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Question 5/14
What is a mirror metric for % Rework in the context of Value Stream Mapping?
Correct Answer: B
The correct answer is B because "% Complete and Accurate" is effectively the mirror metric of "% Rework." In value stream mapping, teams need to understand not only how long work takes, but also the quality of the work as it moves between steps. If work arrives incomplete, incorrect, unclear, or unusable, downstream teams must spend time clarifying, correcting, or repeating work. That creates rework, delays, queues, frustration, and reduced flow efficiency.
"% Complete and Accurate" measures the proportion of work that can proceed without needing correction or additional information. A higher complete-and-accurate percentage indicates better upstream quality and smoother flow. Conversely, a high rework percentage indicates that defects, missing information, poor requirements, weak handoffs, or inadequate validation are causing work to loop backward through the system.
The other options are not the correct mirror metric. Unplanned work and planned work describe work-type allocation, not quality of transfer. Repeated work is similar in meaning to rework, but it is not the recognized inverse measurement. Relevant study guide references: Measuring to Improve; Value Stream Mapping; Measuring to Learn; Becoming a DevOps Organization.
"% Complete and Accurate" measures the proportion of work that can proceed without needing correction or additional information. A higher complete-and-accurate percentage indicates better upstream quality and smoother flow. Conversely, a high rework percentage indicates that defects, missing information, poor requirements, weak handoffs, or inadequate validation are causing work to loop backward through the system.
The other options are not the correct mirror metric. Unplanned work and planned work describe work-type allocation, not quality of transfer. Repeated work is similar in meaning to rework, but it is not the recognized inverse measurement. Relevant study guide references: Measuring to Improve; Value Stream Mapping; Measuring to Learn; Becoming a DevOps Organization.
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