Financial forecasting is a crucial tool for any business because it enables you to anticipate profits. The ability to accurately predict fluctuations in revenue allows you to overcome cash flow issues and budget accordingly. While there are many methodologies for preparing a financial forecast , two of the most common are top-down and bottom-up analyses. A top-down analysis starts with a business assessing the market as a whole. First you determine the current market size available for your business and factor in relevant sales trends. Then you can estimate how much of the market will buy your products or services.
Today we are going to have a comparative study of the two approaches being used in field of structured and object oriented programming. We shall start with a brief understanding of the both followed by comparison and conclusion. Image Source. When talking in terms of computer science and programming, the algorithms we use to solve complex problems in a systematic and controlled way are designed on the basis of two approaches that is Top-down and Bottom-up approach.
Top-down vs. bottom-up: Which financial forecasting model works for you?
Top-down and bottom-up are both strategies of information processing and knowledge ordering, used in a variety of fields including software, humanistic and scientific theories see systemics , and management and organization. In practice, they can be seen as a style of thinking, teaching, or leadership. A top-down approach also known as stepwise design and stepwise refinement and in some cases used as a synonym of decomposition is essentially the breaking down of a system to gain insight into its compositional sub-systems in a reverse engineering fashion.
Top-down vs. Object Database Design. There is still a great deal of controversy about the best way to approach database design for object-oriented systems. Architecturally, some experts argue that the relational model is not well suited for use in an object-oriented environment while other experts maintain that relational architectures are more suitable for traditional data processing.