ProfitLensConsulting
Započnite1.999 EUR999 EUR

Kako funkcionira

Nijedan korak ne čeka konzultanta. Sustav vas vodi od sirovih podataka do sljedivih preporuka.

  1. Korak 1

    01Učitajte podatke

    Učitajte transakcijske podatke u CSV, tekstualnom ili Excel formatu iz uobičajenih izvoza. Datoteke se pohranjuju šifrirano u okruženju Microsoft Azure u Švedskoj, unutar EU-a.

  2. Korak 2

    02Potvrdite stupce

    Sustav predlaže značenje svakog stupca. Vi pregledavate i potvrđujete mapiranje.

  3. Korak 3

    03Kontrola kvalitete

    Podaci se provjeravaju automatski. Ozbiljne pogreške zaustavljaju obradu, a manja se odstupanja dokumentiraju.

  4. Korak 4

    04Deterministička analiza

    Analitički mehanizam izračunava nalaze i potencijal. Svaki je broj sljediv.

  5. Korak 5

    05AI intervjui

    Pošaljite osobne poveznice ključnim osobama. Inteligentni chatbotovi prikupljaju poslovni kontekst dok analiza traje. Za razliku od zakazanog sastanka, sudionici mogu prekinuti intervju u bilo kojem trenutku i nastaviti kasnije putem iste poveznice – bez usklađivanja kalendara.

  6. Korak 6

    06Izvještaj i razgovor o rezultatima

    Nalazi i intervjui pretvaraju se u izvještaj, nadzornu ploču, prezentaciju i paket materijala za radionicu. AI chatbot objašnjava rezultate i razmatra inicijative.

Što vam je potrebno

  • Transakcijski podaci na razini stavke narudžbe ili računa.
  • Osoba koja može potvrditi značenje stupaca.
  • Neobvezno: osobe koje mogu sudjelovati u AI intervjuima o poslovanju.

Definiran proizvod, fiksna cijena

Standardna analiza stoji 999 EUR bez poreza. Paket materijala za radionicu je uključen. Možete dodati radionicu koju vodi konzultant ili prezentaciju upravi.

Jesu li vaši podaci dovoljno dobri?

Najčešća prepreka nisu vaši podaci – oni su gotovo uvijek dovoljni. Potreban je izvoz sirovih podataka na razini stavke iz vašeg ERP sustava. Ukratko:

Stvarni nazivi nisu potrebni

Ako nazive kupaca ili proizvoda smatrate osjetljivima, slobodno ih maskirajte – zamijenite ih vlastitim oznakama poput "Kupac A" ili "Proizvod 12". Jedini je uvjet da maskiranje bude dosljedno: isti kupac uvijek mora imati isti maskirani naziv, u cijeloj datoteci i na svakom listu. U protivnom se redci ne mogu povezati niti se mogu donijeti ispravni zaključci. Samo nam u koraku mapiranja navedite koji su stupci maskirani.

  • Jedan redak za svaku prodanu stavku – stavke računa ili narudžbe, a ne zaokretna tablica ili sažetak.
  • Cijela godina – kalendarska godina ili posljednjih 12 mjeseci – kako bi bili vidljivi godišnji sezonski i cjenovni učinci.
  • Svaki redak pokazuje kada, kome, koji proizvod, koliko i po kojoj cijeni.
  • Jedinični trošak, ako je dostupan – bez njega prikazujemo cijenu, ali ne i maržu.
  • Sirovi podaci izravno iz sustava bolji su od obrađenih datoteka. Stupci mogu imati bilo koje nazive – pomažemo vam ih mapirati.
  • Excel ili CSV, do 100 MB po datoteci. Dopušteno je više listova. Veći skupovi podataka mogu se podijeliti u više datoteka, primjerice jednu godinu po datoteci, i spojiti funkcijom Proširi povijest.
Prikaži detaljan zahtjev za podacima

Slobodno proslijedite zahtjev svojem kontroleru ili administratoru sustava – u njemu je točno navedeno kako datoteka treba izgledati.

