Klarvo.

▶ Reporting and data infrastructure

Your reporting problem is not always a reporting problem.

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.

First I find out why it takes days. Then I make sure it never does again.

Atalay Deveci · Updated 2026-10-08

What this service actually is

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.

It is not a software licence sale, and it is not installing a ready-made tool and walking away. Dashboards are the visible part. The hard part is making "revenue" mean the same thing to sales, finance and operations.

The uncomfortable part

Late reports usually look like a missing tool. Most of the time the cause is somewhere else.

  • The same metric has more than one definition.

    Invoiced revenue or collected? Returns deducted or not? When every department calculates with its own definition, the meeting is spent on which number is right instead of on the decision.

  • The data sources don't talk to each other.

    When ERP, CRM, the e-commerce platform and Excel files sit apart, every report means merging by hand. That costs time and carries a new risk of error every time.

  • Plenty of reports, few decisions.

    If the reporting setup produces pages of tables but never says which number should trigger which decision, the problem is focus, not speed. An unnecessary report produced faster is still unnecessary.

I will tell you early which of these applies. If it turns out you don't need a dashboard, I will tell you that too.

▶ 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.

▶ When you should not hire me for this

If any of these is true for you, let's not start this engagement:

  • 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.

  • You need someone to produce reports permanently.

    That is an analyst hire. I build the setup and hand it over; I don't produce reports on an ongoing basis.

  • Access to the source systems can't be given.

    Nothing can be automated without access to the data. Access has to be settled up front.

▶ Engagement shape

When the scope is clear we start with a fixed-scope pilot of 4–6 weeks. When your data situation is unclear, a ~2-week AI & Data Opportunity Assessment first makes clear what is worth automating.

The scope is agreed in writing up front. From week one, the only thing I need is access to the source systems and the people involved.

30-day exit
If it isn't working, you can end the engagement with 30 days' notice.
Invoiced from Türkiye
I invoice through my company registered in Türkiye.
Reply within 24 hours
I reply to every message within 24 hours.

▶ Questions and answers

Do we need a BI tool licence?

No. I write dashboards from scratch in code instead of using an off-the-shelf BI tool, so we're not held back by a tool's limits in design or calculation. If the company already has a tool that works well, staying with it is also an option.

Our data is spread across ERP and Excel. Does that work?

Yes, a large part of the job is pulling exactly that together. In week one we make clear which source is good for what and what needs cleaning up first.

Who runs the dashboards after the project?

Your team. I hand over with a metric glossary, documentation and a short training. If nobody inside works with data, we talk about that up front.

Will all our current reports change?

No. Reports used in decisions get automated, unused ones get dropped. That is what the inventory is for.

▶ Fastest route

Start with one email.

The link below opens an email with the questions that make the first conversation useful already written in. No form, no account. I reply within 24 hours.

hi@klarvoanalytics.com

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