Knowing how to effectively leverage data to benefit projects and programs is important, but there is often a lack of awareness about how to implement it and the benefits it can bring. In this article, Benson Mafudze and Connor Smith of AECOM Data Advisory outline his five ways project managers can use data analytics to improve project performance.
Given the speed at which technology and data regulations are advancing, and the large amount of off-the-shelf software that is expected to revolutionize today's projects, there is a growing need for administrators to capture, store, and visualize data. It's natural to have a hard time choosing the most effective method.
That's why a deeper understanding of the processes and efficiencies that data empowerment brings can provide exponential benefits.
Here are five effective ways to use data analytics.
1/ Make data easier to access
As a data specialist, interpreting vast amounts of data from tables and graphs comes naturally. But for others, including project stakeholders, that information may not be so simple. This is where business intelligence (BI) tools for data visualization come in handy.
When used effectively, BI visualizations can help you communicate your project's reports in a clear and easy-to-understand format. These tools not only make data easier to access, but they also provide a more unified workspace with customized dashboards for each stakeholder group and review session, allowing cross-team collaboration. Collaboration can be improved.
2/ Provide a single source of truth
As a project manager, the overall success of the project ultimately rests on your shoulders.
Effective use of data analysis principles in conjunction with regular reporting increases a sense of control and accountability across project teams.
Eliminate the occurrence of rogue files stored on your desktop, increase protection via cloud storage, and ensure data access across projects with a single reporting dashboard suite .
3/ Employ trend analysis to gain critical insights
One of the most obvious data analysis principles that can be applied to project data is trend analysis. This is a strategy used to predict future results based on past data.
Trend analysis not only helps identify positive outcomes, but also allows project managers to address issues before they escalate.
Additionally, custom analytics within digital reports can be configured to automatically update each of these key metrics whenever new data is updated, instantly generating a headline view of key performance indicators.
4/ Integrate your data into a unified platform
Because data is often stored in numerous databases, software packages, and traditional corporate servers, report creation often requires hours of copying, pasting, and formatting slide packs.
BI software like Microsoft Power BI and Tableau allow users to load and transform data from a seemingly endless list.A database such as Azure.
This, combined with a robust data model, enables comparison and analysis of datasets that would normally be difficult.
5/ Early action means early results
The main challenge faced by project managers, especially when participating in program projects in a troubleshooting role, is trying to achieve results quickly.
Once a project begins, it can be difficult to spend time adjusting processes and practices. By engaging with a data specialist early to define project-specific analytical outputs, you can implement data-driven solutions faster and more effectively. Stakeholders can expect more informed decisions, increased efficiency, and better team integration from the start, leading to improved outcomes and improved outcomes.