Part two of this discussion continues the argument that all businesses should collect enough manufacturing data to improve decisions and process performance.
Why digital data matters
Process automation is fundamentally about controlling and monitoring manufacturing events. When parts of the process are disconnected and cannot use upstream or downstream data, productivity gains erode.
The article makes a strong claim: any manufacturing data that is not stored electronically is effectively dead data. Dead data is expensive because it cannot be easily aggregated, analyzed, or used to improve operations in real time.
The hidden cost of paper
The cost of paper-based operational systems is significant: - creating SOPs, work instructions, and forms - issuing paper logbooks and forms by shift or area - gathering, sorting, scanning, and storing completed paperwork - managing long-term storage through internal effort or outside vendors
Paper pages may be individually useful, but they do not naturally become a living operational dataset.
What electronic data unlocks
Once data is digital, it becomes reusable and analyzable. The article highlights several categories of value:
Descriptive analytics: Electronic records make it possible to look backward and understand what happened.
Predictive analytics: Stored process history can be used to identify patterns and forecast performance based on variables like crew, time of day, season, raw material supplier, or facility.
Review by exception: If all relevant data is captured digitally, controls can be applied in real time. Supervisors can be alerted when something drifts outside of an acceptable range instead of reviewing every page manually.
Technology paths forward
The article points to practical ways companies can start modernizing: - enterprise business systems that track digital operations - manufacturing execution and web-form systems that replace paper-based collection - central storage of production data rather than isolated spreadsheets - sensor and recipe integrations that bring machine-level signals into usable records
The overall takeaway is that manufacturing data should be made alive—stored digitally, shared meaningfully, and used to improve operations instead of sitting dormant in paper archives.