HKSM

A technique that compares actual technical metrics against planned targets or thresholds to detect variance, forecast capability, and guide decisions. It supports timely corrective or preventive actions so the solution meets its requirements.

Key Points

• Compares measured technical parameters to baselined requirements and interim targets.
• Uses thresholds and trend analysis to provide early warning and forecast performance.
• Focuses on parameters such as capacity, latency, accuracy, reliability, weight, power, and safety.
• Integrates with requirements, quality, risk, and change management to inform decisions.
• Produces actionable outputs such as variance reports, forecasts, and change requests.
• Performed iteratively at reviews, sprints, and major milestones.
• Relies on objective measurement methods, valid data, and consistent units.

Purpose of Analysis

• Validate that the solution is progressing toward meeting technical requirements.
• Detect deviations early to reduce rework, cost, and delivery risk.
• Provide evidence for trade-off decisions across scope, quality, cost, and schedule.
• Support timely risk identification and mitigation for emerging technical shortfalls.
• Increase stakeholder confidence through transparent performance reporting.

Method Steps

• Define measurable performance parameters and acceptance criteria traceable to requirements.
• Establish baseline values, interim targets, and decision thresholds.
• Plan how and when each parameter will be measured or modeled, including tools and data sources.
• Collect and validate measurements at planned intervals under representative conditions.
• Analyze variance and trends; model impacts and forecast future performance.
• Assess implications for scope, schedule, cost, compliance, safety, and risk.
• Recommend corrective or preventive actions; raise change requests as needed.
• Communicate results and update baselines and plans once changes are approved.

Inputs Needed

• Product requirements, specifications, and quality criteria.
• Technical baseline and configuration documentation.
• Measurement and test plan with methods, tools, sampling, and timing.
• Actual measurements, test results, simulations, and prototype data.
• Thresholds, control limits, and acceptance criteria.
• Assumptions, constraints, and operating conditions.
• Risk register, issue log, and change log.

Outputs Produced

• Variance analysis reports and annotated trend or control charts.
• Forecasts of technical capability and estimates to achieve target performance.
• Recommended corrective and preventive actions.
• Change requests and updates to requirements, designs, or test plans.
• Updates to the risk register and issue log.
• Stakeholder communications and information radiators.

Interpretation Tips

• Confirm data quality, calibration, and environmental conditions before acting.
• Look for sustained trends, not single points; investigate special-cause variation.
• Evaluate system-level trade-offs to avoid optimizing one metric at the expense of others.
• Use consistent units and definitions across teams to prevent false variance.
• Align conclusions with stakeholder priorities and business value, not just technical elegance.
• Update thresholds as understanding matures, but avoid moving targets without governance.

Example

A team developing a handheld device must achieve 10 hours of continuous operation. Early tests show 8.5 hours, then 9.2 hours after firmware optimization. Technical performance analysis compares results to the 10-hour target, projects the trend, and indicates the requirement will be missed without additional action. The project manager facilitates a trade-off on battery capacity versus weight and schedule, submits a change request for component substitution, and updates related risks.

Pitfalls

• Vague or non-measurable performance parameters.
• Test conditions that do not represent real operating environments.
• Uncontrolled changes to baselines and thresholds.
• Cherry-picking data or confirmation bias.
• Optimizing metrics in isolation and ignoring system impacts.
• Waiting until late stages to analyze, when fixes are costly.
• Overreacting to noisy data and creating churn.

PMP Example Question

During execution, measured reliability is below the interim target and trending downward. What should the project manager use to compare results with targets and predict whether the requirement will be met?

1. Technical performance analysis
2. Earned value analysis
3. Stakeholder engagement assessment
4. Procurement performance review

Correct Answer: A — Technical performance analysis

Explanation: This technique compares actual technical metrics to planned targets and forecasts future capability. EVM focuses on cost and schedule, not technical parameters.