Klarvo.

Reporting automation for manufacturing

Production, quality and sales reports are compiled by hand from different systems every month, and the same figure comes out differently from each department.

▶ The solution

I automate the reports that are built by hand today, bring scattered data into one source of truth, and build the dashboards management will actually read.

▶ Use case

ERP, production tracking and quality data are combined into one source, and efficiency, scrap and delivery reports are generated from it automatically.

▶ Data you need

ERP tables or exports, production tracking data and quality records.

The industry's data landscape

In manufacturing, data usually lives in the ERP (orders, stock, purchasing), in production tracking (downtime, scrap, shifts) and in quality records. These systems rarely talk to each other; even the same product can carry different codes in each. So the first job is often to bring them together in one table.

Reporting automation means the numbers someone collects, merges and presents by hand every week or month update themselves. Underneath are three jobs: getting the data into one place, calculating each metric with one definition, and showing the result on a dashboard the decision maker can read.

The math behind it

Annual hours = Σ (hours per report × people × repeats per year)

  • Hours per report: time to prepare it once
  • People: how many contribute
  • Repeats per year: 52 for weekly, 12 for monthly
When reports feed from a single source of truth, most of these hours disappear [1]. Work out the annual cost of your own reports with the Manual Reporting Cost tool.

How I work

  1. Week 1

    Report inventory.

    Which report is for whom, built from which source, in how much time, and which one is actually used in a decision. At the end it is clear what gets automated and what gets dropped.

  2. Weeks 2–3

    One source of truth.

    The core metric definitions are written down and agreed with the teams involved. Sources are brought together and pipelines that refresh the data on a schedule are set up.

  3. Weeks 4–5

    Readable dashboards.

    A small number of dashboards for management and teams, written in code to fit the need, with no BI licence attached. Each has an owner and a purpose, and replaces a report that was built by hand.

  4. Final week

    Handover.

    A metric glossary, documentation of the data pipelines and a short training for your team. The system has to run without me; that is the deliverable.

Full service details: Reporting and data infrastructure →

▶ Questions and answers

Reporting automation for manufacturing — what data do you need?

ERP tables or exports, production tracking data and quality records.

When is this the wrong choice?

You have one source and a few reports. A well-built spreadsheet or your software's own reports may be enough. Building infrastructure would be an unnecessary cost. The problem is the decision process, not the data. If the numbers are right but nobody acts on them, that is a management issue. A better dashboard won't fix it.

How does this work start?

With a short intro call. I listen to what you need and tell you plainly whether your data is enough for the job and what the first step should be. I reply to every message within 24 hours.

▶ Concepts

Linked to Wikipedia and Wikidata.

▶ Sources

  1. [1]Wikipedia, Single source of truth, 2026-10. en.wikipedia.org/wiki/Single_source_of_truth
  2. [2]Wikipedia, Extract, transform, load, 2026-10. en.wikipedia.org/wiki/Extract,_transform,_load

▶ Intro call

Let's talk about your situation.

In a 30-minute call I listen to what you need and tell you plainly how I can help.

Book an intro call

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