

Why Plants Still Run on Spreadsheets, and Which Ones to Replace First
Why factory spreadsheets survive, a one-week inventory to find the ones that matter, which to replace first, and how to retire each one safely.
Knowledge base
Articles on measuring OEE, running maintenance, closing quality issues and using data on the shop floor. Written by the DBR77 team.


Why factory spreadsheets survive, a one-week inventory to find the ones that matter, which to replace first, and how to retire each one safely.
If you are new to IRIS, read these three articles first.






25 articles


Why factory spreadsheets survive, a one-week inventory to find the ones that matter, which to replace first, and how to retire each one safely.


What GRI 305 and CDP ask a plant for, where each number comes from, four steps to keep it ready, and what IRIS ESG covers. No SASB, TCFD or CSRD support.


One change record with approvers and an effective date, a checklist of routings, instructions and station setup to update, and a check that it reached the line.


LTIF and TRIR formulas with their sources, why hours must come from attendance, how to classify every event, and which leading indicators to report.


A 90-day review of IRIS in six areas, a clear scale, fix or stop decision, and a template for copying a working setup to more lines and plants.


Who decided, when, on what data and why. The fields every decision record needs, extra rules for AI-assisted decisions, and a 15-minute audit test.


One owner per task, ownership that moves only on acceptance, and escalation by role and clock time. Handover rules that hold, including for AI suggestions.


Roll out IRIS in waves: one pilot line, one or two modules, a parallel run and written go criteria. A module order and success measures that keep lines running.


Most factory AI pilots stall on data, not models. The five kinds of operational data AI needs, why the flow matters, and a readiness test for one line.


Three levels of AI in plant operations (observe, advise, act), five questions that set the level for each decision, and how to write approval rules that hold.


Six uses of AI that work in plants today, what each one needs, where AI is still weak, and how to pick a first use case without the autonomous factory hype.


Build a plant operating system business case from your own baseline: measure the losses, value them, count the full cost and set a break-even a pilot can prove.


Compare plant operating systems on your own scenarios, not feature lists: eight criteria, demo questions and a scoring method for COOs, IT and purchasing.


Unify MES, WMS, QMS and CMMS without a big-bang project: shared master data first, then key events, and replace a system only when it blocks the flow.


Most APS plans fail on old assumptions about cycle times, machines, material and crews. The live data that keeps a plan valid, and when to replan or hold.


Lines wait for material when the warehouse sees production too late. The real-time signals your WMS needs, how to set up pull replenishment, what to measure.


Link every defect to its order, machine, shift, material lot and last work order, set rules for when quality calls in maintenance, and verify each fix.


Run maintenance on data: one asset list, work orders ranked by criticality and production impact, inspections triggered by usage and condition, clear KPIs.


OEE can rise while delivery slips and stock grows. Five reasons why, the measures to put next to OEE, and how to build a short plant scorecard that holds up.


Give every factory KPI one definition, one data source, one owner and one view. A four-step method based on ISO 22400, with an OEE definition card example.


How a shop floor signal becomes a task with one owner, a deadline and a verified result. The seven steps of the execution loop and how to measure it.


Siloed tools and spreadsheets cost a plant in retyping, reconciling, late signals and quality escapes. Where the cost hides and how to measure it in two weeks.


ERP plans the business, MES runs production orders, a plant operating system runs all plant work on one record. Who does what, and where MES stops.


A dashboard shows a problem but gives it no owner, deadline or check. The five gaps between the screen and the shop floor, and how to close them.


A plant operating system runs production, maintenance, quality and warehouse work on one data model and turns signals into owned tasks. Here is how.
Start a 14-day trial on your plant's data, or open the interactive demo with sample data.