The Steps to Implement Predictive Analytics
The following is the step-by-step process that CAN would use to implement predictive analytics into your business systems:
We select from our catalog of intellectual property which mathematical formula or survey questions will be most effective to explain the activity being studied, and develops a list of potential dependent and independent variables.
We will meet with individuals on your team to learn more about your business, employees, and customers. This meeting is intended to be a discussion to determine the independent variables that are most likely to be significant and their correlation to the dependent variables. To encourage discussion, before the meeting, participants will be given a list of proposed dependent and independent variables, a description of the hypothetical model, and how the results will be applied.
At the beginning of the meeting, the we will give a brief introduction of how the hypothetical model will be developed as well as an overview of the proposed dependent and independent variables. After the introduction, one member of our team will work to moderate the discussion and take notes. The outcome of the meeting with be a list of:
- Important Historical Events: Understanding historical events help to identify outliers and their cause(s), such as errors in the data, changes in business paradigms, or significant events outside of the business.
- Assumptions: No model can be perfect, and thus require a certain number of assumptions. Assumptions are non-conscious theories about how the world works. It is important to understand the assumptions so that results can be accurately produced and interpreted.
- Dependent Variable: The Dependent variable represent the desired outcome that is being studied. The predicted dependent variable is explained by the mathematical mixing of the independent variables. The value of the dependent variable will change whenever the independent variables change, and that is why it is called the dependent variable.
- Independent Variables: Independent Variables are variables that are hypothesized to have an impact on the dependent variable. When the independent variables change, the dependent variable changes as well.
After the second step, the our team will collect the data for the dependent and independent variables from internal and external sources. CAN will work with your team to securely transfer the data from your internal sources. If the necessary data is not available CAN will develop a survey. Once the data has been collected it is loaded into the CAN database, cleansed, and connected to the modeling environment.
Contemporary Analysis will study the data and present an overview to your team to ensure that we are correctly interpreting the data.
The data will then be run through mathematical models to determine which variables have the most significant impact on the activity being studied. Models are selected based on statistical robustness, standard error, and how well they represent the data.
A research report will be developed to provide information on the variables and why they were selected, the quality of the data, the quality of the model, and suggestions on how the research can be applied. The report is developed both as a comprehensive study and an executive summary to facilitate those who are non-specialists, but want to gain an understanding, and for those requiring a greater level of detail.
CAN will meet with your team to present the results of the research, the report, and suggestions of how results can be implemented. The CAN team will also work with the management team to break down results into specific and actionable tasks.
Please contact us to learn how we can help implement predictive analytics into your organization.