ProfitLensConsulting
Započnite1.999 EUR999 EUR

Kako funkcioniše

Nijedan korak ne čeka konsultanta. Sistem vas vodi od sirovih podataka do preporuka sa proverljivom osnovom.

  1. Korak 1

    01Otpremite podatke

    Otpremite podatke o transakcijama u CSV, tekstualnom ili Excel formatu, koristeći uobičajeni izvoz. Datoteke se čuvaju šifrovano na platformi Microsoft Azure u Švedskoj, unutar EU.

  2. Korak 2

    02Potvrdite kolone

    Sistem predlaže značenje svake kolone. Vi pregledate i potvrđujete mapiranje.

  3. Korak 3

    03Kontrola kvaliteta

    Podaci se proveravaju automatski. Ozbiljne greške zaustavljaju obradu; manja odstupanja se dokumentuju.

  4. Korak 4

    04Deterministička analiza

    Analitički mehanizam izračunava nalaze i potencijal. Svaka brojka je proverljiva.

  5. Korak 5

    05AI intervjui

    Pošaljite lične linkove ključnim osobama. Inteligentni četbotovi prikupljaju poslovni kontekst dok analiza traje. Za razliku od zakazanog sastanka, učesnici mogu zastati u bilo kom trenutku i nastaviti kasnije putem istog linka — bez usklađivanja kalendara.

  6. Korak 6

    06Izveštaj i razgovor o rezultatima

    Nalazi i intervjui pretvaraju se u izveštaj, kontrolnu tablu, prezentaciju i paket materijala za radionicu. AI četbot objašnjava rezultate i razmatra inicijative.

Šta vam je potrebno

  • Podaci o transakcijama na nivou stavke porudžbine ili fakture.
  • Osoba koja može da potvrdi značenje kolona.
  • Opciono: osobe koje mogu da odgovore na pitanja o poslovanju u AI intervjuima.

Definisan proizvod, fiksna cena

Standardna analiza košta 999 EUR bez poreza. Paket materijala za radionicu je uključen. Moguće je dodatno ugovoriti radionicu koju vodi konsultant ili prezentaciju rukovodstvu.

Da li su vaši podaci dovoljno dobri?

Najčešća prepreka nisu vaši podaci — oni su gotovo uvek dovoljni. Potreban je izvoz sirovih podataka iz ERP sistema, na nivou stavke. Ukratko:

Pravi nazivi nisu neophodni

Ako su nazivi kupaca ili proizvoda osetljivi, slobodno ih maskirajte — zamenite ih svojim oznakama, poput "Kupac A" ili "Proizvod 12". Jedini uslov je doslednost: isti kupac mora uvek imati isti maskirani naziv, u celoj datoteci i na svakom radnom listu. U suprotnom, redovi se ne mogu povezati niti se mogu izvesti ispravni zaključci. Samo nam u koraku mapiranja navedite koje su kolone maskirane.

  • Jedan red po prodatoj stavci — stavke faktura ili porudžbina, a ne pivot tabela ili zbirni pregled.
  • Cela godina — kalendarska godina ili poslednjih 12 meseci — kako bi se videli sezonski uticaji i efekti cena tokom godine.
  • Svaki red pokazuje kada, kome, koji proizvod, koliko i po kojoj ceni je prodato.
  • Jedinični trošak, ako je dostupan — bez njega prikazujemo cenu, ali ne i maržu.
  • Sirovi podaci direktno iz sistema bolji su od obrađenih datoteka. Kolone mogu imati bilo koje nazive — pomažemo vam da ih mapirate.
  • Excel ili CSV, do 100 MB po datoteci. Više radnih listova nije problem. Veći skupovi podataka mogu se podeliti u više datoteka, na primer po jedna godina u svakoj, i spojiti opcijom Proširi istoriju.
Prikaži detaljan zahtev za podatke

Slobodno prosledite zahtev svom kontroloru ili administratoru sistema — u njemu je precizno navedeno kako datoteka treba da izgleda.

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).