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Statistical Project Management in Action, Parts I & II: Measuring Project Volatility and Applying Core Concepts

  • ID: 4833871
  • Report
  • December 2019
  • Region: Global
  • Cutter Consortium
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Successful project planning requires a balance between the desire for project managers to have simpler project plans that require less effort to maintain and the desire for senior management to have measurable project performance.

The two-part Statistical Project Management in Action series introduces a framework that uses basic numeric methods from statistics, especially the concept of variance, and adapts them to project management.  You’ll discover a rich set of metrics that will help you keep close tabs on all projects, especially the renegades.

Part I of the series focuses on measuring project volatility. It explores why project volatility is so difficult to detect, sheds light on the limitations of current approaches for controlling volatility, and discusses how to apply eight project-volatility measures that work as metrics in action for project planning. You’ll get the help you need to detect project volatility earlier in the lifecycle, facilitate management intervention without burdening the project management team, and quickly visualize how much volatility is being injected on a project each day. Learn more about Part I: Measuring Project Volatility.

Part II of the series - scheduled for publication in December 2019 - will bring together all of the core concepts of Statistical Project Management (SPM). You’ll learn how to create a customized list of object types, use a project-evaluation rubric, and infer project growth through analysis of the project behavioral data. Part II: Applying Core Concepts will also explore the differences between SPM and classic project management techniques - SPM does not model dependencies - and discuss how to handle staff resource contention.

Part II will help you:

  • Choose how heavy you want your project management methodology to be
  • Err to the side of simplicity
  • Gain an equispaced measurement trap for monitoring human behavior within projects
  • Understand the challenges of expressing objects
  • Describe objects and assign them to the right object types
  • Space out the measurement model across all aspects of a project - objects, tasks, milestones
  • Successfully model system testing within a project plan
  • Examine how projects grow
  • Gain daily insights into what causes project behavior, and design project interventions quickly
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