Beacon Quality Blog

Organizations just getting started with layered process audits typically focus on basic metrics like audit completion rate and overdue corrective actions. As they progress along their digital transformation journey, however, they could be getting more value from these specialized audits by asking more complex questions.

Executed correctly, layered process audits (LPAs) take place every shift, generating hundreds of data points daily. Multiply that out over the course of a year, and it’s clear that manufacturers have some pretty robust data sets at their fingertips.

Managing these vast quantities of data can be difficult when relying on spreadsheets and other manual data analytics tools. An automated LPA platform integrated with business intelligence tools like Tableau and Power BI makes it much simpler (even if many analyses still require having an analyst or data scientist on staff).

With that in mind, let’s look at some examples of how manufacturers can leverage deeper insights from the volume of data they collect daily.

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According to a recent LNS Research survey, 37% of quality leaders cite an inability to measure quality metrics as their number one barrier to achieving quality goals. Even worse, the survey showed a full 4 in 5 companies have poor visibility into real-time metrics.

These figures highlight a central problem in quality management: in an era of increasingly large data sets, how can manufacturers leverage this data for meaningful improvement?

It’s a question that’s especially relevant for manufacturers engaged in layered process audits (LPAs), a high-frequency verification strategy where teams conduct short audits every shift. With hundreds or even thousands of audits taking place over the course of a year, making sense of a large volume of data is a core challenge of LPA programs.

While plant managers often track metrics at a granular level, director and VP-level leaders need to look at the data a little differently at a higher level. Let’s look at four of the most important enterprise-level layered process audit metrics to track. 

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Implementing layered process audits (LPAs) in your facility can mean conducting hundreds of audits every single month, a process that generates a large volume of quality data.

As manufacturers lean into Industry 4.0 initiatives, that volume of data is only growing. But according to Forrester, up to 73% of data within businesses never gets analyzed.

How can automotive and aerospace manufacturers leverage more of their LPA data to maintain steady progress towards their quality goals?

The answer lies in dashboarding, which allows teams to keep their most important metrics front and center for more effective communication and goal-setting. This post looks at some of the most critical numbers to focus on in order to ensure your LPA program is effective at driving down defects, complaints and costs.

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