DATA REQUEST – input for pricing analysis (ProfitLens)

1. SCOPE
- Transaction data at line level: each row should correspond to a single invoice line or order line (line item), not a whole order or a summary. An order containing five different items is delivered as five separate rows.
- Period: one full year – a calendar year or the rolling last 12 months up to the last closed month. Two years enable year-over-year comparison, and four complete quarters give rolling twelve-month values. Feel free to update every quarter: new files can extend the history or replace a previous period, and every analysis is saved as a version so progress can be tracked over time.
- All sales within the unit to be analysed. If anything is excluded (entity, country, channel, internal sales) – state what and why.
- For larger groups: analyse one coherent business unit, division or market per analysis, with consistent currency and pricing logic.
- No aggregation, no pivot tables, no subtotals or section headers.

2. FIELDS PER ROW
- Date (REQUIRED) – Transaction date (YYYY-MM-DD). Alternatively year and month as two separate columns.
- Customer number (REQUIRED) – Unique key per customer, consistent throughout the file.
- Customer name (optional) – The customer's name.
- Item number (REQUIRED) – Unique key per product, consistent throughout the file.
- Product name (optional) – The product's name.
- Quantity (REQUIRED) – Units sold on the line. Negative value for credit notes/returns.
- Unit price (REQUIRED) – Net price after discount, in the file's currency. State if it is gross.
- Unit cost (recommended) – Standard cost, purchase price or full cost – state which.
- Amount (optional) – Line total (quantity × price).
- Currency (recommended) – Currency code per row, or state that the whole file is in one currency.
- Discount (optional) – As amount or percent – state which. Back-end rebates in their own column.
- List price (optional) – Gross price before discount, if available.
- Customer segment (recommended) – E.g. industry, size or channel. May be delivered as a separate sheet.
- Sales rep (recommended) – Responsible salesperson or sales code.

3. FORMAT
- Excel (.xlsx) or CSV (UTF-8). Max 100 MB per file. Larger datasets are split by period (e.g. one year per file); each file is uploaded separately and merged with the previous one via Extend history. For datasets over 100,000 rows, CSV is recommended first – it cuts file size substantially and handles hundreds of thousands of rows without hitting the file limit.
- Exactly one header row at the top of each sheet. No merged cells, no empty columns between fields.
- Column names may be your system's own – we map them in the next step.
- Dates as real dates (YYYY-MM-DD). If only year and month exist, deliver them as two separate columns.
- Numbers as numbers, not text. No thousands separators, no currency symbols in cells. One consistent decimal separator.
- Negative amounts with a minus sign, not parentheses.
- Credit lines and returns must be included and flagged (own column or negative quantity).

4. PRICE AND COST
- State clearly whether the price is gross (list price) or net after discount. Never mix in the same column.
- If both list and net price exist: deliver both as separate columns.
- Discount as amount or percent – state which. Back-end rebates and annual bonuses in their own columns if they exist.
- Unit cost: state which cost it is (standard cost, latest purchase price, average full cost) and when it was last updated.
- Currency: a column with currency code, or confirmation that the whole file is in one currency.

5. KEYS AND MASTER DATA
- Customer number and item number must be the same keys throughout the file.
- Real names are not required. Customers and products may be masked (e.g. "Customer A"), but the masking must be consistent: the same customer/product must always carry the same masked name throughout the file and in all sheets. State which columns are masked.
- If customer segment, region, channel or sales rep lives in a separate register – deliver it as its own sheet with the customer number as key.
- If cost or invoiced outcome sits in another system – deliver it as its own sheet and state which key links it to the transactions.

6. OTHER
- The better the data, the sharper the analysis — but the file does not need cleaning. Empty fields, duplicates and odd values are handled and reported in our quality control.
- Feel free to add a short note about known data limitations (system migration, incomplete period, reused item numbers).