Practical approach to data
Piotr joined Lublin Logic Services in March 2021. Previously, for 4 years, he dealt with data in local warehouses near Lublin. He doesn't like theory and clever buzzwords no one in a small company understands. For him, only what's visible in the profit table at the end of the quarter counts. Numbers don't lie, so Piotr bases every decision on hard facts pulled from your sales system.
Facts on the table: What does Piotr do in the office?
In our team, Piotr builds simple neural networks that solve daily problems. He doesn't deal with abstract projects. If you have a problem with stock sitting in the warehouse or being missing at the worst moment, he finds patterns in order history. Recently, for a construction industry client, he prepared a model that reduced unnecessary storage costs by 23%. We tidy up the data and Piotr is exceptionally effective at it.
- Building models predicting sales for the next 14 days.
- Analyzing receipts to detect what customers most often buy in a set.
- Implementing tools that catch invoice errors automatically.
Real results for local business
Piotr believes technology only makes sense when it saves people time. Last year, he closed 37 projects for companies employing 7 to 18 people. One of the more interesting tasks was analysis for a local bakery on Kunickiego St. Piotr calculated that changing the baking hour by 45 minutes would save around 3,200 PLN monthly on electricity and returns. We check facts, we don't guess – this is his main principle for every order.
Groundwork and honesty
He can be brutally honest. If your database is too small or too messy for a neural network to work sensibly, Piotr will tell you at the first meeting. We don't push for expensive solutions that won't work for you. Sometimes a thorough Excel cleaning is enough, which he performs in 3.2 hours, instead of implementing big systems. For him, success is the moment the owner sees savings in black and white.
When not at the code, Piotr is often on-site with clients. He claims you can't properly analyze shop traffic without seeing it with your own eyes. He walks between shelves, looks at how people buy, then returns to the office and translates it into an algorithm. This combination of observation and math gives us the best effects. Sometimes one small change in product layout suggested by his calculations raises sales of a specific group of products by 11% in a month.