacturer won’t increase production.

In healthcare, marginal analysis helps hospitals and providers allocate resources, determine optimal staffing levels, and assess the cost-effectiveness of treatments. Below is a hypothetical example about a hospital staffing decision.

A hospital evaluates whether hiring an additional nurse for the night shift is cost-effective.

• Marginal cost: The nurse’s salary and benefits amount to $108,000 per year.
• Marginal benefit: The additional nurse allows the hospital to treat 10 more patients per night, each generating an average revenue of $500, leading to an additional annual revenue of $1,825,000
• Decision: Since the marginal benefit ($1,825,000) is higher than the marginal cost ($108,000), hiring the nurse is a good financial decision for the hospital.

While marginal analysis is a powerful tool for optimizing decision-making, it has inherent limitations to consider. These are a few of the challenges to consider:

• Difficulty measuring intangible costs and benefits: It’s hard to measure factors, such as brand reputation, employee morale, or customer satisfaction.
• Unpredictable variables: Many business decisions involve uncertainty, making it difficult to forecast the exact marginal benefits or costs.
• Short-term focus: Marginal analysis is typically used for incremental, short-term decision-making rather than long-term strategic planning.

While marginal analysis is useful for fine-tuning operations, it is not always the best standalone decision-making tool. Businesses should complement it with other approaches in situations such as when you’re considering expanding into a new market.

The integration of AI-driven analytics and sales automation tools has changed how businesses conduct marginal analysis. It’s now faster, more accurate, and highly scalable. Traditional marginal analysis requires manual data collection and calculations, and that can be time-consuming and prone to human error. Using Sales AI can help reduce those challenges and provide you with more benefits, such as:

• Automated data processing and real-time insights: AI-driven sales analytics automatically collect and process large datasets, eliminating the need for manual number-crunching. A sales platform can use AI to track customer purchasing behaviours and adjust pricing dynamically based on demand fluctuations.
• Predictive marginal analysis: AI-powered sales forecasting models help businesses predict future marginal costs and benefits with greater accuracy. For instance, a retail chain uses AI to forecast the impact of increasing product prices by 5% across different store locations.
• Automated workflows: Using AI to optimise workflows to make your marginal analysis more efficient. By automating the process of calculating marginal analysis, your team can save time and energy.

Overall, marginal analysis can help you test how a change might benefit your company. If you’re thinking of hiring a new employee or expanding your product line, this formula can help you determine if that’s in your best interest. It’s a simple way to gain more insight into your company’s financial potential and to inform your decisions about potential growth opportunities. To make this process more effective, consider implementing AI sales agents can help you build sales pipelines and gather data you need for effective marginal analyses. These tools can help you perform this simple test faster, so you can move forward with confidence.

Get started with Salesforce Sales Cloud to start performing smarter analyses.

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