The facility relied on manual spreadsheets for daily plant data, with no shift-level visibility into operational efficiency.
Placeholder and inconsistent job entries defeated naive ingestion, and analysis was limited to monthly retrospectives rather than actionable shift-level insight.
Tensile built an ingestion-to-dashboard platform for an industrial glass-container manufacturer: Python ingestion via the Google Sheets API, a PostgreSQL warehouse with row-level security, engineered efficiency KPIs, web dashboards, and a shift-approval application, plus a composite-business-key engine that resolves dirty job data.
Defect and downtime tracking now runs at shift granularity instead of monthly aggregation.
A composite-business-key engine fixes placeholder and inconsistent job entries that defeated naive ingestion.
A PostgreSQL warehouse with row-level security and engineered efficiency KPIs replaces manual spreadsheets.
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