context
In today's rapidly evolving markets, the need for companies to react swiftly to the changing environment is essential. Making the right decision in such an atmosphere is easier when there is a clear view on what the future will bring. Predictive modelling helps companies to foresee the future, and thus supports today's business decisions, closing the performance management cycle.
Predictive modelling is the process by which a specific model is created or chosen to try to best predict the probability of a particular outcome. In the context of performance management it is used particularly in the areas of data mining and forecasting, using one or more classifiers in trying to determine the probability of a set of data belonging to another set. Predictive modelling can be applied in every industry or business domain where the underlying information is available.
key considerations
Successful predictive modelling projects rely on several key components:
- detailed business understanding: to avoid wrongfully correlated variables, extensive business knowledge is required for accurate data preparation and outcome analysis.
- information availability: predictive models rely on sufficient and reliable historical data. To ensure the model's rightfulness, the data must be cleansed and must contain identifiable patterns. The role of the data warehouse and Enterprise Information Management systems is fundamental in this exercise.
- appropriate model selection: a variety of models and techniques is available, each with their specific application fields. Appropriate model selection is a primary success factor in a successful predictive modelling project.
- adequate technology selection: the selection of the most appropriate data modelling tool requires a correct assessment of the environment, as well as good communication between all departments involved, ensuring its perfect integration.
Keyrus and predictive modelling
Through more than ten years of dedicated business intelligence and performance management consultancy, Keyrus has acquired strong expertise in several business domains, allowing us to successfully support our customers in data interpretation and model development with a comprehensive team of business and technical consultants.
