Measuring the present state
We export customers, suppliers and articles, then count: likely duplicates, empty mandatory fields, spelling variants of one name, inconsistent units of measure.
A report is never better than the records feeding it. In a trading company, after a few years, the same wholesaler exists four times in the ERP, one article carries two codes because it once arrived by the box and once by the unit, and the online shop creates a fresh customer for every guest order. We put all of that back in order, then we set the rules that stop the mess from returning six months later.
The software matters least here. What matters is that one person owns each register and that the rules are written plainly enough for a new joiner to follow without asking.
We export customers, suppliers and articles, then count: likely duplicates, empty mandatory fields, spelling variants of one name, inconsistent units of measure.
Company identities are compared with public business registers and VAT numbers with the European validation service. A correct record matters all the more now that invoices leave in electronic form.
Consistent naming, barcodes, units and packaging factors. We link your internal codes to the listings published on marketplaces, often through a feed tool such as Lengow or Shoppingfeed.
Redundant records are brought together so that accounting documents, payments and sales history afterwards point at the right entry, with no orphaned lines left behind.
How a name and an address are written, which fields are mandatory, and above all who is allowed to create a customer or an article in the system.
We identify consumer accounts inactive beyond your retention period so you can delete or anonymise them in agreement with your DPO.
The assessment is short. The clean-up is deliberately spread over time so that neither current sales nor the monthly accounting close are disturbed.
Through secure remote access, or from an export, we count the errors and show which of them distort your reports the most.
Conventions are written with the people who create records every day, in sales and in the warehouse, not only with managers.
Active customers and selling articles first, the archive last. Every merge is approved by the owner of the register concerned.
Checks at the moment of creation and a monthly quality report stop standards from slipping as soon as attention moves elsewhere.
The most expensive duplicate hides among your articles, not your customers. When one product carries two codes, stock splits between them, and the marketplace listing attached to the first shows nothing available while a full pallet waits in the warehouse. That error costs sales every day and appears in no financial statement: nobody looks for it, because nothing reports what was never sold.
From haste and from integrations, almost every time. A salesperson cannot find the customer because the search used an abbreviated name, so a new record appears. The online shop pushes every guest order across as a new partner. Searching by company identifier, pulling details automatically from public sources and configuring the integration properly removes most of the problem.
Finding the suspicious pairs can, and it saves a great deal of time. The merge itself deserves human approval. Two companies with almost identical names are sometimes a parent and its subsidiary, with separate tax identities, and joining them mixes payments that are very hard to separate afterwards.
Rarely below two hundred and fifty staff. Written rules, entry validation inside Sage, Cegid, EBP or Odoo and a regular quality report handle the bulk of it. A dedicated tool earns its keep once several applications must share the same records in real time and none of them can act as the single reference.
That is almost always the most neglected part. We show how many accounts have gone unused for years, and you decide with your DPO what gets deleted or anonymised. Accounting documents are left alone: they fall under a retention duty of their own, separate from managing a customer list.
Tell us which reports fail to add up and which lists look cluttered. We start by measuring how large the problem really is.
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