ProfitLensConsulting
Kom i gang13.990 DKK6.990 DKK

Sådan fungerer det

Intet trin venter på en konsulent. Systemet guider dig fra rå data til sporbare anbefalinger.

  1. Trin 1

    01Upload data

    Upload transaktionsdata som CSV, tekst eller Excel via almindelige eksportfiler. Filerne lagres krypteret i Microsoft Azure i Sverige, inden for EU.

  2. Trin 2

    02Bekræft kolonner

    Systemet foreslår, hvad hver kolonne betyder. Du gennemgår og bekræfter mappingen.

  3. Trin 3

    03Kvalitetskontrol

    Data kontrolleres automatisk. Alvorlige fejl stopper kørslen; mindre afvigelser dokumenteres.

  4. Trin 4

    04Deterministisk analyse

    Motoren beregner resultater og potentiale. Hvert tal er sporbart.

  5. Trin 5

    05AI-interviews

    Send personlige links til nøglepersoner. Intelligente chatbots indsamler forretningskontekst, mens analysen kører. I modsætning til et booket møde kan deltagerne holde pause når som helst og fortsætte senere via samme link – ingen kalendere, der skal koordineres.

  6. Trin 6

    06Rapport og resultatchat

    Analyseresultater og interviews bliver til en rapport, et dashboard, en præsentation og en workshoppakke. En AI-chatbot forklarer resultaterne og drøfter initiativer.

Det skal du bruge

  • Transaktionsdata på ordrelinje- eller fakturaniveau.
  • En person, der kan bekræfte, hvad kolonnerne betyder.
  • Valgfrit: personer, der kan deltage i AI-interviews om forretningen.

Fast produkt, fast pris

Standardanalysen koster 6.990 DKK ekskl. moms. En workshoppakke er inkluderet. En konsulentledet workshop eller ledelsespræsentation kan tilkøbes.

Er dine data gode nok?

Den typiske forhindring er ikke dine data – de er næsten altid tilstrækkelige. Der er brug for et råt udtræk på linjeniveau fra dit ERP-system. Kort fortalt:

Rigtige navne er ikke nødvendige

Hvis kunde- eller produktnavne er følsomme, kan du maskere dem – erstat dem med dine egne koder som "Kunde A" eller "Produkt 12". Det eneste krav er, at maskeringen er konsekvent: Den samme kunde skal altid have det samme maskerede navn i hele filen og på alle ark. Ellers kan rækkerne ikke kobles sammen, og de rigtige konklusioner kan ikke drages. Angiv blot i mappingtrinnet, hvilke kolonner der er maskerede.

  • Én række pr. solgt vare – faktura- eller ordrelinjer, ikke en pivottabel eller opsummering.
  • Ét helt år – et kalenderår eller de seneste 12 måneder – så sæsonudsving og priseffekter gennem et helt år bliver synlige.
  • Hver række viser hvornår, til hvem, hvilket produkt, hvor mange og til hvilken pris.
  • Kostpris pr. enhed, hvis den er tilgængelig – uden den viser vi pris, men ikke margin.
  • Rå data direkte fra systemet er bedre end bearbejdede filer. Kolonnerne må hedde hvad som helst – vi hjælper dig med at mappe dem.
  • Excel eller CSV, op til 100 MB pr. fil. Flere ark er helt fint. Større datasæt kan opdeles i flere filer, f.eks. ét år pr. fil, og samles med Udvid historik.
Vis den detaljerede dataforespørgsel

Send gerne forespørgslen til din controller eller systemadministrator – den beskriver præcist, hvordan filen skal se ud.

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).