Growth Curve Definition
A growth curve is a graphical representation of the increase in a particular quantity over time. A growth curve has different applications in different fields of study — for example, in biology, growth curves are typically used to assess pathological fields or during entomology trials, while in economic growth analysis, they can be used to analyze the increase in the market value of goods and services produced by an economy over time. Over the past few decades, growth curves have developed into vital statistical tools that help determine growth patterns irrespective of whether such patterns are linear, exponential or quadratic. As a result, they are extensively used in finance, especially by businesses, in order to create a mathematical model to analyze the growth in sales or profits, and also to predict future sales.
A Little More on What is Growth Curve
Growth curves can be typically classified into two types –
- Exponential growth curve, or, J Curve.
- Logistic growth curve, or S Curve.
Exponential growth curve: Exponential growth, also referred to as unrestricted growth, usually occurs in an ideal environment with unlimited resources — the growth is slow in the beginning, but increases rapidly with the passage of time. Exponential growth curves are most commonly used to denote population growth, growth of wealth and investments, business growth, and growth in website traffic as well as followers on social media. A great example to illustrate exponential growth would be that of living bacteria in a petri dish in a laboratory — under ideal conditions, the bacteria will reproduce by binary fission, i.e by splitting in half, roughly once every hour. Now assuming that the petri dish originally contained 1 million bacteria cells, it would end up with 2 million cells after an hour. After two hours, there would be 4 million bacteria cells. The number of bacteria cells in the petri dish would increase to 8 million cells after the passage of three hours, and so on. However, it should be borne in mind that it is usually not possible to sustain exponential growth over long periods of time since there is a limit to the availability of resources in the real world.
Logistic growth curve: Logistic growth, or restricted growth occurs when the numbers begin to approach a finite carrying capacity — the growth is typically fast in the initial stage, but drastically slows down with the passage of time. Logistic growth patterns are most prominent in graphical representations of increase in literary skills or language proficiency, weight loss regimes and musical skills. Logistic growth also occurs in populations that begin to experience environmental resistance while approaching the carrying capacity. A good example of logistic growth would be that of a person partaking in mass building or strength training at the gym — the initial muscle or strength gains will be quick and fairly noticeable. However, once the individual attains a certain degree of fitness, the gain will typically slow down and become much less noticeable as time passes.
In business, the shape of the growth curve essentially determines the direction that the company will be required to take in the market. For many businesses, logistic growth markets are not the most desirable places for product launches because such saturated markets do not leave much room for profits. On the other hand, exponential growth markets do provide opportunities for fast growth and handsome profits, but they also typically lure in a lot of competitors.
History of Growth Curves
Growth curves can trace their origins to physical sciences such as biology, which makes extensive use of exponential, logistic, monomolecular, and Gompertz curves. However, with advancements in information technology, especially since the dawn of the new millennium, growth curves have become a staple of business models. With the continuous change to demographics and the coming of age of artificial intelligence, researchers are increasingly abandoning conventional methods of analyzing growth curves or trends in lieu of more developed and industry-specific methodologies.