Agile for Project Control
Agile provides greater opportunities for control and risk management and offers unique benefits that traditional methods miss, such as:
They are all complex real-world problems being solved with applications of intelligence (AI). This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.
- Transparency with daily standup meetings discussing work status, risk, and pace.
- How a clear definition of done drives acceptance by all key stakeholders.
- Measuring performance and benefits of working solutions during project delivery.
- Iteratively testing to gain authentic feedback on solution requirements and stability.
- Regular retrospectives that drive continuous improvement into the team.
In this course, you will learn how these levers of control far exceed traditional management methods of earned value management (EVM), which relies on estimates and no changes in scope. We'll discuss how the key to unlocking the control potential is to learn what to manage, and how to measure it.
This answer varies across levels of management, separating the concerns between the organization and the team. For the organization, the focus is on what capabilities are delivered and how to measure return on investment (ROI) capabilities provide. For teams, it’s a focus on team velocity and how to ensure its measurement is useful for diagnosing internal and external productivity constraints.
No Need to Travel
28 February 2019
2-3 hrs effort per week/module
- Agile systems engineering to ensure valuable, integrated solutions
- Controlling projects through actual measurements vs. estimates (e.g. EVM)
- Essential methods for managing People, Process, and Product on empowered teams
- How to always be closing (ABC) with every project increment using a definition of done/li>
- Enterprise alignment: how and why strategic plans, portfolio optimization, and project management can align with simple metrics, with facilitative leadership
- How real-world constraints and agile simplify portfolio management and decision science methods: go beyond LP, IP, and Genetics-based Search
Week 1: The first week of the control course examines the reason for controlling projects, why traditional controls such as Earned Value Management fail so often, and the three key components to any controlling process: value, constraints, and verification. Systems Engineering models are considered for their effectiveness in controlling, with an emphasis on the predominant controlling approach, the V-Model, and how it equivocates testing with development.
Week 2: The second week examines how control is managed across the project lifecycle, with the three Ps of management: people, process, and product. Real-world approaches and tools are discussed for all three levers across varying staffing approaches, release and sprint processes for quality assurance, and the use of product-level tools for quality control.
Week 3: The third week drives home the need to “begin with the end in mind” by closing User Stories incrementally using a Definition of Done that links the three Ps together across each sprint cycle (planning, execution, and control).
Week 4: The final fourth week addresses controlling Agile processes at scale, from sampling and building intuition across Agile team ceremonies, to managing team decisions and performance, and even portfolios of projects using simplified metrics. The fourth week will also look at how to align portfolio and project management metrics to an organization’s strategy as a means of managing up the risks of being defunded or constrained by corporate policy.