Automated Project Office (APO) is a predictive analytics IT management solution that reduces project costs by up to 40% and improves team productivity by 30% through early identification of potential issues. APO monitors key risk measures like rework prevention, task clarity, process adherence, and management participation to provide real-time visibility into project risks. Customers report that APO significantly increases confidence in successful deployments by enabling early course corrections to prevent major problems.
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Apo predictive analytics
1. Predictive Analytics
Results through Automated Project Office SM
Automated Project Office (APO) is an IT management solution that reduces project
development costs by up to 40% by preventing rework. At the same time, APO optimizes
team productivity by up to 30%. APO’s Predictive Analytics drive these improved outcomes
based on:
• Early operational insight into potential issues
• Enforced defined processes
• Highlighting anomalies from historical trends, data, and metrics
• Acceleration of the adoption of enterprise standards and best practices
THE APO DIFFERENCE
APO’s Predictive Analytics is a step above traditional project management and portfolio
management solutions. Dashboards provide an executive-level view of emerging risks at both
the portfolio and project levels. APO’s Predictive Analytics measures include:
• Rework Prevention Level (RPL). Since rework
accounts for approximately
40% of IT project costs,
rework prevention provides
tangible cost savings.
Rework prevention also
drives increased stakeholder
and sponsor satisfaction.
• Specific, Measurable,
Accountable, Relevant, &
Timely (SMART)– Clarity of Task
Assignments. If the project
team members don’t have
clear and specific assignments,
the likelihood of successful
project delivery drops dramatically.
• Process Adherence Level (PAL). If the organization’s standard processes are not being
followed, project success decreases and project cost increases.
• Senior Management Participation Level (SMPL). A powerful early indicator of project
success or failure is the level of senior management commitment.