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th3chris
01Grown IT landscape
From need to reliable delivery

The software you already run

Every change a risk, every interface a special case — and nobody who knows the whole picture.

Your software has run for years and carries the day-to-day. Only every change to it gets more expensive: one new function touches three systems, two departments and a supplier, an update gets scheduled for the weekend, and the next project needs half a year of lead time first. That situation can be unwound step by step while operations continue.

At a glance
  • Your systems stay in operation while things change
  • Changes become plannable instead of weekend projects
  • New applications get connected once instead of to every system separately
  • Disruptions become visible before your customers call
  • You decide after each step whether the next one follows

Where it starts

The survey

Before anything gets built there is one self-contained first engagement: over one to two weeks I look at which systems you run, how data moves between them, and where things regularly jam. At the end you hold a document your management can read and your IT can use — and it is yours, even if you build nothing with me afterwards or take it to another provider.

Duration
One to two weeks
Price
Fixed, named in advance
Result
A document that is yours
Request the survey

A free 30-minute conversation comes first. If the survey is not worth it for you, you will hear that there.

The underlying problem

Why changes get more expensive over time

In the beginning there was one system. Then came a shop, an industry solution, a supplier with its own interface, a spreadsheet somebody built that has since become indispensable. Every single addition was reasonable. Together they form a web in which nobody can say for certain what happens when you change something in one place.

You do not notice it on the day of the change but weeks later: a report no longer adds up, an order lands in the warehouse twice, a customer gets last quarter's price. Finding the cause takes days, and the search usually costs more than the correction itself.

The reaction is nearly always the same: better to change nothing. That is exactly how software turns from a tool into a constraint. Projects get postponed because nobody wants to carry the risk, and the list of things that should long since work differently grows every year.

The expensive mistake

Rebuilding everything at once sounds like the clean cut and is the riskiest route: months without a visible result, a switchover date on which everything has to work simultaneously, and a legacy system that still needs maintaining alongside.

The way out is rarely a complete rebuild. It is a sequence: first make visible how things connect today, then separate the points that hurt most often, so a change there no longer drags three other systems with it, and only then renew piece by piece — each time with a result that is useful on its own.

What is shifting right now

Building your own was the expensive option for years. AI-assisted development has brought that effort down considerably, and the arithmetic changes with it: what did not pay off three years ago can be viable today. That applies especially where you are paying for access to your own data.

My approach

In which order

What comes first is settled once the survey is done. Work starts where the ratio of effort to relief is best, not where the technology would be most interesting.

  1. 1

    First the point that disrupts most often, solved with a result your people notice in daily work.

  2. 2

    Your business rules get set down once and then apply everywhere alike, for people as much as for systems.

  3. 3

    Renewal happens in stages of a few weeks. Each replaces exactly one area and goes live on its own.

  4. 4

    After each stage you decide whether the next one follows. Switching back stays possible until then.

Concrete delivery

What you actually get

A map of your system landscape

Which systems talk to each other, which data goes where, and where something depends on a single person. A document your management reads and your IT uses.

Clear ownership between systems

For every piece of information it is settled which system owns it and who may change it. That ends the arguments about which figure counts.

One shared access point instead of many

Shop, app, reporting and partners collect their data in one place from now on. When a new application arrives, it is connected in days rather than months.

Changes that arrive checked

Every adjustment runs through the same automatic checks before it lands in the day-to-day. Errors surface while they are still cheap.

An operation you can see

Dashboards show response times, error rates and the state of your important processes. When something breaks, the cause is narrowed down in minutes rather than days.

Renewal in sections

Old parts are replaced one after another while the rest keeps running. You see a result after each section and can stop at any time.

Production experience

Where this already works

Tool distribution: one data basis for every application

At an internationally operating tool distributor, orders, product data and customer access ran over connections that had grown one by one. Today shop, apps and sales systems collect the same figures from one shared place. A new application is plugged in there instead of working through every core system again — and when something changes in one of those systems, not every team has to follow suit separately.

