MPPA is built using ML to analyze multidimensional and multisource data. MPPA is trained on process delay data by using process mining to identify common process paths, interconnections, deviations, and hidden patterns. It maps the critical path across multiple subprocesses, identifies bottlenecks, and recommends AI-driven actions using automated alerts.
MPPA integrates explainable AI techniques to understand which factors contributed to the alert, and recommends next-best actions tailored to those factors when predicting process delays at the start of each project. In addition, by using robotic process automation, the alerts and recommended actions integrate directly into the enterprise project management tool.
Our hybrid ecosystem combines our cloud and on-premises resources, delivering control for solution scalability, security, and sustainability. It empowers us to incrementally add more features and objectives to our deployment solution without compromising customer value.
Our alerts predict roadblocks early, allowing project managers (PMs) to engage our customers in time to mitigate delays and effect change. Previously, the process had been influenced largely by the experience of our PMs. Delays and issues were handled retroactively at their discretion.
With our process deployment solution, PMs are forewarned to proactively handle most process deviations and unexpected events. They receive alerts in their project planning tool early in the process to allow for preventive actions. The recommended, best practice solutions empower them to eliminate or minimize delays that can be costly and frustrating.