Why Manufacturing Data is Failing the Shop Floor

Formic argues that manufacturers must stop collecting 'supposed to' metrics and start aligning data with the specific roles and goals of their operations teams.

The FPI platform emphasizes customer-driven metrics, built around the genuine needs communicated by manufacturers.
The FPI platform emphasizes customer-driven metrics, built around the genuine needs communicated by manufacturers.
Formic

In today’s manufacturing environments, due to the proliferation of sensors, dashboards, and automated KPIs, data is everywhere. Then why is the universal feeling among packaging and processing manufacturers one of frustration? Whether companies and their operators are willing to admit it or not, just because they have the data, doesn’t mean they are sure if it’s the right data, and they certainly don't feel like they're using it effectively. Call it a data paradox.

This was the core message delivered by Molly Garrison, a Product Manager at Formic, during her PACK EXPO Las Vegas Innovation Stage session “From Data Overload to Insight: What Manufacturing Teams Really Need to See.”

"The majority of companies that I have spoken with or worked for do not feel like they’re doing the best job they can do," Garrison said, drawing on her extensive background on the shop floor and in operations. "It doesn't matter whether you are a really big company or a small single-facility company."

Collecting data just because it’s there Many organizations chase metrics simply because they can be collected, or because they are perceived as necessary—what Garrison called, the 'supposed to' data.Many organizations chase metrics simply because they can be collected, or because they are perceived as necessary—what Garrison called, the "supposed to" data.Formic

Garrison believes the current state of manufacturing data is characterized by overload and misalignment. Many organizations chase metrics simply because they can be collected, or because they are perceived as necessary—what she calls, the "supposed to" data. This focus diverts attention from the operational pain points that truly keep teams up at night: staffing challenges, order fulfillment pressures, and the sheer flood of disconnected information.

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