Operational solution

How can multiple factories report consistently?

Multi-site reporting requires a shared core definition for each measure plus explicit local context. Sites need agreed cutoffs, calendars, units, product mappings, corrections, and quality checks before totals can be compared responsibly.

Discuss your operation Explore solutions

Diagnose

Recognizable symptoms

The problem often appears in several places at once.

The same KPI differs by local formula

Sites submit files at different cutoffs

Product and downtime categories do not map

Corporate totals hide missing data

Diagnose

Likely underlying causes

Confirm causes through observation and records before selecting technology.

Metrics were designed locally

Master data has no cross-site steward

Consolidation accepts incomplete files

Central reporting ignores production context

Diagnose

A proposed workflow

The sequence below is a starting design, not a claim about the current operation.

01
Select decisions and a small common measure setDefine evidence and the exception path
02
Document local formulas and legitimate differencesDefine evidence and the exception path
03
Approve shared definitions and mapping rulesDefine evidence and the exception path
04
Validate site submissions with visible completenessDefine evidence and the exception path
05
Consolidate without hiding local exceptionsDefine evidence and the exception path
06
Review changes through a cross-site governance groupConfirm ownership and handover

Design

Data inputs

Use the minimum information needed and define its source and retention.

Reference	Input or decision to establish
01	Site calendar, shift and cutoff
02	Product, line and unit mappings
03	Measure numerator, denominator and exclusions
04	Submission status, correction and approval

Design

Human responsibilities

Automation routes information; accountable people retain operational decisions.

01Business sponsor owns comparison purpose

Use a representative example to confirm the cause, owner, decision rule, and exception path.

02Site owners attest local submissions

Use a representative example to confirm the cause, owner, decision rule, and exception path.

03Data stewards manage mappings

Use a representative example to confirm the cause, owner, decision rule, and exception path.

04Report owner publishes exceptions and revisions

Use a representative example to confirm the cause, owner, decision rule, and exception path.

Design

Exception handling

The exception path is part of the workflow, not an afterthought.

Missing sites remain labeled in totals

Non-comparable contexts are segmented

Late corrections restate affected periods visibly

Local required metrics can coexist outside the common core

Measure

Measures of success

Baseline each definition and compare like-for-like periods.

Sites submitting by agreed cutoff

Records passing shared validation

Metrics with approved definitions and owners

Restatements and unresolved mapping exceptions

Measure

Limitations

Standardization is not uniformity. Comparing unlike product mixes, planned time, or quality rules can mislead even when arithmetic is correct.

Buying questions

Questions to resolve before work starts

These answers establish a practical default. Actual scope follows the systems, process, data, risks, and responsibilities in view.

01Can this work with our existing systems?

Usually, but compatibility must be confirmed. We first identify supported interfaces, data ownership, update frequency, security constraints, and failure behavior. Where a direct connection is unsafe or unavailable, a controlled file exchange or staged replacement may be more appropriate.

02What happens when an automated step fails?

The design should make failures visible, retain the source record, route the item to an owned exception queue, allow authorized correction, and preserve an audit history. A workflow is incomplete until its exception path is tested.

03How do we know whether the work is worthwhile?

Agree the metric, definition, baseline period, comparison conditions, data source, owner, and review date before changing the workflow. Released capacity is reported separately from cash savings, and operational outcomes are not attributed to software without comparable evidence.

04How are scope, timeline, and price determined?

They depend on process variation, systems and interfaces, data condition, security requirements, testing effort, number of sites, training, and support boundaries. Discovery produces an evidence-based scope rather than an unsupported fixed promise.

Start with one process

Which workflow currently costs your team the most time?

Bring one normal example and one exception. Use them to frame the systems, decisions, controls, and evidence a sensible next step needs.

Discuss your operation

Recognizable symptoms

Likely underlying causes

A proposed workflow

Data inputs

Human responsibilities

Exception handling

Measures of success

Limitations

Questions to resolve before work starts

Related routes through the site

Services

Resources and tools

Illustrative scenarios

Which workflow currently costs your team the most time?