Agile, Hybrid and Predictive approach by Industries
Understanding the Project Life Cycle; What is Monte Carlo Analysis?
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☝️ Agile, hybrid and predictive approach use by industries
🔮 Understanding the Project Life Cycle
💼 What is Monte Carlo Analysis?
💡 Recommendation zone
Agile, hybrid and predictive approach use by industries
When broken out by industry, there are wide gaps in the use of agile, hybrid and predictive approaches, further indicating that organizations are using the approach that best suits their projects.
These variations by industry, coupled with conversations with subject matter experts around the world, indicate that organizations are choosing the ways of working that best meet the increasingly complex needs of each project and help them balance predictability with uncertainty and innovation in an ambidextrous fashion, where agile, hybrid and predictive approaches coexist and are adopted depending on the business needs and strategy.
Financial services organizations are most likely to report using agile always or often (58%) and least likely to use predictive (45%). On the opposite side of the spectrum, construction organizations are least likely to use agile (27%) or hybrid (37%) and most likely to use predictive approaches (76%). Information technology (55%), healthcare (53%) and financial services (53%) are most likely to use hybrid approaches.
source: PMI Pulse of profession report 2024
Understanding the Project Life Cycle
The project life cycle is a fundamental concept in project management that outlines the stages a project goes through from initiation to closure. Understanding the project life cycle is crucial for project managers and team members as it provides a structured approach to planning, executing, and completing projects. This article delves deeply into the phases of the project life cycle, exploring their significance, activities, and best practices.
Phases of the Project Life Cycle
1. Initiation
Overview:
The initiation phase marks the beginning of a project. This phase involves defining the project at a high level and obtaining authorization to proceed.
Key Activities:
- Project Charter Development: Creating a document that formally authorizes the project, outlining its objectives, scope, stakeholders, and high-level requirements.
- Feasibility Study: Assessing the viability of the project in terms of technical, economic, and legal feasibility.
- Stakeholder Identification: Identifying individuals and groups with an interest in the project and understanding their needs and expectations.
- Initial Risk Assessment: Identifying potential risks and high-level strategies to mitigate them.
Best Practices:
- Clearly define the project’s purpose and objectives.
- Engage key stakeholders early to gather input and secure support.
- Conduct thorough feasibility studies to ensure the project is viable.
2. Planning
Overview:
The planning phase involves developing a detailed roadmap for achieving the project’s objectives. This phase is critical for setting the foundation for successful project execution and control.
Continue reading here: The PM Newsletter
Picture source: resourceguruapp.com
What is Monte Carlo Analysis?
It is a potent risk management tool that is used to conduct a quantitative study of risks in project management. Project managers can evaluate the possible impact of risks on their projects using this mathematical technique, which was created in 1940 by the renowned atomic nuclear scientist Stanislaw Ulam.
In essence, it aids project managers in comprehending how particular risks may impact project budgets or deadlines. Project managers can assess the possibility of various situations by using Monte Carlo Analysis to acquire useful insights into a range of potential outcomes and probabilities.
Consider a situation where you don't know how long a project will take. The time required to complete each project activity is, however, roughly estimated in your possession. In this circumstance, you may use Monte Carlo Analysis to provide both a best-case (optimistic) and worst-case (pessimistic) scenario for the length of each work.
Let's consider these combinations:
If every work is accomplished by the optimistic deadline, there is a 5% probability of finishing the project in 10 months.
A 20% likelihood exists that it will be finished in 12 months.
The likelihood of finishing in 14 months is 35%.
98% of the time, the project will be finished in 16 months.
100% of the time, the project will be finished in 18 months (assuming the worst-case scenario).
Having access to this data allows project managers to more accurately predict the project timeline and facilitates more efficient project planning.
🎯Merits:
Early Indication: Gives early indications of the propensity to meet project deadlines and milestones.
Realistic Budget and Schedule: Facilitates the development of more precise and realistic budgets and timelines.
Identifying Overruns: Identifies potential schedule and expense overruns and forecasts their likelihood, assisting in pro-active risk reduction.
Influence Evaluation: Quantifies risks to allow for a thorough evaluation of their potential influence on the project.
Decision-Making Based on Objective Information: Offers objective information to aid in making decisions on how to carry out a project.
🎯De-merits:
Triple Estimates: Requires three estimates for each activity or factor being studied, which might take a lot of time.
Reliability of Estimates: The analysis's accuracy depends on the accuracy of the estimates given, underscoring the value of precise information.
Project-level analysis: Monte Carlo simulation illustrates the overall probability for the entire project or significant subgroups (such as phases). It is not permitted to analyze particular risks or activities, thus the project's scope must be carefully considered.
Join the discussion on this topic here: LinkedIn discussion
Picture source: projectmanagementacademy.net
Recommendation zone
Harness the Power of AI in Project Management: Artificial Intelligence is revolutionizing project management, offering unprecedented benefits and efficiencies. PMI's enlightening article, "The Benefits of AI for Project Management," explores how AI technologies can transform your project management practices.
Uncover the Evolving Role of the Project Manager: The landscape of project management is constantly changing, and staying ahead means understanding these shifts. Dive into PMI's insightful article, "The Role of the Project Manager," to explore how the role is evolving and what it means for future project leaders.
Embrace the Fit-for-Purpose Approach in Project Management: Adaptability and purpose-driven strategies are crucial for success in today's dynamic business environment. PMI's insightful article, "Project Management Embraces the Fit-for-Purpose Approach," delves into how this methodology transforms project management.
Contributor: Markus Kopko, continue reading here: Article
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