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Dashboards & KPIs for Production

operating context

When KPIs proliferate but nobody trusts the numbers

Production dashboards often proliferate: each function has its own, each report tells different numbers, and nobody can trust a single indicator anymore.

01

KPIs defined in different ways

Issue

The same indicator (OEE, scrap, downtime) has different formulas across departments, systems and reports: every discussion starts with defending one's own number.

Solution

Without a single definition (formula, source, scope), each dashboard builds its own reality and decisions slip into committee.

02

Dashboards designed as pretty cockpits

Issue

Visual impact was the priority, not the operational question: missing drill-downs, arbitrary time comparisons, no path from symptom to cause.

Solution

A useful dashboard starts from operational questions: what is getting worse, why, who must act, by when.

03

No review cadence

Issue

Numbers exist but nobody reads them together in a structured rhythm: KPIs become an archive instead of an improvement lever.

Solution

Short, recurring KPI meetings are needed: clear roles, standard questions, recorded decisions. Otherwise the measurement system stays decorative.

operating method

How we work: 4 phases in sequence

01

KPI workshop

Definition of relevant KPIs for each level: operator, supervisor, plant manager, executive.

KPI auditFormulasOwner
02

Data integration

Connection to data sources: MES, ERP, PLC, databases, spreadsheets.

Indicator modelSemantic layerSingle source
03

Design and development

View design, dashboard development and real-time refresh configuration.

View blueprintDrill-downComparisons
04

Deploy and training

Installation on shop floor displays and devices, user training and feedback iteration.

CadenceRitualsDecision
expected output

The building blocks of a credible industrial dashboard

Value comes from shared definitions, clear storytelling and a reading cadence aligned with operations.

Relationships between indicators, formulas, sources and ownership to avoid apparently similar but inconsistent numbers.

tech spec

Technical spec

explorer
architecture/ 2
operations/ 2
indicator-model.ts
// single KPI definition

Indicator model

Formula: Defined and versioned
Source: Single source of truth
Owner: One per KPI
KPIFormula
// shared KPI vocabulary

Semantic layer

Scope: Plant / line / product
Time: Standard calendar
Hierarchies: Consistent comparisons
SemanticHierarchies
// question-driven dashboards

View blueprint

Questions: Operational before chart
Drill-down: From symptom to cause
Comparisons: Baseline + target
DashboardUX
// KPI review cadence

Governance cadence

Rhythm: Shift / day / week
Roles: Who reads, who decides
Output: Recorded decision
CadenceGovernance
architecture/indicator-model.ts Markdown
next_step.initialize

Need a KPI system that actually drives decisions?

Shared indicator model, view blueprint, reading cadence — numbers become a lever.