Data Analytics in Project Management

Managing projects means making decisions. To make the right decisions the process needs to be supported by data mining and machine learning techniques.

Data is one of the most significant aspects of any organization. There are two means by which project managers leverage data- business intelligence and business analytics. Using analytics, helps managers and executives to keep a watch for early presagesof in terms of budgets, costs, and timelines and take corrective action. Analytics also helps managers capture the rate of work, so they can easily predict the timeline for their projects.

The ability to analyze the performance of a project objectively, and make rational and informed decisions, plays a huge part in a project’s success.

The right Project management needs to have accurate planning, tracking, and analyzing the progress of a project. Today, project managers have a wide range of project metrics to manage, measure, observe and analyze the performance of their projects. 

Analysing Project Portfolios

Across all organizations, there is competition from multiple projects for a limited number of resources. By conducting a project portfolio analysis, firms can evaluate a large number of project proposals and select those that are most viable given the organization’s constraints. Each project can be assessed against a wide range of assessment criteria to determine its viability. This includes:

• Technical, economic, legal, capability, and capacity restraints
• Resource requirements
• Project complexity
• Project risks
• Training requirements

Careful analysis can help organizations select and priorities projects that allow for the optimal allocation of finite resources. This helps the organization select the projects that are beneficial for the organization and help them to grow.

Managing Project Risks

Every project has inherent risks, but incorporating data analytics into the project management process can allow you to identify, rank, and prioritise those risks. Any analysis of the risks facing an organisation should include the following factors as a bare minimum:

• Size and complexity of the project
• The organisation’s risk tolerance
• The competence of the project or risk manager

This level of risk identification and analysis will allow the organisation to mitigate the likelihood of a particular risk occurring and predict the possible effects if the risk does occur.

To understand Analytics in Operations and Project Management and help the organization grow it is important to have the right knowledge set. To be able to understand the process more clearly, executive education is of great importance. MDI Gurgaon in collaboration with Hughes Global Education has launched the Advance Programme in Operations and Project Management. The course is designed to facilitate the overall development of young professionals by introducing them to advance concepts of operations management and project management, including deep insights into IT and materials management.