Knowing the Data Is Half the Battle (Quality Digest)

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The other half is delivering the information to the right person

By Eric Weisbrod

“If only I had known.” This phrase has been uttered countless times by nearly everyone. Additional information or a different vantage point could help us know when to buy or sell stock (“I should have bought that Google stock at the IPO”), what birthday presents to buy (“I wish I knew their son already had that video game”), how we maneuver our vehicles (“Your friend could’ve told me he parked right behind me”), and many other instances in our personal lives. This desire for additional information is also found in the professional world, especially if you work in a quality position.

Knowing more information is generally a good thing, but knowing the “right” information is what really makes a difference when making decisions. What is the right information? That depends on the problem and your role in solving it. A quality director has different tools at her disposable than a quality manager, quality engineer, or line operator does. Knowing what information to collect, when to collect it, and how to present it is critical when making decisions in a manufacturing environment.

Same information, different audiences

In most manufacturing environments, companies collect data of some sort. These data may be required for regulatory purposes or customer requirements, or needed for product and process improvement. Regardless of the reason for collecting data, it’s critical to make that information available to the appropriate individuals in a format that allows them to make the best decisions based on those data. Here are some common examples of roles, the information that is displayed, and how it is used.

Shop floor operator

Data type. Direct measurements from processes or products. These values may be entered manually, collected from a measurement device, or automatically reported from something like a process loop control.

Data presentation. Data for shop-floor operators must drive immediate actions to continue making the products the company depends on. An extremely useful data presentation is a control chart that tells the operator when process adjustments should be made. This is a simple way of presenting data to individuals responsible for many other tasks and who need to know what action to take based on their data.

Data use. These data should be used to make process adjustments.

Quality engineer

Data type. Quality engineers most often use the same data set collected by the shop-floor operator.

Data presentation. Quality engineers will be very interested in process behavior, as can be seen in control charts, and will often want to extend beyond simple control charts as they strive for process improvement. Normalized control charts, group control charts, box and whisker charts, histograms, and Pareto charts are all ways for a quality engineer to make decisions about his process.

Data use. Quality engineers perform deep analyses with the goal of process improvement.

Quality director

Data type. Summarized and aggregate key process indicators are needed to give senior management an overall view of operations.

Data type. Because senior management often needs to evaluate data from many sites, processes, and suppliers, the ideal data presentation is one that can concisely summarize this information. Aggregated data in Pareto charts, line charts, box and whisker plots, and gauge displays are effective ways to summarize large amounts of information.

Data type. The primary use of these aggregated data is to make strategic improvements to help the business. These improvements may be with compliance, traceability, product giveaway, downtime reduction, and scrap, to name several.

Achieving results

The first step to improved data visibility at all levels is to begin collecting the data, with an understanding that more data isn’t necessarily the answer. Many pieces of equipment and systems are able to export data, so there is often a lot of “free data” available. This can be both a blessing and a curse. Make sure the data that are being collected are actionable and have been determined to be an indicator of your process or product performance.

Once the appropriate data are being collected, it is important to make those data available to those who need it in a format they can use. The best way to do this is with a central system that acts as the data collection repository and can present the data in the needed formats. A central system has many advantages:

Process improvement. With all data in a single repository, it is possible to compare data from different pieces of equipment, sites, vendors, and products without having to manipulate the data.

Traceability. A single repository makes it easier to find the needed results during an audit or for customer reporting. Anyone who has lived through these events knows that sifting through filing cabinets for results isn’t fun.

System management. A single quality system allows administration to be much simpler than maintaining multiple systems. Ideally, the quality system should be managed by the quality department so adjustments can be made to meet the ever-changing needs of the quality organization.

With a central repository, the data collection and reporting needs can be met with flexible tools to provide the necessary results. The same data repository can provide real-time control charts to shop-floor operators to make their data actionable, send email alerts to supervisors to alert them that an issue has occurred, provide notifications that collections are due to ensure compliance, and provide aggregate data to senior management to improve the company’s business.

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