The true power of machine learning algorithms is in their ability to find patterns and relationships between events and actions by processing enormous amounts of data.
The Easy Projects Machine Learning Module uses this approach to predict when a project is most likely to be completed. To figure it out, Easy Projects utilizes our proprietary algorithm to process all available historical data and analyze dozens of variables:
- Who is working on a project;
- What’s their past performance history;
- How quickly tasks are being closed;
- Who is the manager;
- History of similar projects;
- Project message history;
- And many more...
As a result, it informs the project manager the most likely project end date and its confidence in this prediction. This forecast can be done at any stage of the project. Of course, in order for the prediction to work accurately, it needs as much historical data as possible, typically at least 6-8 months worth of data.
This functionality will be the most useful for larger-scale projects (3-6 months). While it’s unlikely for the algorithm to determine the exact day when the project is going to finish, even a range of several days can be a huge help for a manager if they can see early on that there is a high probability of missing the planned deadline. By taking preemptive corrective actions early, project managers can potentially save their organizations thousands of dollars in contractual obligations, overtime payments, and unhappy clients.