Buffer

A buffer is a planned margin of time, cost, or resources added to a schedule or budget to absorb uncertainty and keep key commitments on track. Buffers may cover known risks (contingency) or unforeseen events (management reserve), and their use is tracked and controlled.

Key Points

  • Purpose: protect dates, scope, and budgets from normal variation and risk impacts.
  • Types: contingency for identified risks; management reserve for unknowns; schedule buffers such as project and feeding buffers in critical chain.
  • Placement and sizing: added at control points (e.g., end of critical path or before merges) and sized using risk analysis or historical data.
  • Governance: consumption is monitored; contingency is managed by the project manager, while management reserve typically needs sponsor approval.

Example

A construction project adds a 10% cost contingency and a 2-week project buffer at the end of the critical path. When a supplier shipment slips by 5 days, the team draws from the buffer, keeping the final completion date unchanged.

PMP Example Question

Which option best describes the primary purpose of a buffer in a project plan?

  1. Unused float that any activity can take without affecting successors
  2. Extra time or budget set aside to absorb uncertainty and protect commitments
  3. Overtime scheduled to accelerate critical activities
  4. Padding added by team members without analysis

Correct Answer: B — Extra time or budget set aside to absorb uncertainty and protect commitments

Explanation: A buffer is a planned allowance to handle variability and risks so that dates and budgets are maintained; it is not float, forced overtime, or unsubstantiated padding.

AI Systems with Claude, for Scrum Masters and Project Managers

Most AI pilots in project management do not fail on the model. They fail because somebody pointed the thing at a decision instead of at a task. This course is built around that distinction, and around the work that follows once you get it right.

Seven sections, taught against one running project from the first lecture to the last. You watch a system get built, then you build the same one against your own sprint. Nothing here is a demo that works only on the example.

You finish with five working systems and you keep them. The sprint report machine turns your board export and standup notes into the report you currently write by hand. The retro intelligence system tells you what the team keeps saying, not just what it said this time. The stakeholder comms engine drafts the update in the register the audience expects. The backlog health monitor flags the quiet decay nobody has time to check for. The risk and dependency tracker follows the chains that actually bite.

Seventy-six working files ship with it, across four sections, so every system is built against real sprint data rather than material invented for a slide. Four sprints of retrospectives, board exports, standup notes, backlog and risk data.

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Build the Sprint Reporting System, Not Another Prompt

AI Systems with Claude is our own course for Scrum Masters and Agile Project Managers, taught against one running project across seven sections. You build five working systems and keep them: the sprint report machine, the retro intelligence system, the stakeholder comms engine, the backlog health monitor, and the risk and dependency tracker. Direct from HK School of Management, not on Udemy.

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