
Production and logistics KPIs gathered from your ERP, your machines and your spreadsheets into one reliable view, built around the indicators your company actually decides on.
In most manufacturing and logistics SMEs the data is not missing — it is scattered. Part of it lives in the ERP, part in machine telemetry, part in files arriving from suppliers and customers, and part, often the most important part, in spreadsheets that one person updates by hand. The result is that answering a simple question — how many orders are late, how much scrap did a line produce this month — takes hours, and two people starting from different sources reach two different numbers.
A custom business intelligence dashboard steps in exactly here: it reconciles the sources, fixes a shared definition for every indicator and makes it available to whoever has to decide, updated automatically. The value is not in the chart, which is the easy part, but in the integration and reconciliation work underneath — and that is precisely what a visualisation tool takes for granted.

When production, finance and sales each calculate the same indicator differently, meetings are spent arguing about which number is right instead of deciding. Fixing once how each KPI is calculated, and having the system always calculate it that way, removes that argument at the root.

In most SMEs reporting is held together by spreadsheets only one person knows how to update. That is a concrete operational risk: if that person is away, the company loses visibility. Automating collection and calculation restores continuity and frees skilled time for work that matters more.

A monthly report tells you what went wrong once nothing can be done about it. With continuously updated data and agreed alert thresholds, a deviation from the production plan or a delay that is building up surfaces while there is still room to react.
This is the question we get asked most, and the honest answer is that the two are not in conflict. A market BI tool — Power BI, Tableau, Qlik and similar — is excellent at visualisation and at letting users explore data freely. Its premise, though, is that data arrives clean and organised in a coherent model. In SMEs that premise is almost always false, and that is where BI projects stall: not on the graphics, but on the fact that the same item has three different codes in three different systems.
| Aspect | Custom dashboard | General-purpose BI tool |
|---|---|---|
| Messy sources | Integration and reconciliation are part of the project | Assumes data is already consolidated |
| Indicators | Agreed with managers and always calculated the same way | Everyone can build their own version |
| Cost | Project investment, no per-user licence | Subscription that grows with the number of users |
| Best fit | Scattered data, process-specific KPIs, few decision makers | Data already in a warehouse, widespread exploratory analysis |
In practice the most solid project is often hybrid: we build the integration layer and the data model — the hard part — and leave visualisation to whatever tool the company has already adopted, if it has one. If there is nothing in place, a dedicated dashboard avoids introducing a per-user subscription for a need that concerns five people.
The rule we follow is to start from a handful of indicators that already have a decision attached to them. A dashboard with forty charts nobody looks at is worth less than one with six numbers somebody acts on: that is how we decide together what goes into the first version and what can wait.
The typical sources in an SME business intelligence project are the ERP database, machine telemetry, warehouse and shipping systems, the e-commerce platform and a variable number of spreadsheets. We read them through the custom APIs and integrations we build, with connectors to older environments such as AS400 and SAP where needed.
The serious work, though, is not technical: it is reconciliation. The same item or the same customer is almost always coded differently across systems, and until those correspondences are explicit no chart is trustworthy. That is why the first phase of the project is always a mapping of the sources together with department managers, not the choice of a visualisation tool.
If what emerges is that the data is scattered because no system holds it together, the natural path is not a dashboard but a custom ERP, with the dashboard built on top later. We tell you that during analysis, before it becomes a problem. The topic sits within the broader path of business process digitalisation.
A general-purpose BI tool is an excellent visualisation layer, but it assumes the data already arrives clean and in a coherent model. In manufacturing and logistics SMEs that is almost never the case. A custom dashboard includes the work the general tool takes for granted — source integration, master-data reconciliation, agreed indicator definitions — and then shows only what that role needs. The two are not in conflict: we often build the custom integration layer and leave visualisation to a tool the company already uses.
No. A structured ERP makes the work simpler because it concentrates a lot of data in one place, but it is not a prerequisite: you start from the data that exists, even if today it lives in spreadsheets and manual exports. In several projects the dashboard served precisely to make visible how much manual work sat behind those numbers, and became the starting point for a custom ERP later on.
We work in short releases: we pick one area with a clear problem — usually production progress or on-time delivery — and put a real dashboard for that area into the company, fed by real data rather than a mock. From there we extend to other areas reusing the integrations already built. The duration depends almost entirely on how accessible and consistent the data sources are: that is the part we estimate first, because it is what actually moves the timeline.
Yes. Dashboards can be hosted on European infrastructure or directly on-premise, depending on how sensitive the data is and what constraints the company has. The data model and the code remain the client's property, as with all our projects, and processing is designed for GDPR compliance.
If your company's numbers are currently rebuilt by hand from spreadsheets and exports, tell us which decisions you would like to make with up-to-date data. The Codebaker team starts by mapping the sources and will tell you honestly whether you need a dashboard, a custom ERP or simply a fixed integration.