Why is Analytics important for Project Managers?
Data-driven approach is endorsed by many and utilizing the available analytical tools as well. But most project managers either are unaware of the analytical approach or they do not feel comfortable to change from their subjective approach to project management decision-making. The uncertainty is because of the lack of training in the analytical tools, technologies and processes.
Also, the high availability of the latest analytical techniques can enable project managers to the analytics paradigm to break down the processes in complex projects to predict their behaviour and outcomes. Project managers can use this predictive data for better decision-making. Analytics enables project managers to analyze the captured data to comprehend patterns and trends. The understanding to determine how projects perform and what type of strategic decisions should be made can be studied, to improve the success rate of the projects.
Effective project management considers efficient management of uncertainties and risks of the project as a must. Project managers, in today’s existence, need to use analytical techniques to monitor and control the risks as well to analyze project schedules and costs in order to maintain accurate records with the analytics-driven approach. Project-based information with analytics can enable project managers and executives to measure, observe and analyze project performance and encourages better decision making and commitment based on facts.
How can project managers take advantage of a data-driven approach to enhance project outcomes?
- Assisting Strategic Decisions:
Analytics aids in decision-making based on facts. Analytics let managers and executives build a stronger understanding of how the in-progress and upcoming projects can fit into the overall vision of the organization.
- Capturing Projections and Early Signals:
With analytics, managers and executives can watch out for early signs of declinations in terms of budgets and timelines so that the decisions can be made accordingly. Analytics helps managers capture the rate of wor. This makes the predictions easier to analyze the estimated time.
- Quality of Deliverable:
As a project manager, you need to comprehend how analytics can reduce your workload, improve processes and enhance the outcomes of your project. Quality is one such ultimate measure of your project’s success upon delivery. Analytics guide you plan, monitor and review the quality throughout your project.
- Managing Data Overload:
Data overload has affected project managers’ capability to capture meaningful information from the vast data available. Analytics can help project managers overcome this issue.
- Enhancing Data Visibility and Control:
An analytics perspective can help in providing a project manager with an entire picture to look into and determine how each project and its project team members are performing. This data comes into the role while prioritizing project tasks and/or moving project team members around to maximize productivity.
- Manage project risks:
One of the areas where Analytics can act as the most important and useful factor is project risk management. Prioritization, project risk identification and ranking depends upon multiple factors which includes
- Size and complexity of the project
- Organization’s risk tolerance
- Risk probability, impact, and horizon
- Competency of the project or risk manager
Here, predictive analytics models are used to analyze the mentioned multiple factors for making rational decisions to manage the risks effectively.
- Predict project schedule delays and cost overruns:
Analytics can also talk about the project’s schedule and tell if it’s under or over budget. Also, analytics allows a project manager to predict the impact of various completion dates on the bottom line (project cost).
- Improve project processes:
Project management includes the execution of multiple project processes. The continuous process improvement is a necessity to eliminate waste and improve the quality of the processes and the product of the project. Improvement projects include four steps:
- Understand and simplify the current situation
- Determine the target spot
- Perform gap analysis
- Make improvement decisions to address the gap
- Improve project stakeholder management:
Analytics helps to improve project stakeholder management by enabling a project manager to predict stakeholder responses to various project decisions.
- Analyzing project portfolios for project selection and prioritization:
Project portfolio analysis one of the most useful applications of analytics. This involves evaluating a large number of project ideas, the selection process and the prioritization, the most viable ones within the constraints of organizational resources and other relevant factors.
“Data isn’t useful without the product context. Conversely, having only product context is not very useful without objective metrics…” – Jonathan Hsu
Provided all the reasons to say that Analytics is important and necessary for Project Managers and Senior Executives, it only makes sense to use more powerful tools involved in creating a longer sustainable competitive edge. The analytics involved in project management approach varies from organization to organization and project to project. The analytical approach for a project can majorly depend upon a multitude of factors like organizational culture, policies and procedures, project environment, project complexity, project size, available resources, available tool and technologies. Also, heavily depends upon the skills, knowledge and experience of the project manager or senior analyst executives.
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