Tuesday, June 22, 2021

The data-driven project manager: Using analytics to improve outcomes

With project failure rates remaining troublesome, many project managers are turning to data for help. Proper use of data can take the guesswork out of decision-making and provide tangible support project managers can use to guide their teams. Data can also prove value in helping project managers schedule work, allocate resources, increase efficiency, reduce costs, and more effectively manage risks.

The key means by which project managers leverage data is through use of business intelligence and business analytics. Business intelligence (BI) is a combination of software and process used to gather, store, and analyze big data from various sources and to convert that data into useful information. BI is considered a descriptive form of data analytics, in that it focuses leverages past and present data to glean insights into what has happened or what is currently happening in a particular process. BI gives companies and project management offices (PMOs) access to real-time metrics to support better and faster decision-making, and to achieve increased visibility into projects, processes, and their outcomes. 

Business analytics (BA), on the other hand, is considered predictive, in that it focuses on the “why” to help make more informed predictions about the future. With BA, data is analyzed to better predict challenges and adapt to provide improved outcomes.

Forward-thinking PMOs are recognizing the need for project decisions and actions to be supported by solid factual data. To become a truly data-driven project manager means stepping up your game in all aspects of project planning and execution — especially when it comes to allocating and managing scarce yet valuable resources.

Here is a look at how integrating data analytics into project management practices can greatly benefit project outcomes.

Matching, allocating, and scheduling resources

Resource management is a tricky area for project managers because resources are often scarce and always changing, making it difficult to plan and allocate resource usage in any given project, let alone when multiple projects compete for resources. Data is key in driving effective decisions around resource availability and allocation. The success of projects rests on being able to match skills, allocate the best resources, and schedule available resources.

Copyright © 2021 IDG Communications, Inc.

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