The importance of data analytics in project management

1. Artificial Intelligence is key to data analytics in
giving suggestions to improve the project
success rate throughout the project lifecycle.
Business intelligence refers to the procedural
and technical infrastructure that collects, stores,
and analyzes the data produced by a company's
activities.
Business analytics refers to the skills,
technologies, and practices for continuous
iterative exploration and investigation of past
business performance to gain insight and drive
business planning based on the data derived.
Every company thrives in its business when there is proper project management in place. This, however, is seen seldom, because
of the large amount of project failure rates. Project managers have slowly run out of options but to turn to data and data analytics for help.
The importance of data analytics in project management
Digital Projects
Matching resources
Allocating the best resources to the
Scheduling available resources.
Managing real time data
Managing risks, issues and test cases,
etc.
stakeholders
Features of Digital Projects in KTern.AI
KTern.AI Digital Projects UVP Impact of data analytics on
project managers
AI, BI and BA
Roles and responsibilities of a project
manager
Everyday work item analytics
Test analytics
Business process insights
Sprint reports
Project signoff reports
Project and process reports etc
Smart project charter and Intelligent risk
management to improve the
Communication and Scope control for the
Project Execution.
Project auto-simulation planner and
Timeline auto-tracker with insights for
better version management linked to the
Project Milestones.
Sign-off approval auto-orchestrator and
Q-gate auto-integration for conformance
to compliance and auto validations.
The project manager has the highest
dependency in line with project
management.
This encloses the initial process of
project planning to proper
management through all the phases of
the project until project completion.
Talking about projects of any altitude,
a large project like a conversion project
from ECC to S/4HANA has much more
elaborate and stretched list of
deliverables, and without data
analytics, it would turn tedious.