Operational dashboards & data automation
Built from the spreadsheet your team already keeps. Delivered in days, not quarters, at a fixed price agreed before I start. Run by the people already doing the work — no analyst to hire, no licence, nothing new to learn. It runs entirely inside your own environment.
For operations, quality and finance teams in manufacturing, logistics, construction and industry — companies with real operational data and nobody whose actual job is making sense of it.
Live demos on synthetic data — open one and load your own file.
Where this usually starts
None of these need a platform or a migration. They need the specific thing built, from the data you already have, and run by the team already doing the work.
The work
Working demos on synthetic data. Not screenshots, not case studies. Each one ships the sample workbook it was built from. Change the numbers and watch the charts follow.
For a quality manager who has the scrap number and not the cause.
Rejection rates across a component overhaul line, split by station, shift and inspector. The weeks that breached control limits are marked, and the cost of each cause is attached to it.
For an ops manager who knows orders are late but not which stage made them late.
Order flow from receive to ship for a third-party fulfilment centre, with the bottleneck stage highlighted. On-time performance is broken out against SLA, and the long tail is shown rather than averaged away.
For anyone who needs to know which week the cash gets tight.
A thirteen-week cash forecast for a project contractor, with the trough marked. It also shows where margin is fading against budget and who is paying late.
Same method, other operations.
Data safety
The dashboard is one file that runs in your browser and reads your spreadsheet locally — no upload, no account, no server of mine in the path. Download any demo above, disconnect from the internet, and it still works.
What this skips
There is no server, no account and no data leaving your network, so there is usually nothing for a security review to review. No vendor questionnaire, no data processing agreement to negotiate, no penetration test evidence, no procurement onboarding.
For most teams that removes the slowest part of buying software. Where an automated refresh does need access to a system of yours, that gets written down before anything is built.
Who's building it
I'm Andrew. Five years turning messy operational processes into working software, currently as an external consultant through a technology consultancy working in the humanitarian sector on multi-site operational reporting. Before that I co-founded a marine technology startup and built its environmental data pipelines, automated operations at a logistics company, and spent a year as a data science teaching assistant at Le Wagon taking bootcamp students through Python, SQL and machine learning.
The work keeps taking the same four shapes: reporting pipelines built out of inconsistent field data; dashboards that track indicators against a framework; automation that removes the re-keying between systems; and handing the result over documented well enough that the team runs it without me.
The business is registered in Belgium and I work European hours. Client data stays in the EEA, and if we work together you're dealing with one person in one timezone, not an account manager in front of a team.
I've narrowed to this because it's the highest-value, lowest-cost thing you can do for a team that is already sitting on the data. Most reporting problems don't need a platform, a migration, or a year — they need someone to build the specific thing, quickly. That's a much smaller job than it's usually sold as, and it's the one I want to be doing.
Questions I get asked
No. The dashboard is one file that runs entirely in your browser and reads your spreadsheet locally. There is no server of mine in the path, no account, and no upload step.
Don't take my word for it — go and try it. Every demo above has a “choose a CSV or XLSX” control, the list of columns it expects, and two download links: the sample workbook it was built from, and the dashboard itself. Download the workbook, change some numbers, drop it back in, and watch the charts follow. Then download the dashboard, disconnect, and do it again — offline, with the network tab recording nothing at all.
If we later automate the refresh, the job runs in your tenant on credentials you own, so the answer stays no. On the rare occasion it has to run on my infrastructure instead, I say so plainly, it goes in a data-processing agreement, and you see it written down before anything is built — never discovered afterwards.
If the shape stays the same — same columns, more rows — you drop in the new export and it works. That's the point of building against the file you already produce rather than a system I've invented.
If the shape changes, or if dropping the file in every week has itself become the annoying manual step, that's when a scheduled refresh earns its place. It reads the source overnight and republishes. If a sanity check fails it keeps yesterday's good version rather than publishing something wrong, and it tells someone — a silently stale dashboard is the expensive failure.
No. It opens in a browser and the filters work like a spreadsheet's. It is built around the file your team already produces, so the columns are the ones they named rather than ones I invented. If someone can read that file today, they can read this.
There is no analyst to hire, no per-seat licence, and nothing to administer. The people who already do the job are the ones who use it, which is the point of keeping it this small.
Then you keep everything and nothing stops working.
A single consultant is a real risk, and it deserves a structural answer rather than a reassuring one.
Mostly in scope and speed, and it's a fair question rather than a dig at the tools. Power BI, Tableau and Looker are good at what they do.
The differences that tend to matter: the same answers in days rather than a quarter; no per-viewer licensing, so sending it to forty people costs the same as four; it runs offline and from a file share; and there's no platform to administer or stay subscribed to.
The honest limit: for some cases — many sources, streaming data, multi-gigabyte volumes, a lot of people writing back — you genuinely do need a real platform. When that's your situation I'll tell you so rather than sell you a clever single file that falls over in a year.
Fixed price per engagement, agreed before the work starts. Most first engagements land between €3,000 and €8,000 depending on how many sources are involved and how clean the data is. If yours is likely to fall outside that, I will say so on the call rather than after.
The exact number comes after a call and a look at a sample file. There is an optional monthly retainer afterwards if you want ongoing changes, and the deliverable keeps working whether or not you take it.
The file someone rebuilds a report from every week. I'll tell you what is answerable from it and what is not, and where the data is too thin to support a chart. No call, no pitch, and it's free.
Not comfortable sending a file to someone you have not met? Send the column headers, a screenshot with the numbers blanked out, or two lines describing it. That is usually enough for me to tell you what is answerable.