Marginal Analysis

Marginal Analysis is a technique used in business intelligence and data analytics to help make decisions about where and how to allocate resources most effectively. It’s a bit like figuring out how much extra study time will improve your grade on a test. Businesses use this type of analysis to understand the benefit of producing one more unit of something—like an additional gadget or service—and whether the profit from selling that unit will cover the cost of making it.

The ‘marginal’ part means it’s concerned with the effect of adding or subtracting a single unit. For example, a company might use Marginal Analysis to decide if it should hire another employee. If the new hire brings in enough additional sales to pay for their salary and more, then it might be a good decision. Marginal Analysis crunches the numbers to ensure that the money and effort spent are adding enough value to justify the investment.

This approach comes in handy when businesses face constraints like limited budgets or production capacity. By focusing on the additional cost and additional revenue associated with small changes, companies can optimize their operations without making huge, risky leaps. Marginal Analysis helps them identify the ‘sweet spot’ where profit is maximized, ensuring every dollar spent is working as hard as it can.