Data Collection: Is Too Much Data a Bad Thing?

The most successful organizations are ones that take a step back and analyze their data on a frequent, regular basis. They schedule time to interrogate their datasets using a variety of statistical tools and techniques—all in order to uncover new insights into how they can improve operations. Sometimes the most valuable information can come from innocuous datasets or even “in-spec” data.

For example, one beverage company that I worked with thought that, since everything was in spec, there were no opportunities for improving fill levels. After convincing them to gather fill volume data, we confirmed that no bottles were underfilled or overfilled. While that was good news, we also found that fill levels varied widely and that, overall, bottles were overfilled by a significant amount. Data analysis revealed operational differences between shifts, and big inconsistencies between fill heads and bottle types. Using these insights, the company made a variety of improvements, resulting in $1.1 million in annual savings—on just one of their 20-plus production lines. Without interrogating the data they would never have enjoyed these savings.

Ultimately, having data for the sake of having them does not lead to improvements. Extracting meaningful intelligence out of the data is what generates results—and organizations do not need every single measurement coming off their lines to do so. Instead, using intelligent sampling tactics, data collection activities can be both effective and efficient.

And now, thanks to the advent of software-as-a-service (or SaaS) technologies, there are even greater opportunities for improvement that extend beyond the four walls of a plant and across the entire enterprise. Using a centralized cloud-based repository, food and beverage manufacturers can easily consolidate quality data from multiple plants, regions, vendors, and even ingredient suppliers. Organizations can conduct the same regular data interrogation—but on a grander scale—and reveal greater opportunities to improve quality, reduce costs, and ensure standardization and consistency across the entire value chain, setting the stage for an exponential return on investments in quality.

Fair is chief operating officer of InfinityQS International, Inc. Reach him at [email protected].