Choosing the right quantitative analytics model depends on the field and questions being asked. Financial professionals might use technical analysis, market researchers assign numerical values, and computing professionals monitor automated systems. Knowing the desired outcomes is important. Outcome logic design helps make strategic decisions, while needs-based assessments interview stakeholders to determine demand. Consult with all interested parties before establishing a model.
Choosing the best quantitative analytics model depends on the field you work in and the questions you would like to ask. Financial professionals interested in analyzing the performance of financial instruments, such as stocks and bonds, might use a quantitative technical analysis model, in which they draw conclusions based on the instruments’ past behaviors. Market researchers, on the other hand, might use models where they can assign numerical values to different variables in a study, such as target demographics, regions, and product and service prices. People who need a quantitative analysis model in a computing context might choose one that allows them to monitor the production levels of automated systems in real time.
Knowing what questions you want to answer or what outcomes you want to achieve is important when it comes to choosing the best quantitative analytics model. People interested in monitoring system results should use a quantitative analysis model for managing results. With this type of model, users define specific factors and actors in a system and can visualize how they influence the results. These people could use the models to continuously improve the systems.
Outcome logic design often works well for making strategic decisions. With this type of analysis model, individuals use methods such as drawing chains of outcomes to see how certain incomes indirectly affect certain factors. For example, a person using a model to determine strategies for opening a store in a new geographic market might analyze how this expansion affects cash flow in other areas of a large organization. People use outcome models to manage risk during strategy development, determine what casualties to expect after implementing a new strategy, and to ensure expected outcomes are logical.
Individuals looking for a model to help them determine whether there is a need for a particular product or practice could benefit from needs-based assessments, where they can interview stakeholders. For example, before an organization introduces a new product to a market, marketers might interview a significant sample of target demographics, then assign numerical values to ratings or responses, as well as to different groups within the demographics. Needs-based models work well for all people who have a product or service to sell, but are not sure if and where a product is in demand.
Before establishing a quantitative analysis model, it is important to consult with all the people who have any interest in your analysis. It may be helpful to divide these people into two groups that you consult separately. A group might include all the people contributing to an actual analysis. The other group might include people who could benefit from an analysis.
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