Since 2020
ongoing engagement
One connection
instead of per-system integration
SAP · PIM · CRM
connected

Industrial group: tools without source code brought together

Software from different parts of an industrial group was meant to feel like a single application to its users. For some of it no source code was available, and the teams responsible were not permitted to share it, which ruled out the usual route. It was solved with a purpose-built connection between the programs, documented and safeguarded, without altering the third-party software itself. Afterwards the tools were centrally operable, and the transition between them stayed invisible to users.

No source code
integrated regardless
One application
transition invisible to users

Laboratory equipment: legacy systems stayed in operation

Production and research wanted to analyse running processes promptly without shutting down the existing legacy systems. Both were possible: the old systems kept running, and new data sources could be added without touching the core.

Prompt
running processes analysable
Legacy systems
stayed in operation
... outstanding mind with excellent skills in development; great software architect. Highly recommended if you need to find a professional fast and scalable solution. We've been working together on a project that was rated by Microsoft professionals as "not possible". Together with Christian our team managed to deliver a great working solution/product!
Oscar Angress
Oscar Angress
Cyber Security Consultant · Bosch Engineering GmbH

Clear answers

Questions you might be asking

Do we have to replace our systems for this?

In most cases no, and the order is your decision anyway. Connecting gets you to a first result faster and is the usual entry point. Replacing pays off once maintenance and workarounds cost more than a rebuild, or when a vendor ends support. I build either, and which works out cheaper for you we calculate beforehand.

We pay a recurring fee for hosted software. Is leaving worth it?

It can be, and it comes down to two figures. First the fee: what do you pay per year, and how often has that price risen? Second, access to your own data — with many providers an export, an interface or a higher query volume costs extra, and those items grow with your business. Where both apply and you use only a fraction of the feature set, building your own pays off faster than it did a few years ago, because AI-assisted development has noticeably reduced the effort. The side effect often outweighs the saving: your data sits with you, and the process follows your business rather than the other way round. We work it through on your real figures — and if the subscription turns out cheaper, you will hear that from me.

What does it cost — upfront and ongoing?

The undertaking is broken into stages, each estimated and quoted on its own. You only ever commission the next one, with a result that is useful by itself. Two items recur: operation, whose cost depends on user count, data volume and where it runs, and maintenance when one of your vendors changes something. Working out where it best runs is part of the advice: on your own hardware, with a German provider, or in the environment you already use. That decision affects both the running cost and who can reach your data — we work the options through together before you commit. I put figures on both once the shape is settled, and both appear in the quote rather than the small print. The initial conversation costs you nothing but time.

Who gets access to our data along the way?

I work with test data wherever possible. Where real data is needed, it happens on your systems, with access you grant and can withdraw at any time. I sign a data processing agreement and a non-disclosure agreement before the first access. Your data stays with you, and none of it goes into AI tools.

In what steps does this run?

In stages of a few weeks. Each replaces exactly one area — pricing, for instance — goes live on its own, and can be switched back to the previous state within a day if something does not fit. Undertakings that could otherwise drag on for years are deliberately cut so you could stop after any stage.

Can we carry on working normally in the meantime?

Yes, that is the condition I work under. Old and new parts run side by side, switching happens section by section, and every step can be undone. A cut-over date on which everything has to work at once is deliberately absent from this approach.

We only have a small IT team. Is that enough?

Yes, and it mainly changes the shape. Then it gets built deliberately simply: few components, little that needs regular maintenance, and nothing that would require you to hire a specialist. What your team needs to handle day to day we settle in advance rather than expecting it afterwards.

How do you make sure the quality holds?

Every change automatically runs through the same checks before it reaches the day-to-day: does everything still work that worked before, are known security holes excluded, does the speed hold. That applies whether a person or an AI tool wrote the code — with AI assistance especially, many small changes accumulate, and these checks are why that does not turn into silent repair debt.

You are one person. What happens if you drop out?

Everything produced is yours: the program code sits in your own account, not with me. Along with it come a written description of the procedures, automated tests any successor can use to check that everything still works, and instructions for setting the system up again from scratch. It is built with tools every systems house knows. On larger undertakings I work with your team or bring in established partners.

Get an initial assessment

Do you know where it actually jams?

Write me three sentences about which systems you run and where it hurts most often. You will hear from me personally whether a survey is worth it for you — including when the answer is no.