Significance of Data Management in improving Project Management

significance of data management in improving project managementDid you know in the past 3-4 years, the market for data and business analytics has been increasing by generating a revenue amount of ₹558 millions?

In the field of Project Management, data analytics is now the key element in the framework. Collecting relevant data, preserving the important aspects of it, and converting this data to  valuable insight for the project can lead to enhanced project risk management.


Data has a significant impact on the project outcomes and helps further simplify it for the clients. Once the importance of data is evident, it is important to know what Data management is and how to be efficient in it. “Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization” – This being said, Data management holds a vital role for a project manager. Analyzing and managing data reduces the complexity of projects, thus making decision-making easy for a project manager.


Consulting Engineers Association of India gives quick insights about the importance of data and data management for a project manager:

importance of data

  • Project risk evaluation: 

Risks are a part of each project. When you start a project, it is necessary to evaluate each and every step involved in it – which is also a risk assessment to further simplify the project as a whole. There are all sorts of different risks attached to different projects and assessment of these risks can be done through data management. Data analytics and data management allow the project manager to identify, rank, and prioritize the risks following a particular project – hence allowing management and project execution easier.

While assessing the risks for a particular project, the following elements are to be considered;

  • Size and project’s complexity: The more complex the project, the more the risks it is surrounded with. The project manager should be well aware of the size and intensity of the project while assessing the risks. This helps in better and more focused data collection and then one could better analyze the data based on the wished outcomes.
  • Client’s level for risk tolerance: How much a client is willing to risk and put his investment at stake to gain the desired results says a lot about the project’s importance and the client’s willingness to achieve the set objectives. Through this, the project manager can also determine the financial willingness of the client for unforeseen events during the project. Hence here, collecting and analyzing the financial elements related to the project can reduce the risks linked.
  • The competence of the project manager: The leadership skills, the decision-making power, the proper execution of the planned elements, team management, communication, and critical thinking helps the project manager to get through the project successfully. It is important to assess the competencies of the project manager in order to run the project smoothly and successfully
  • Forecasting Data beforehand:

Right data collection and analysis can be an added advantage for project managers to evaluate the early risk events in terms of budget, quality of the outcome, the time frame and the planning. Hence the forecasting of data beforehand can go a long way to modify, adjust and eliminate any elements of the project.

  • Measuring Success:

Some decades ago, the process of measuring success through sales or voluntary customer data, such as surveys or reviews was a bit difficult due to various factors. Now the organizations have the capacity to recognize greater about their clients than ever before through information mining. This helps the task managers to scrutinize massive quantities of facts to look for trends. Finding useful traits allows assignment managers to create success initiatives.



data mistakes to avoid

  • Data mistakes to Avoid

These are a few data mistakes a project manager can avoid while managing data:

  • Collecting Irrelevant data: The first query a project manager should ask themselves as they’re searching for facts in data is if the information relevant. There’s an enormous amount of information available and thus it the manager should be able to filter what data is important to the project at hand.
  • Not leveraging that data : Once the relevant facts has been gathered, the a company should learn to leverage that data quickly, in order to have a competitive edge.
  • Conclusion

Statistics and data management can be useful to project managers in a lot of ways if used within the right manner. But it is also important to keep in mind that not all facts are applicable or relevant to the project and it has be segregated to find traits and data this are useful for the team.


Check out this artcle by Consulting Engineers Association of India on Women in leadership role for Engineering consultancy sector to understand the issues faced and impacts of female leaders in the sector.


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