A quality system for IoT quality monitoring that exists only for the auditor produces paperwork, not quality. Inspection catches problems in this strand of quality and productivity management; it does not prevent them. The professional literature on the quality and productivity management capability converges on a small set of controls that reliably work. The course gives participants a defensible structure for IoT quality monitoring and the judgement to adapt it. The programme works equally well for those formalising this aspect of quality and productivity management for the first time and those improving an existing approach. Exercises escalate in difficulty, ending with the ambiguous situations that make the quality and productivity management capability hard in practice. Most organisations already have a policy on IoT quality monitoring; far fewer can show it working. Participants take away a working set of documents supporting this area of quality and productivity management, ready to be adapted internally. The final module sets out how progress on this aspect of quality and productivity management will be evidenced six months later.
Expected Learning Outcomes
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Identify the sources of variation in IoT quality monitoring and rank them by effect.
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Recognise early indicators that IoT quality monitoring is drifting away from its intended design.
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Set the minimum documentation for IoT quality monitoring that is genuinely necessary, and stop there.
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Build capability in root cause analysis across the team handling IoT quality monitoring.
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Design a training and briefing approach that sustains competence in IoT quality monitoring.
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Reduce waste and non-value-adding steps in IoT quality monitoring.
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Map the process behind IoT quality monitoring as it is actually performed.
Who Should Attend
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Analysts producing the data on which decisions about IoT quality monitoring rest.
