Why implement an industrial dashboard?
An industrial dashboard becomes useful when leadership and managers need a shared reading of production without hunting numbers across multiple tools. In many plants, information is spread across the ERP, MES, CMMS, Excel files, quality tools, and sometimes the machine data itself. The right dashboard does not replace all of that: it brings together what matters for faster decisions.
The real issue is not only displaying indicators. You also need to understand where the problem is, who must act, and which data is authoritative. That shared reading is what turns a reporting screen into a genuinely useful steering tool.
Which indicators belong in an industrial dashboard?
A good industrial dashboard often starts with OEE/TEEP-style metrics, real pace, work order progress, produced quantities, and gaps between target and reality. These indicators give a reliable first view of what is working, what is slowing down, and what is blocked.
Depending on the need, you also add cycle times, available capacity, rejects, rework, and the events that explain deviations. Tools like Power BI can help shape those data, but the core remains the quality of the model and the business definitions.
Understanding downtime and performance losses
The dashboard must also show planned downtime, unplanned downtime, failures, missing materials, machine unavailability, and micro-stops. Without that view, you see the result but not the cause.
Koragence can structure views that highlight recurring causes, the downtime Pareto, MTBF, and MTTR. The goal is to identify what really costs time, then trace it back to the right action quickly.
Integrating quality into the production dashboard
Quality should not stay separate from production. A strong dashboard shows conforming parts, non-conformities, rejects, rework, blocked lots, and pending checks, with a clear link to the line, the machine, and the batch involved.
This view makes audits and drift analysis easier. It also helps quality teams work from a single source of truth instead of rebuilding history across multiple files.
Adapting dashboards to operators, managers, and leadership
Not every role needs to see the same thing. Operators need a simple view of machines, shift targets, and alerts to handle. Production managers need a broader view of lines, delays, rejects, and priorities.
Leadership, on the other hand, mainly needs trends, costs, capacity, and bottlenecks without getting lost in operational detail. One system can therefore provide several views, each adapted to the decision to make.
Connecting ERP, MES, CMMS, quality, and machines
An industrial dashboard becomes truly valuable when it connects the right systems: SAP, Sage X3, Microsoft Dynamics 365, Odoo, a MES, a CMMS, a QMS, or machine data via SCADA, IoT, and IIoT.
When some data remains manual, you can also connect Excel, CSV, or JSON files. The right work is then to choose a clear source of truth for each piece of information and keep the exchanges readable and secure.
Which tools should be used to build an industrial dashboard?
In many projects, Power BI remains an excellent starting point, especially in a Microsoft environment. Grafana can be very useful for technical supervision dashboards, while Tableau or Qlik can also fit depending on the need.
When the need becomes specific, a custom dashboard can be the better fit. It lets you reproduce the real workshop workflows, handle actions directly in the interface, and keep ergonomics that are truly adapted to the teams.
How often should industrial data be refreshed?
Frequency depends on the subject. A machine status or critical incident may require refreshes in a few seconds. Production pace may need near-real-time reading. By contrast, some leadership KPIs may be refreshed once a day or once a week.
The right rhythm is not the fastest possible one: it is the one that helps decisions happen at the right time without unnecessarily overloading systems or cluttering the view with noise.
How Koragence builds an industrial dashboard
Koragence starts with an audit of the existing information system: tools, data, source quality, field usage, and friction points. Then we talk with production, quality, maintenance, and leadership to understand the real decisions the dashboard must support.
From there, we map the data, clarify the KPIs, build a prototype, and validate the views with the relevant teams. The goal is to deliver a first useful version, not a decorative mockup.
What a strong industrial dashboard should deliver
A strong dashboard should first reduce manual reporting and surface the problems that truly cost money more quickly. It should also help identify bottlenecks, quality drifts, and margin losses before they become structural.
The other key value is history. Leadership must be able to review trends without depending on manual exports or Excel files recreated for every committee meeting.
